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Interventions visant à améliorer les pratiques de prescription d'antibiotiques aux patients hospitalisés

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Referencias

References to studies included in this review

Abramowitz 1982 {published data only}

Abramowitz PW, Nold EG, Hatfield SM. Use of clinical pharmacists to reduce cefamandole, cefoxitin and ticarcillin costs. American Journal of Hospital Pharmacy 1982;39:1176‐80. CENTRAL

Adachi 1997 {published data only}

Adachi W, Bolding F, Armstrong R. Experience with vancomycin education and order sheet to limit vancomycin use. Hospital Pharmacy 1997;32:1370‐3. CENTRAL

Akenroye 2014 {published data only}

Akenroye AT, Baskin MN, Samnaliev M, Stack AM. Impact of a bronchiolitis guideline on ED resource use and cost: a segmented time‐series analysis. Pediatrics 2014;133:e227‐34. CENTRAL

Aldeyab 2012 {published data only}

Aldeyab M, Kearney M, Scott M, Aldiab M, Alahmadi Y, Darwish Elhajji F, et al. An evaluation of the impact of antibiotic stewardship on reducing the use of high‐risk antibiotics and its effect on the incidence of Clostridium difficile infection in hospital settings. Journal of Antimicrobial Chemotherapy 2012;67:2988‐96. CENTRAL

Aldeyab 2014 {published data only}

Aldeyab MA, Scott MG, Kearney MP, Alahmadi YM, Magee FA, Conlon G, et al. Impact of an enhanced antibiotic stewardship on reducing methicillin‐resistant Staphylococcus aureus in primary and secondary healthcare settings. Epidemiology and Infection 2014;142:494‐500. CENTRAL

Ananda‐Rajah 2010 {published data only}

Ananda‐Rajah MR, McBryde ES, Buising KL, Redl L, Macisaac C, Cade JF, et al. The role of general quality improvement measures in decreasing the burden of endemic MRSA in a medical‐surgical intensive care unit. Intensive Care Medicine 2010;36:1890‐8. CENTRAL

Annane 2013 {published data only}

Annane D, Maxime V, Faller JP, Mezher C, Clec'h C, Martel P, et al. Procalcitonin levels to guide antibiotic therapy in adults with non‐microbiologically proven apparent severe sepsis: a randomised controlled trial. BMJ Open 2013;3:e002186. CENTRAL

Ansari 2003 {published data only}

Ansari F, Gray K, Nathwani D, Phillips G, Ogston S, Ramsay C, et al. Outcomes of an intervention to improve hospital antibiotic prescribing: interrupted time series with segmented regression analysis. Journal of Antimicrobial Chemotherapy 2003;52(5):842‐8. CENTRAL

Avorn 1988 {published data only}

Avorn J, Soumerai SB, Taylor W, Wessels MR, Janousek J, Weiner M. Reduction of incorrect antibiotic dosing through a structured educational order form. Archives of Internal Medicine 1988;148:1720‐4. CENTRAL

Bailey 1997 {published data only}

Bailey TC, Ritchie DJ, McMullin ST, Kahn M, Reichley RM, Casabar E, et al. A randomized, prospective evaluation of an interventional program to discontinue intravenous antibiotics at two tertiary care teaching institutions. Pharmacotherapy 1997;17(2):277‐81. CENTRAL

Bantar 2006 {published data only}

Bantar C, Franco D, Heft C, Vesco E, Arango C, Izaguirre M, et al. Does a reduction in antibiotic consumption always represent a favorable outcome from an intervention program on prescribing practice?. International Journal of Infectious Diseases 2006;10:231‐5. CENTRAL

Barlow 2007 {published data only}

Barlow G, Nathwani D, Davey P. The effect of implementing the British Thoracic Society community‐acquired pneumonia guidelines on antibiotic prescribing and costs in a UK teaching hospital. Clinical Microbiology and Infection 2006;12:498‐500. CENTRAL
Barlow G, Nathwani D, Williams F, Ogston S, Winter J, Jones M, et al. Reducing door‐to‐antibiotic time in community‐acquired pneumonia: Controlled before‐and‐after evaluation and cost‐effectiveness analysis. Thorax 2007;62(1):67‐74. CENTRAL

Bassetti 2009 {published data only}

Bassetti M, Righi E, Ansaldi F, Molinari MP, Rebesco B, McDermott JL, et al. Impact of limited cephalosporin use on prevalence of methicillin‐resistant Staphylococcus aureus in the intensive care unit. Journal of Chemotherapy 2009;21:633‐8. CENTRAL

Baysari 2013 {published data only}

Baysari MT, Oliver K, Egan B, Li L, Richardson K, Sandaradura I, et al. Audit and feedback of antibiotic use: utilising electronic prescription data. Applied Clinical Informatics 2013;4:583‐95. CENTRAL

Bell 2014 {published data only}

Bell S, Davey P, Nathwani D, Marwick C, Vadiveloo T, Sneddon J, et al. Risk of Acute Kidney Injury with gentamicin as surgical prophylaxis. JASN Journal of the American Society of Nephrologists 2014;25:2625‐32. CENTRAL

Belliveau 1996 {published data only}

Belliveau PP, Rothman AL, Maday CE. Limiting vancomycin use to combat vancomycin‐resistant Enterococcus faecium. American Journal of Health‐System Pharmacy 1996;53(13):1570‐5. CENTRAL

Benson 2014 {published data only}

Benson JM. Incorporating pharmacy student activities into an antimicrobial stewardship program in a long‐term acute care hospital. American Journal of Health‐System Pharmacy 2014;71:227‐30. CENTRAL

Berild 2002 {published data only}

Berild D, Ringertz SH, Aabyholm G, Lelek M, Fosse B. Impact of an antibiotic policy on antibiotic use in a paediatric department. Individual based follow‐up shows that antibiotics were chosen according to diagnoses and bacterial findings. International Journal of Antimicrobial Agents 2002;20:333‐8. CENTRAL

Borde 2014a {published and unpublished data}

Borde JP, Kaier K, Steib‐Bauert M, Vach W, Geibel‐Zehender A, Busch H, et al. Feasibility and impact of an intensified antibiotic stewardship programme targeting cephalosporin and fluoroquinolone use in a tertiary care university medical center. BMC Infectious Diseases 2014;14:201. CENTRAL

Borde 2014b {published and unpublished data}

Borde JP, Batin N, Rieg S, Feik R, Reimling C, Kern WV, et al. Adherence to an antibiotic stewardship bundle targeting Staphylococcus aureus blood stream infections at a 200‐bed community hospital. Infection 2014;42(4):713‐9. CENTRAL

Borde 2015a {published and unpublished data}

Borde JP, Kern WV, Hug M, Steib‐Bauert M, With KD, Busch HJ, et al. Implementation of an intensified antibiotic stewardship programme targeting third‐generation cephalosporin and fluoroquinolone use in an emergency medicine department. Emergency Medicine Journal (EMJ) 2015;32(7):509‐15. CENTRAL

Borde 2015b {published and unpublished data}

Borde JP, Litterst S, Ruhnke M, Feik R, Hubner J, deWith K, et al. Implementing an intensified antibiotic stewardship programme targeting cephalosporin and fluoroquinolone use in a 200‐bed community hospital in Germany. Infection 2015;43(1):45‐50. CENTRAL

Bouadma 2010 {published data only}

Bogner J, Nitschmann S. Management of antibiotics in regard of procalcitonin levels: PRORATA trial (PROcalcitonin to Reduce Antibiotic Treatments in Acutely ill patients). Internist 2010;51:1582‐4. CENTRAL
Bouadma L, Luyt CE, Tubach F, Cracco C, Alvarez A, Schwebel C, et al. Use of procalcitonin to reduce patients' exposure to antibiotics in intensive care units (PRORATA trial): a multicentre randomised controlled trial. Lancet 2010;375:463‐74. CENTRAL

Bouza 2004 {published data only}

Bouza E, Sousa D, Munoz P, Rodriguez‐Creixems M, Fron C, Lechuz JG. Bloodstream infections: a trial of the impact of different methods of reporting positive blood culture results. Clinical Infectious Diseases 2004;39(8):1161‐9. CENTRAL

Bouza 2007 {published data only}

Bouza E, Torres MV, Radice C, Cercenado E, de Diego R, Sanchez‐Carrillo C, et al. Direct E‐test (AB Biodisk) of respiratory samples improves antimicrobial use in ventilator‐associated pneumonia. Clinical Infectious Diseases: an official publication of the Infectious Diseases Society of America 2007;44:382‐7. CENTRAL

Bradley 1999 {published data only}

Bradley SJ, Wilson ALT, Allen MC, Sher HA, Goldstone AH, Scott GM. The control of hyperendemic glycopeptide‐resistant Enterococcus spp. on a haematology unit by changing antibiotic usage. Journal of Antimicrobial Chemotherapy 1999;43(2):261‐6. CENTRAL

Bruins 2005 {published data only}

Bruins M, Oord H, Bloembergen P, Wolfhagen M, Casparie A, Degener J, et al. Lack of effect of shorter turnaround time of microbiological procedures on clinical outcomes: a randomised controlled trial among hospitalised patients in the Netherlands. European Journal of Clinical Microbiology and Infectious Diseases 2005;24(5):305‐13. CENTRAL

Buising 2008a {published and unpublished data}

Buising KL, Thursky KA, Robertson MB, Black JF, Street AC, Richards MJ, et al. Electronic antibiotic stewardship ‐ reduced consumption of broad‐spectrum antibiotics using a computerized antimicrobial approval system in a hospital setting. Journal of Antimicrobial Chemotherapy 2008;62:608‐16. CENTRAL

Buising 2008b {published and unpublished data}

Buising KL, Thursky KA, Black JF, MacGregor L, Street AC, Kennedy MP, et al. Improving antibiotic prescribing for adults with community acquired pneumonia: Does a computerised decision support system achieve more than academic detailing alone? A time series analysis. BMC Medical Informatics & Decision Making 2008;8:35. [DOI: 10.1186/1472‐6947‐8‐35]CENTRAL

Bunz 1990 {published data only}

Bunz D, Gupta S, Jewesson P. Metronidazole cost containment: a two‐stage intervention. Hospital Formulary 1990;25(11):1167‐77. CENTRAL

Burton 1991 {published data only}

Burton ME, Ash CL, Hill DP, Handy T, Shepherd MD, Vasko MR. A controlled trial of the cost benefit of computerized bayesian aminoglycoside administration. Clinical Pharmacology Therapeutics 1991;49(6):685‐94. CENTRAL

Buyle 2010 {published data only}

Buyle F, Vogelaers D, Peleman R, Van Maele G, Robays H. Implementation of guidelines for sequential therapy with fluoroquinolones in a Belgian hospital. Pharmacy World & Science 2010;32:404‐10. CENTRAL

Calfee 2003 {published data only}

Calfee DP, Brooks J, Zirk NM, Giannetta ET, Scheld WM, Farr BM. A pseudo‐outbreak of nosocomial infections associated with the introduction of an antibiotic management programme. Journal of Hospital Infection 2003;55(1):26‐32. CENTRAL

Calil 2001 {published data only}

Calil R, Marba ST, Von Nowakonski A, Tresoldi AT. Reduction in colonization and nosocomial infection by multiresistant bacteria in a neonatal unit after institution of educational measures and restriction in the use of cephalosporins. American Journal of Infection Control 2001;29(3):133‐8. CENTRAL

Camins 2009 {published data only}

Camins BC, King MD, Wells JB, Googe HL, Patel M, Kourbatova EV, et al. Impact of an antimicrobial utilization program on antimicrobial use at a large teaching hospital: a randomized controlled trial. Infection Control and Hospital Epidemiology 2009;30:931‐8. CENTRAL

Carling 2003 {published data only}

Carling P, Fung T, Killion A, Terrin N, Barza M. Favorable impact of a multidisciplinary antibiotic management program conducted during 7 years. Infection Control and Hospital Epidemiology 2003;24(9):699‐706. CENTRAL

Chan 2011 {published data only}

Chan YY, Lin TY, Huang CT, Deng ST, Wu TL, Leu HS, et al. Implementation and outcomes of a hospital‐wide computerised antimicrobial stewardship programme in a large medical centre in Taiwan. International Journal of Antimicrobial Agents 2011;38(6):486‐92. CENTRAL

Chan 2015 {published data only}

Chan S, Hossain J, Di Pentima MC. Implications and impact of prior authorization policy on vancomycin use at a tertiary pediatric teaching hospital. Pediatric Infectious Disease Journal 2015;34(5):506‐8. CENTRAL

Chandy 2014 {published and unpublished data}

Chandy SJ, Naik GS, Charles R, Jeyaseelan V, Naumova EN, Thomas K, et al. The impact of policy guidelines on hospital antibiotic use over a decade: A segmented time series analysis. PLoS ONE 2014;9(3):e92206. CENTRAL

Charbonneau 2006 {published data only}

Charbonneau P, Parienti JJ, Thibon P, Ramakers M, Daubin C, du Cheyron D, et al. Fluoroquinolone use and methicillin‐resistant Staphylococcus aureus isolation rates in hospitalized patients: a quasi experimental study. Clinical Infectious Diseases 2006;42(6):778‐84. CENTRAL

Cheng 2009 {published data only}

Cheng VCC, To KKW, Li IWS, Tang BSF, Chan JFW, Kwan S, et al. Antimicrobial stewardship program directed at broad‐spectrum intravenous antibiotics prescription in a tertiary hospital. European Journal of Clinical Microbiology & Infectious Diseases 2009;28:1447‐56. CENTRAL

Christ‐Crain 2004 {published data only}

Christ‐Crain M, Jaccard‐Stolz D, Bingisser R, Gencay MM, Huber PR, Tamm M, et al. Effect of procalcitonin‐guided treatment on antibiotic use and outcome in lower respiratory tract infections: cluster‐randomised, single‐blinded intervention trial. Lancet 2004;363(9409):600‐7. CENTRAL

Christ‐Crain 2006 {published data only}

Christ‐Crain M, Stolz D, Bingisser R, Muller C, Miedinger D, Huber PR, et al. Procalcitonin guidance of antibiotic therapy in community‐acquired pneumonia: a randomized trial. American Journal of Respiratory and Critical Care Medicine 2006;174(1):84‐93. CENTRAL

Chu 2003 {published data only}

Chu LA, Bratzler DW, Lewis RJ, Murray C, Moore L, Shook C, et al. Improving the quality of care for patients with pneumonia in very small hospitals. Archives of Internal Medicine 2003;163(3):326‐32. CENTRAL

Clerc 2014 {published data only}

Clerc O, Prod'hom G, Senn L, Jaton K, Zanetti G, Calandra T, et al. Matrix‐assisted laser desorption ionization time‐of‐flight mass spectrometry and PCR‐based rapid diagnosis of Staphylococcus aureus bacteraemia. Clinical Microbiology and Infection2014; Vol. 20, issue 4:355‐60. CENTRAL

Climo 1998 {published data only}

Climo MW, Israel DS, Wong ES, Williams D, Coudron P, Markowitz SM. Hospital‐wide restriction of clindamycin: effect on the incidence of Clostridium difficile‐associated diarrhea and cost. Annals of Internal Medicine 1998;128(12 Pt 1):989‐95. CENTRAL

Connor 2007 {published data only}

Connor DM, Binkley S, Fishman NO, Gasink LB, Linkin D, Lautenbach E. Impact of automatic orders to discontinue vancomycin therapy on vancomycin use in an antimicrobial stewardship program. Infection Control and Hospital Epidemiology 2007;28:1408‐10. CENTRAL

Cook 2011a {published data only}

Cook PP, Catrou PG, Christie JD, Young PD, Polk RE. Reduction in broad‐spectrum antimicrobial use associated with no improvement in hospital antibiogram. Journal of Antimicrobial Chemotherapy 2004;53:853‐9. CENTRAL
Cook PP, Rizzo S, Gooch M, Jordan M, Fang X, Hudson S. Sustained reduction in antimicrobial use and decrease in methicillin‐resistant Staphylococcus aureus and Clostridium difficile infections following implementation of an electronic medical record at a tertiary‐care teaching hospital. Journal of Antimicrobial Chemotherapy 2011;66:205‐9. CENTRAL

Cook 2011b {published data only}

Cook PP, Gooch M, Rizzo S. Reduction in fluoroquinolone use following introduction of ertapenem into a hospital formulary is associated with improvement in susceptibility of Pseudomonas aeruginosa to group 2 carbapenems: a 10‐year study. Antimicrobial Agents & Chemotherapy 2011;55:5597‐601. CENTRAL

Cortoos 2011 {published data only}

Cortoos PJ, Gilissen C, Mol PG, Van den Bossche F, Simoens S, Willems L, et al. Empirical management of community‐acquired pneumonia: impact of concurrent A/H1N1 influenza pandemic on guideline implementation. Journal of Antimicrobial Chemotherapy 2011;66:2864‐71. CENTRAL

Danaher 2009 {published data only}

Danaher PJ, Milazzo NA, Kerr KJ, Lagasse CA, Lane JW. The Antibiotic Support Team ‐ a successful educational approach to antibiotic stewardship. Military Medicine 2009;174:201‐5. CENTRAL

Dancer 2013 {published data only}

Dancer S, Kirkpatrick P, Corcoran D, Christison F, Farmer D, Robertson C. Approaching zero: Temporal effects of a restrictive antibiotic policy on hospital‐acquired Clostridium difficile, extended‐spectrum beta‐lactamase‐producing coliforms and meticillin‐resistant Staphylococcus aureus. International Journal of Antimicrobial Agents 2013;41:137‐42. CENTRAL

Dean 2001 {published data only}

Dean NC, Silver MP, Bateman KA, James B, Hadlock CJ, Hale D. Decreased mortality after implementation of a treatment guideline for community‐acquired pneumonia. American Journal of Medicine 2001;110(6):451‐7. CENTRAL

Dean 2006 {published data only}

Dean NC, Bateman KA, Donnelly SM, Silver MP, Snow GL, Hale D. Improved clinical outcomes with utilization of a community‐acquired pneumonia guideline. Chest 2006;130(3):794‐9. CENTRAL

de Champs 1994 {published data only}

de Champs C, Franchineau P, Gourgand JM, Loriette Y, Gaulme J, Sirot J. Clinical and bacteriological survey after change in aminoglycoside treatment to control an epidemic of Enterobacter cloacae. Journal of Hospital Infection 1994;28(3):219‐29. CENTRAL

Dempsey 1995 {published data only}

Dempsey CL. Nursing home‐acquired pneumonia: outcomes from a clinical process improvement program. Pharmacotherapy 1995;15(1 Pt 2):33S‐8S. CENTRAL

Ding 2013 {published data only}

Ding J, Chen Z, Feng K. Procalcitonin‐guided antibiotic use in acute exacerbations of idiopathic pulmonary fibrosis. International Journal of Medical Sciences 2013;10:903‐7. CENTRAL

Dranitsaris 2001 {published data only}

Dranitsaris G, Spizzirri D, Pitre M, McGeer A. A randomized trial to measure the optimal role of the pharmacist in promoting evidence‐based antibiotic use in acute care hospitals. International Journal of Technology Assessment in Health Care 2001;17(2):171‐80. CENTRAL

Dua 2014 {published data only}

Dua A, Desai SS, Seabrook GR, Brown KR, Lewis BD, Rossi PJ, et al. The effect of Surgical Care Improvement Project measures on national trends on surgical site infections in open vascular procedures. Journal of Vascular Surgery 2014;60:1635‐9. CENTRAL

Dull 2008 {published data only}

Dull D, Baird SK, Dulac J, Fox L. Improving prophylactic perioperative antibiotic utilization in a hospital system. Journal for Healthcare Quality 2008;30:48‐56. CENTRAL

Duvoisin 2014 {published data only}

Duvoisin G, Fischer C, Maucort‐Boulch D, Giannoni E. Reduction in the use of diagnostic tests in infants with risk factors for early‐onset neonatal sepsis does not delay antibiotic treatment. Swiss Medical Weekly 2014;144:w13981. CENTRAL

Elligsen 2012 {published data only}

Elligsen M, Walker SAN, Pinto R, Simor A, Mubareka S, Rachlis A, et al. Audit and feedback to reduce broad‐spectrum antibiotic use among intensive care unit patients: a controlled interrupted time series analysis. Infection Control and Hospital Epidemiology 2012;33:354‐61. CENTRAL

Esposito 2011 {published data only}

Esposito S, Tagliabue C, Picciolli I, Semino M, Sabatini C, Consolo S, et al. Procalcitonin measurements for guiding antibiotic treatment in pediatric pneumonia. Respiratory Medicine 2011;105:1939‐45. CENTRAL

Everitt 1990 {published data only}

Everitt DE, Soumerai SB, Avorn J, Klapholz H, Wessels M. Changing surgical antimicrobial prophylaxis practices through education targeted at senior department leaders. Infection Control and Hospital Epidemiology 1990;11(11):578‐83. CENTRAL

Farinas 2012 {published data only}

Farinas M, Saravia G, Calvo‐Montes J, Benito N, Martinez‐Garde J, Farinas‐Alvarez C, et al. Adherence to recommendations by infectious disease consultants and its influence on outcomes of intravenous antibiotic‐treated hospitalized patients. BMC Infectious Diseases 2012;12:292. CENTRAL

Fine 2003 {published data only}

Fine MJ, Stone RA, Lave JR, Hough LJ, Obrosky DS, Mor MK, et al. Implementation of an evidence‐based guideline to reduce duration of intravenous antibiotic therapy and length of stay for patients hospitalized with community‐acquired pneumonia: a randomized controlled trial. American Journal of Medicine 2003;115(5):343‐51. CENTRAL

Fitzpatrick 2008 {published data only}

Fitzpatrick RW, Edwards CMC. Evaluation of a tool to benchmark hospital antibiotic prescribing in the United Kingdom. Pharmacy World & Science 2008;30:73‐8. CENTRAL

Fowler 2007 {published data only}

Fowler S, Webber A, Cooper BS, Phimister A, Price K, Carter Y, et al. Successful use of feedback to improve antibiotic prescribing and reduce Clostridium difficile infection: a controlled interrupted time series. Journal of Antimicrobial Chemotherapy 2007;59:990‐5. CENTRAL

Franz 2004 {published data only}

Franz AR, Bauer K, Schalk A, Garland SM, Bowman ED, Rex K, et al. Measurement of interleukin 8 in combination with C‐reactive protein reduced unnecessary antibiotic therapy in newborn infants: a multicenter, randomized, controlled trial. Pediatrics 2004;114(1):1‐8. CENTRAL

Fraser 1997 {published data only}

Fraser GL, Stogsdill P, Dickens JD, Wennberg DE, Smith RP, Prato S. Antibiotic optimization: an evaluation of patient safety and economic outcomes. Archives of Internal Medicine 1997;157:1689‐94. CENTRAL

Fridkin 2002 {published data only}

Fridkin SK, Lawton R, Edwards JR, Tenover FC, McGowan JE, Gaynes RP. Monitoring antimicrobial use and resistance: comparison with a national benchmark on reducing vancomycin use and vancomycin‐resistant enterococci. Emerging Infectious Diseases 2002;8(7):702‐7. CENTRAL

Friedberg 2009 {published data only}

Friedberg MW, Mehrotra A, Linder JA. Reporting hospitals' antibiotic timing in pneumonia: adverse consequences for patients?. American Journal of Managed Care 2009;15:137‐44. CENTRAL

Fukuda 2014 {published data only}

Fukuda T, Watanabe H, Ido S, Shiragami M. Contribution of antimicrobial stewardship programs to reduction of antimicrobial therapy costs in community hospital with 429 beds ‐ before‐after comparative two‐year trial in Japan. Journal of Pharmaceutical Policy and Practice 2014;7:10. CENTRAL

Gerding 1985 {published data only}

Gerding DN, Larson TA. Aminoglycoside resistance in gram‐negative bacilli during increased amikacin use. Comparison of experience in 14 United States hospitals with experience in the Minneapolis Veterans Administration Medical Center. American Journal of Medicine 1985;79(1A):1‐7. CENTRAL

Goldstein 2009 {published data only}

Goldstein EJ, Citron DM, Peraino V, Elgourt T, Meibohm AR, Lu S. Introduction of ertapenem into a hospital formulary: effect on antimicrobial usage and improved in vitro susceptibility of Pseudomonas aeruginosa. Antimicrobial Agents & Chemotherapy 2009;53:5122‐6. CENTRAL

Grohs 2014 {published data only}

Grohs P, Kerneis S, Sabatier B, Lavollay M, Carbonnelle E, Rostane H, et al. Fighting the spread of AmpC‐hyperproducing Enterobacteriaceae: beneficial effect of replacing ceftriaxone with cefotaxime. Journal of Antimicrobial Chemotherapy 2014;69:786‐9. CENTRAL

Gulmezoglu 2007 {published data only}

Gulmezoglu AM, Langer A, Piaggio G, Lumbiganon P, Villar J, Grimshaw J. Cluster randomised trial of an active, multifaceted educational intervention based on the WHO Reproductive Health Library to improve obstetric practices. BJOG: An International Journal of Obstetrics & Gynaecology 2007;114:16‐23. CENTRAL

Gums 1999 {published data only}

Gums JG, Yancey RW, Hamilton CA, Kubilis PS. A randomized, prospective study measuring outcomes after antibiotic therapy intervention by a multidisciplinary consult team. Pharmacotherapy 1999;19(12):1369‐77. CENTRAL

Gupta 1989 {published data only}

Gupta S, Bachand RL, Jewesson PJ. Impact of a two‐stage intervention program on cefazolin usage at a major teaching hospital. Hospital Formulary 1989;24(1):41‐4, 46. CENTRAL

Hadi 2008 {published data only}

Hadi U, Keuter M, Van Asten H, Van Den Broek P, on behalf of the study group Antimicrobial Resistance in Indonesia Prevalence, Prevention. Optimizing antibiotic usage in adults admitted with fever by a multifaceted intervention in an Indonesian governmental hospital. Tropical Medicine & International Health 2008;13:888‐99. CENTRAL

Halm 2004 {published data only}

Halm EA, Horowitz C, Silver A, Fein A, Dlugacz YD, Hirsch B, et al. Limited impact of a multicenter intervention to improve the quality and efficiency of pneumonia care. Chest 2004;126(1):100‐7. CENTRAL

Hess 1990 {published data only}

Hess DA, Mahoney CD, Johnson PN, Corrao WM, Fisher A. Integration of clinical and administrative strategies to reduce expenditures for antimicrobial agents. American Journal of Hospital Pharmacy 1990;47:585‐91. CENTRAL

Himmelberg 1991 {published data only}

Himmelberg CJ, Pleasants RA, Weber DJ, Kessler JM, Samsa GP, Spivey JM, et al. Use of antimicrobial drugs in adults before and after removal of a restriction policy. American Journal of Public Health 1991;48:1220‐7. CENTRAL

Hitti 2012 {published data only (unpublished sought but not used)}

Hitti EA, Lewin JJ, Lopez J, Hansen J, Pipkin M, Itani T, et al. Improving door‐to‐antibiotic time in severely septic emergency department patients. Journal of Emergency Medicine 2012;42:462‐9. CENTRAL

Hochreiter 2009 {published data only}

Hochreiter M, Kohler T, Schweiger AM, Keck FS, Bein B, von Spiegel T, et al. Procalcitonin to guide duration of antibiotic therapy in intensive care patients: a randomized prospective controlled trial. Critical Care (London, England) 2009;13:R83. CENTRAL

Huber 1982 {published data only}

Huber SL, Patry RA, Hudson HD. Influencing drug use through prescribing restrictions. American Journal of Hospital Pharmacy 1982;39:1898‐901. CENTRAL

Hulgan 2004 {published data only}

Hulgan T, Rosenbloom ST, Hargrove F, Talbert DA, Arbogast PG, Bansal P, et al. Oral quinolones in hospitalized patients: an evaluation of a computerized decision support intervention. Journal of Internal Medicine 2004;256(4):349‐57. CENTRAL

Inaraja 1986 {published data only}

Inaraja MT, Paloma JM, Giraldez J, Idoate AJ, Hualde S. Computer‐assisted antimicrobial‐use monitoring. American Journal of Hospital Pharmacy 1986;43:664‐70. CENTRAL

Jensen 2011 {published data only}

Jensen JU, Hein L, Lundgren B, Bestle MH, Mohr TT, Andersen MH, et al. Procalcitonin‐guided interventions against infections to increase early appropriate antibiotics and improve survival in the intensive care unit: a randomized trial. Critical Care Medicine 2011;39:2048‐58. CENTRAL

Jobson 2015 {published data only}

Jobson M, Sandrof M, Valeriote T, Liberty AL, Walsh‐Kelly C, Jackson C. Decreasing time to antibiotics in febrile patients with central lines in the emergency department. Pediatrics 2015;135:e187‐95. CENTRAL

Jump 2012 {published data only}

Jump R, Olds D, Seifi N, Kypriotakis G, Jury L, Peron E, et al. Effective antimicrobial stewardship in a long‐term care facility through an infectious disease consultation service: Keeping a LID on antibiotic use. Infection Control and Hospital Epidemiology 2012;33:1185‐92. CENTRAL

Kallen 2009 {published and unpublished data}

Kallen AJ, Thompson A, Ristaino P, Chapman L, Nicholson A, Sim BT, et al. Complete restriction of fluoroquinolone use to control an outbreak of Clostridium difficile infection at a community hospital. Infection Control & Hospital Epidemiology 2009;30:264‐72. CENTRAL

Kanwar 2007 {published data only}

Kanwar M, Brar N, Khatib R, Fakih MG. Misdiagnosis of community‐acquired pneumonia and inappropriate utilization of antibiotics: side effects of the 4‐h antibiotic administration rule. Chest 2007;131:1865‐9. CENTRAL

Kerremans 2008 {published data only}

Kerremans JJ, Verboom P, Stijnen T, Hakkaart‐van Roijen L, Goessens W, Verbrugh HA, et al. Rapid identification and antimicrobial susceptibility testing reduce antibiotic use and accelerate pathogen‐directed antibiotic use. Journal of Antimicrobial Chemotherapy 2008;61:428‐35. CENTRAL

Kerremans 2009 {published data only}

Kerremans JJ, van der Bij AK, Goessens W, Verbrugh HA, Vos MC. Immediate incubation of blood cultures outside routine laboratory hours of operation accelerates antibiotic switching. Journal of Clinical Microbiology 2009;47:3520‐3. CENTRAL

Khan 2003 {published data only}

Khan R, Cheesbrough J. Impact of changes in antibiotic policy on Clostridium difficile‐associated diarrhoea (CDAD) over a five‐year period in a district general hospital. Journal of Hospital Infection 2003;54(2):104‐8. CENTRAL

Kim 2008 {published data only}

Kim JY, Sohn JW, Park DW, Yoon YK, Kim YM, Kim MJ. Control of extended‐spectrum {beta}‐lactamase‐producing Klebsiella pneumoniae using a computer‐assisted management program to restrict third‐generation cephalosporin use. Journal of Antimicrobial Chemotherapy 2008;62:416‐21. CENTRAL

Knudsen 2014 {published data only}

Knudsen JD, Andersen SE, Bispebjerg Intervention Group. A multidisciplinary intervention to reduce infections of ESBL‐ and AmpC‐producing, gram‐negative bacteria at a University Hospital. PLoS ONE 2014;9:e86457. CENTRAL

Kristoffersen 2009 {published data only}

Kristoffersen KB, Sogaard OS, Wejse C, Black FT, Greve T, Tarp B, et al. Antibiotic treatment interruption of suspected lower respiratory tract infections based on a single procalcitonin measurement at hospital admission ‐ a randomized trial. Clinical Microbiology & Infection 2009;15:481‐7. CENTRAL

Kritchevsky 2008 {published data only}

Kritchevsky SB, Braun BI, Bush AJ, Bozikis MR, Kusek L, Burke JP, et al. The effect of a quality improvement collaborative to improve antimicrobial prophylaxis in surgical patients: a randomized trial. Annals of Internal Medicine 2008;149:472‐80. CENTRAL

Kumana 2001 {published data only}

Kumana CR, Ching TY, Kong Y, Ma EC, Kou M, Lee RA, et al. Curtailing unnecessary vancomycin usage in a hospital with high rates of methicillin resistant Staphylococcus aureus infections. British Journal of Clinical Pharmacology 2001;52(4):427‐32. CENTRAL

Lacroix 2014 {published data only}

Lacroix L, Manzano S, Vandertuin L, Hugon F, Galetto‐Lacour A, Gervaix A. Impact of the lab‐score on antibiotic prescription rate in children with fever without source: a randomized controlled trial. PLoS One 2014;9:e115061. CENTRAL

Lafaurie 2012 {published data only}

Lafaurie M, Porcher R, Donay JL, Touratier S, Molina JM. Reduction of fluoroquinolone use is associated with a decrease in methicillin‐resistant Staphylococcus aureus and fluoroquinolone‐resistant Pseudomonas aeruginosa isolation rates: a 10 year study. Journal of Antimicrobial Chemotherapy 2012;67:1010‐5. CENTRAL

Landgren 1988 {published data only}

Landgren FT, Harvey KJ, Mashford ML, Moulds RFW, Guthrie B, Hemming M. Changing antibiotic prescribing by educational marketing. Medical Journal of Australia 1988;149:595‐9. CENTRAL

Landman 1999 {published data only}

Landman D, Chockalingam M, Quale JM. Reduction in the incidence of methicillin‐resistant Staphylococcus aureus and ceftazidime‐resistant Klebsiella pneumoniae following changes in a hospital antibiotic formulary. Clinical Infectious Diseases 1999;28(5):1062‐6. CENTRAL

LaRosa 2007 {published data only}

LaRosa LA, Fishman NO, Lautenbach E, Koppel RJ, Morales KH, Linkin DR. Evaluation of antimicrobial therapy orders circumventing an antimicrobial stewardship program: investigating the strategy of "stealth dosing". Infection Control and Hospital Epidemiology 2007;28:551‐6. CENTRAL

Lautenbach 2003 {published data only}

Lautenbach E, LaRosa LA, Marr AM, Nachamkin I, Bilker WB, Fishman NO. Changes in the prevalence of vancomycin‐resistant enterococci in response to antimicrobial formulary interventions: impact of progressive restrictions on use of vancomycin and third‐generation cephalosporins. Clinical Infectious Diseases 2003;36(4):440‐6. CENTRAL

Lawes 2012 {published data only}

Lawes T, Edwards B, Lopez‐Lozano J, Gould I. Trends in Staphylococcus aureus bacteraemia and impacts of infection control practices including universal MRSA admission screening in a hospital in Scotland, 2006‐2010: Retrospective cohort study and time‐series intervention analysis. BMJ Open 2012;2:e000797. CENTRAL

Layios 2012 {published data only}

Layios N, Lambermont B, Canivet JL, Morimont P, Preiser JC, Garweg C, et al. Procalcitonin usefulness for the initiation of antibiotic treatment in intensive care unit patients. Critical Care Medicine 2012;40:2304‐9. CENTRAL

Lee 1995 {published data only}

Lee J, Carlson JA, Chamberlain MA. A team approach to hospital formulary replacement. Diagnostic Microbiology and Infectious Diseases 1995;22:239‐42. CENTRAL

Lee 2007 {published data only}

Lee J, Pai H, Kim YK, Kim NH, Eun BW, Kang HJ, et al. Control of extended‐spectrum beta‐lactamase‐producing Escherichia coli and Klebsiella pneumoniae in a children's hospital by changing antimicrobial agent usage policy. Journal of Antimicrobial Chemotherapy 2007;60:629‐37. CENTRAL

Lee 2014 {published data only}

Lee TC, Frenette C, Jayaraman D, Green L, Pilote L. Antibiotic self‐stewardship: trainee‐led structured antibiotic time‐outs to improve antimicrobial use. Annals of Internal Medicine 2014;161:S53‐8. CENTRAL

Lesprit 2013 {published data only}

Lesprit P, Landelle C, Brun‐Buisson C. Clinical impact of unsolicited post‐prescription antibiotic review in surgical and medical wards: a randomized controlled trial. Clinical Microbiology and Infection: the official publication of the European Society of Clinical Microbiology and Infectious Diseases 2013;19:E91‐7. CENTRAL

Leverstein‐van Hall 2001 {published data only}

Leverstein‐van Hall MA, Fluit AC, Blok HE, Box AT, Peters ED, Weersink AJ, et al. Control of nosocomial multiresistant Enterobacteriaceae using a temporary restrictive antibiotic agent policy. European Journal of Clinical Microbiology and Infectious Diseases 2001;20:785‐91. CENTRAL

Liebowitz 2008 {published data only}

Liebowitz LD, Blunt MC. Modification in prescribing practices for third‐generation cephalosporins and ciprofloxacin is associated with a reduction in meticillin‐resistant Staphylococcus aureus bacteraemia rate. Journal of Hospital Infection 2008;69:328‐36. CENTRAL

Linkin 2007 {published data only}

Linkin DR, Fishman NO, Landis JR, Barton TD, Gluckman S, Kostman J, et al. Effect of communication errors during calls to an antimicrobial stewardship program. Infection Control and Hospital Epidemiology 2007;28:1374‐81. CENTRAL

Liu 2013 {published data only}

Liu BH, Li HF, Lei Y, Zhao SX, Sun ML. Clinical significance of dynamic monitoring of procalcitonin in guiding the use of antibiotics in patients with sepsis in ICU. Chinese Critical Care Medicine 2013;25(11):690‐3. CENTRAL

Long 2014 {published data only}

Long W, Li LJ, Huang GZ, Zhang XM, Zhang YC, Tang JG, et al. Procalcitonin guidance for reduction of antibiotic use in patients hospitalized with severe acute exacerbations of asthma: A randomized controlled study with 12‐month follow‐up. Critical Care 2014;18(5):471. CENTRAL

Madaras‐Kelly 2006 {published data only}

Madaras‐Kelly KJ, Remington RE, Lewis PG, Stevens DL. Evaluation of an intervention designed to decrease the rate of nosocomial methicillin‐resistant Staphylococcus aureus infection by encouraging decreased fluoroquinolone use. Infection Control and Hospital Epidemiology 2006;27(2):155‐69. CENTRAL

Magedanz 2012 {published data only}

Magedanz L, Silliprandi EM, Santos RP. Impact of the pharmacist on a multidisciplinary team in an antimicrobial stewardship program: a quasi‐experimental study. International Journal of Clinical Pharmacy 2012;34:290‐4. CENTRAL

Maravic‐Stojkovic 2011 {published data only}

Maravic‐Stojkovic V, Lausevic‐Vuk L, Jovic M, Rankovic A, Borzanovic M, Marinkovic J. Procalcitonin‐based therapeutic strategy to reduce antibiotic use in patients after cardiac surgery: a randomized controlled trial. Srpski Arhiv Za Celokupno Lekarstvo 2011;139:736‐42. CENTRAL

Marwick 2013 {published data only}

Marwick C, Guthrie B, Pringle J, Evans J, Nathwani D, Donnan P, et al. A multifaceted intervention to improve sepsis management in general hospital wards with evaluation using segmented regression of interrupted time series. BMJ Quality & Safety 2014;23:e2. [DOI: 10.1136/bmjqs‐2013‐002176]CENTRAL

Masia 2008 {published data only}

Masia M, Matoses C, Padilla S, Murcia A, Sanchez V, Romero I, et al. Limited efficacy of a nonrestricted intervention on antimicrobial prescription of commonly used antibiotics in the hospital setting: results of a randomized controlled trial. European Journal of Clinical Microbiology & Infectious Diseases 2008;27:597‐605. CENTRAL

May 2000 {published data only}

May AK, Melton SM, McGwin G, Cross JM, Moser SA, Rue LW. Reduction of vancomycin‐resistant enterococcal infections by limitation of broad‐spectrum cephalosporin use in a trauma and burn intensive care unit. Shock 2000;14(3):259‐64. CENTRAL

McElnay 1995 {published data only}

McElnay JC, Scott MG, Sidara JY, Kearney P. Audit of antibiotic usage in medium‐sized general hospital over an 11‐year period. The impact of antibiotic policies. Pharmacy World and Science 1995;17(6):207‐13. CENTRAL

McGowan 1976 {published data only}

McGowan JE, Findland M. Usage of antibiotics in a general hospital: Effect of requiring justification. Journal of Infectious Diseases 1974;130(2):165‐8. CENTRAL
McGowan JE, Finland M. Effects of monitoring the usage of antibiotics: An interhospital comparison. Southern Medical Journal 1976;69(2):193‐5. CENTRAL

McLaughlin 2005 {published data only}

McLaughlin CM, Bodasing N, Boyter AC, Fenelon C, Fox JG, Seaton RA. Pharmacy‐implemented guidelines on switching from intravenous to oral antibiotics: an intervention study. Quarterly Journal of Medicine 2005;98(10):745‐52. CENTRAL

McNulty 1997 {published data only}

McNulty C, Logan M, Donald IP, Ennis D, Taylor D, Baldwin RN, et al. Successful control of Clostridium difficile infection in an elderly care unit through use of a restrictive antibiotic policy. Journal of Antimicrobial Chemotherapy 1997;40:707‐11. CENTRAL

Mercer 1999 {published data only}

Mercer KA, Chintalapudi SR, Visconti EB. Impact of targeted antibiotic restriction on usage and cost in a community hospital. Journal of Pharmacy Technology 1999;15:79‐84. CENTRAL

Meyer 1993 {published data only}

Meyer KS, Urban C, Eagan JA, Berger BJ, Rahal JJ. Nosocomial outbreak of Klebsiella infection resistant to late‐generation cephalosporins. Annals of Internal Medicine 1993;119(5):353‐8. CENTRAL

Meyer 2007 {published data only}

Meyer E, Buttler J, Schneider C, Strehl E, Schroeren‐Boersch B, Gastmeier P, et al. Modified guidelines impact on antibiotic use and costs: duration of treatment for pneumonia in a neurosurgical ICU is reduced. Journal of Antimicrobial Chemotherapy 2007;59:1148‐54. CENTRAL

Meyer 2009 {published data only}

Meyer E, Lapatschek M, Bechtold A, Schwarzkopf G, Gastmeier P, Schwab F. Impact of restriction of third generation cephalosporins on the burden of third generation cephalosporin resistant K. pneumoniae and E. coli in an ICU. Intensive Care Medicine 2009;35:862‐70. CENTRAL

Meyer 2010 {published data only}

Meyer E, Schwab F, Pollitt A, Bettolo W, Schroeren‐Boersch B, Trautmann M. Impact of a change in antibiotic prophylaxis on total antibiotic use in a surgical intensive care unit. Infection 2010;38:19‐24. CENTRAL

Micek 2004 {published data only}

Micek ST, Ward S, Fraser VJ, Kollef MH. A randomized controlled trial of an antibiotic discontinuation policy for clinically suspected ventilator‐associated pneumonia. Chest 2004;125(5):1791‐9. CENTRAL

Mittal 2014 {published data only}

Mittal V, Darnell C, Walsh B, Mehta A, Badawy M, Morse R, et al. Inpatient bronchiolitis guideline implementation and resource utilization. Pediatrics 2014;133:e730‐7. CENTRAL

Mol 2005 {published data only}

Mol PGM, Wieringa JE, Nannan Panday PV, Gans ROB, Degener JE, Laseur M, et al. Improving compliance with hospital antibiotic guidelines: a time‐series intervention analysis. Journal of Antimicrobial Chemotherapy 2005;55(4):550‐7. CENTRAL

Newland 2012 {published data only}

Newland JG, Stach LM, De Lurgio SA, Hedican E, Yu D, Herigon JC, et al. Impact of a prospective‐audit‐with‐feedback antimicrobial stewardship program at a children's hospital. Journal of the Pediatric Infectious Diseases Society 2012;1:179‐86. CENTRAL
Newman RE, Hedican EB, Herigon JC, Williams DD, Williams AR, Newland JG. Impact of a guideline on management of children hospitalized with community‐acquired pneumonia. Pediatrics 2012;129:e597‐604. CENTRAL

Nobre 2008 {published data only}

Nobre V, Harbarth S, Graf JD, Rohner P, Pugin J. Use of procalcitonin to shorten antibiotic treatment duration in septic patients: a randomized trial. American Journal of Respiratory & Critical Care Medicine 2008;177:498‐505. CENTRAL

Nuila 2008 {published data only}

Nuila F, Cadle RM, Logan N, Musher DM. Antibiotic stewardship and Clostridium difficile‐associated disease. Infection Control and Hospital Epidemiology 2008;29:1096‐7. CENTRAL

Oliveira 2013 {published data only}

Oliveira CF, Botoni FA, Oliveira CRA, Silva CB, Pereira HA, Serufo JC, et al. Procalcitonin versus C‐reactive protein for guiding antibiotic therapy in sepsis: a randomized trial. Critical Care Medicine 2013;41:2336‐43. CENTRAL

Oosterheert 2005 {published data only}

Oosterheert JJ, Van Loon AM, Schuurman R, Hoepelman AI, Hak E, Thijsen S, et al. Impact of rapid detection of viral and atypical bacterial pathogens by real‐time polymerase chain reaction for patients with lower respiratory tract infection. Clinical Infectious Diseases 2005;41(10):1438‐44. CENTRAL

Ostrowsky 2014 {published data only}

Ostrowsky B, Ruiz R, Brown S, Chung P, Koppelman E, van Deusen LC, et al. Lessons learned from implementing Clostridium difficile‐focused antibiotic stewardship interventions. Infection Control and Hospital Epidemiology 2014;35:S86‐95. CENTRAL

Ozkaya 2009 {published data only}

Ozkaya E, Cambaz N, Coskun Y, Mete F, Geyik M, Samanci N. The effect of rapid diagnostic testing for influenza on the reduction of antibiotic use in paediatric emergency department. Acta Paediatrica 2009;98:1589‐92. CENTRAL

Palmay 2014 {published data only}

Palmay L, Elligsen M, Walker SAN, Pinto R, Walker S, Einarson T, et al. Hospital‐wide rollout of antimicrobial stewardship: A stepped‐wedge randomized trial. Clinical Infectious Diseases 2014;59(6):867‐74. CENTRAL

Parienti 2011 {published data only}

Parienti JJ, Cattoir V, Thibon P, Lebouvier G, Verdon R, Daubin C, et al. Hospital‐wide modification of fluoroquinolone policy and meticillin‐resistant Staphylococcus aureus rates: a 10‐year interrupted time‐series analysis. Journal of Hospital Infection 2011;78:118‐22. CENTRAL

Parikh 2014 {published data only}

Parikh K, Hall M, Teach SJ. Bronchiolitis management before and after the AAP guidelines. Pediatrics 2014;133:e1‐7. CENTRAL

Patel 1989 {published data only}

Patel M, Jackson C. Targeted interventions on oral antibiotic expenditure. British Journal of Pharmaceutical Practice 1989;11:306‐8. CENTRAL

Paul 2006 {published data only}

Kofoed K, Zalounina A, Andersen O, Lisby G, Paul M, Leibovici L, et al. Performance of the TREAT decision support system in an environment with a low prevalence of resistant pathogens. Journal of Antimicrobial Chemotherapy 2009;63:400‐4. CENTRAL
Leibovici l, Kariv G, Paul M. Long‐term survival in patients included in a randomized controlled trial of TREAT, a decision support system for antibiotic treatment. Journal of Antimicrobial Chemotherapy 2013;68:2664‐6. CENTRAL
Paul M, Andreassen S, Tacconelli E, Nielsen AD, Almanasreh N, Frank U, et al. Improving empirical antibiotic treatment using TREAT, a computerized decision support system: cluster randomized trial. Journal of Antimicrobial Chemotherapy 2006;58(6):1238‐45. CENTRAL

Pear 1994 {published data only}

Pear SM, Williamson TH, Bettin KM, Gerding DN, Galgiani JN. Decrease in nosocomial Clostridium difficile‐associated diarrhea by restricting clindamycin use. Annals of Internal Medicine 1994;120(4):272‐7. CENTRAL

Perez 2003 {published data only}

Perez A, Dennis RJ, Rodriguez B, Castro AY, Delgado V, Lozano JM, et al. An interrupted time series analysis of parenteral antibiotic use in Colombia. Journal of Clinical Epidemiology 2003;56(10):1013‐20. CENTRAL

Peto 2008 {published data only}

Peto Z, Benko R, Matuz M, Csullog E, Molnar A, Hajdu E. Results of a local antibiotic management program on antibiotic use in a tertiary intensive care unit in Hungary. Infection 2008;36:560‐4. CENTRAL

Petrikkos 2007 {published data only}

Petrikkos G, Markogiannakis A, Papaparaskevas J, Daikos GL, Stefanakos G, Zissis NP, et al. Differences in the changes in resistance patterns to third‐ and fourth‐generation cephalosporins and piperacillin/tazobactam among Klebsiella pneumoniae and Escherichia coli clinical isolates following a restriction policy in a Greek tertiary care hospital. International Journal of Antimicrobial Agents 2007;29:34‐8. CENTRAL

Pires 2011 {published data only}

Pires dos Santos R, Jacoby T, Pires Machado D, Lisboa T, Gastal SL, Nagel FM, et al. Hand hygiene, and not ertapenem use, contributed to reduction of carbapenem‐resistant Pseudomonas aeruginosa rates. Infection Control & Hospital Epidemiology 2011;32:584‐90. CENTRAL

Po 2012 {published data only}

Po JL, Nguyen BQ, Carling PC. The impact of an infectious diseases specialist‐directed computerized physician order entry antimicrobial stewardship program targeting linezolid use. Infection Control & Hospital Epidemiology 2012;33:434‐5. CENTRAL

Poehling 2006 {published data only}

Poehling KA, Zhu Y, Tang YW, Edwards K. Accuracy and impact of a point‐of‐care rapid influenza test in young children with respiratory illnesses. Archives of Pediatrics & Adolescent Medicine 2006;160:713‐8. CENTRAL

Popovski 2015 {published data only}

Popovski Z, Mercuri M, Main C, Sne N, Walsh K, Sung M, et al. Multifaceted intervention to optimize antibiotic use for intra‐abdominal infections. Journal of Antimicrobial Chemotherapy 2015;70:1226‐9. CENTRAL

Price 2010 {published and unpublished data}

Price J, Cheek E, Lippett S, Cubbon M, Gerding DN, Sambol SP, et al. Impact of an intervention to control Clostridium difficile infection on hospital‐ and community‐onset disease; an interrupted time series analysis. Clinical Microbiology & Infection 2010;16:1297‐302. CENTRAL

Pulcini 2011 {published and unpublished data}

Pulcini C, Defres S, Aggarwal I, Nathwani D, Davey P. Design of a 'day 3 bundle' to improve the reassessment of inpatient empirical antibiotic prescriptions. Journal of Antimicrobial Chemotherapy 2008;61(6):1384‐8. doi: 10.1093/jac/dkn113.. CENTRAL
Pulcini C, Dellamonica J, Bernardin G, Molinari N, Sotto A. Impact of an intervention designed to improve the documentation of the reassessment of antibiotic therapies in an intensive care unit. Medecine et Maladies Infectieuses 2011;41:546‐52. CENTRAL

Qu 2012 {published data only}

Qu R, Ji Y, Ling Y, Ye CY, Yang SM, Liu YY, et al. Procalcitonin is a good tool to guide duration of antibiotic therapy in patients with severe acute pancreatitis. A randomized prospective single‐center controlled trial. Saudi Medical Journal 2012;33:382‐7. CENTRAL

Rattanaumpawan 2010 {published data only}

Rattanaumpawan P, Sutha P, Thamlikitkul V. Effectiveness of drug use evaluation and antibiotic authorization on patients' clinical outcomes, antibiotic consumption, and antibiotic expenditures. American Journal of Infection Control 2010;38:38‐43. CENTRAL

Rattanaumpawan 2011 {published data only}

Rattanaumpawan P, Morales KH, Binkley S, Synnestvedt M, Weiner MG, Gasink LB, et al. Impact of antimicrobial stewardship programme changes on unnecessary double anaerobic coverage therapy. Journal of Antimicrobial Chemotherapy 2011;66:2655‐8. CENTRAL

Richards 2003 {published data only}

Richards MJ, Robertson MB, Dartnell JG, Duarte MM, Jones NR, Kerr DA, et al. Impact of a web‐based antimicrobial approval system on broad‐spectrum cephalosporin use at a teaching hospital. Medical Journal of Australia 2003;178:386‐90. CENTRAL

Richardson 2000 {published data only}

Richardson LP, Wiseman SW, Melani PN, Lyons MJ, Kauffman CA. Effectiveness of a vancomycin restriction policy in changing the prescribing patterns of house staff. Microbial Drug Resistance 2000;6(4):327‐30. CENTRAL

Ross 2014 {published data only}

Ross RK, Hersh AL, Kronman MP, Newland JG, Metjian TA, Localio AR, et al. Impact of Infectious Diseases Society of America/Pediatric Infectious Diseases Society guidelines on treatment of community‐acquired pneumonia in hospitalized children. Clinical Infectious Diseases: an official publication of the Infectious Diseases Society of America 2014;58:834‐8. CENTRAL

Saizy‐Callaert 2003 {published data only}

Saizy‐Callaert S, Causse R, Furhman C, Le Paih MF, Thebault A, Chouaid C. Impact of a multidisciplinary approach to the control of antibiotic prescription in a general hospital. Journal of Hospital Infection 2003;53(3):177‐82. CENTRAL

Salama 1996 {published data only}

Salama S, Rotstein C, Mandell L. A multidisciplinary hospital‐based antimicrobial use program: impact on hospital pharmacy expenditures and drug use. Canadian Journal of Infectious Diseases 1996;7:104‐9. CENTRAL

Schnoor 2010 {published data only (unpublished sought but not used)}

Schnoor M, Meyer T, Suttorp N, Raspe H, Welte T, Schafer T, et al. Development and evaluation of an implementation strategy for the German guideline on community‐acquired pneumonia. Quality & Safety in Health Care 2010;19:498‐502. CENTRAL

Schouten 2007 {published data only}

Schouten JA, Hulscher MEJL, Trap‐Liefers J, Akkermans RP, Kullberg BJ, Grol RPTM, et al. Tailored interventions to improve antibiotic use for lower respiratory tract infections in hospitals: a cluster‐randomized, controlled trial. Clinical Infectious Diseases 2007;44:931‐41. CENTRAL

Schroeder 2009 {published data only}

Schroeder S, Hochreiter M, Koehler T, Schweiger AM, Bein B, Keck FS, et al. Procalcitonin (PCT)‐guided algorithm reduces length of antibiotic treatment in surgical intensive care patients with severe sepsis: results of a prospective randomized study. Langenbeck's Archives of Surgery/Deutsche Gesellschaft fur Chirurgie 2009;394:221‐6. CENTRAL

Schuetz 2009 {published data only}

Schuetz P, Batschwaroff M, Dusemund F, Albrich W, Burgi U, Maurer M, et al. Effectiveness of a procalcitonin algorithm to guide antibiotic therapy in respiratory tract infections outside of study conditions: a post‐study survey. European Journal of Clinical Microbiology & Infectious Diseases 2010;29:269‐77. CENTRAL
Schuetz P, Christ‐Crain M, Albrich W, Zimmerli W, Mueller B, Pro Hosp Study Group. Guidance of antibiotic therapy with procalcitonin in lower respiratory tract infections: insights into the ProHOSP study. Virulence 2010;1:88‐92. CENTRAL
Schuetz P, Christ‐Crain M, Thomann R, Falconnier C, Wolbers M, Widmer I, et al. Effect of procalcitonin‐based guidelines vs standard guidelines on antibiotic use in lower respiratory tract infections: the ProHOSP randomized controlled trial. JAMA 2009;302:1059‐66. CENTRAL

Schwann 2011 {published data only}

Schwann NM, Bretz KA, Eid S, Burger T, Fry D, Ackler F, et al. Point‐of‐care electronic prompts: an effective means of increasing compliance, demonstrating quality, and improving outcome. Anesthesia & Analgesia 2011;113:869‐76. CENTRAL

Schwartz 2007 {published data only}

Schwartz DN, Abiad H, DeMarais PL, Armeanu E, Trick WE, Wang Y, et al. An educational intervention to improve antimicrobial use in a hospital‐based long‐term care facility. Journal of the American Geriatrics Society 2007;55:1236‐42. CENTRAL

Senn 2004 {published data only}

Senn L, Burnand B, Francioli P, Zanetti G. Improving appropriateness of antibiotic therapy: randomized trial of an intervention to foster reassessment of prescription after 3 days. Journal of Antimicrobial Chemotherapy 2004;53(6):1062‐7. CENTRAL

Shehabi 2014 {published data only}

Shehabi Y, Sterba M, Garrett PM, Rachakonda KS, Stephens D, Harrigan P, et al. Procalcitonin algorithm in critically ill adults with undifferentiated infection or suspected sepsis. A randomized controlled trial. American Journal of Respiratory and Critical Care Medicine 2014;190:1102‐10. CENTRAL

Shen 2011 {published data only}

Shen J, Sun Q, Zhou X, Wei Y, Qi Y, Zhu J, et al. Pharmacist interventions on antibiotic use in inpatients with respiratory tract infections in a Chinese hospital. International Journal of Clinical Pharmacy 2011;33:929‐33. CENTRAL

Shojania 1998 {published data only}

Shojania KG, Yokoe D, Platt R, Fiskio J, Ma'luf N, Bates DW. Reducing vancomycin use utilizing a computer guideline: results of a randomized controlled trial. Journal of the American Medical Informatics Association 1998;5(6):554‐62. CENTRAL

Singh 2000 {published data only}

Singh N, Rogers P, Atwood CW, Wagener MM, Yu VL. Short‐course empiric antibiotic therapy for patients with pulmonary infiltrates in the intensive care unit. A proposed solution for indiscriminate antibiotic prescription. American Journal of Respiratory and Critical Care Medicine 2000;162(2 Pt 1):505‐11. CENTRAL

Sirinavin 1998 {published data only}

Sirinavin S, Suvanakoot P, Sathapatayavongs B, Malatham K. Effect of antibiotic order form guiding rational use of expensive drugs on cost containment. Southeast Asian Journal of Tropical Medicine and Public Health 1998;29(3):636‐42. CENTRAL

Skaer 1993 {published data only}

Skaer TL, Sclar DA, Won JKH, Markowski DJ. Effect of academic detailing on the utilization of intravenous antimicrobial therapy. Current Therapeutic Research 1993;53(4):349‐55. CENTRAL

Skrlin 2011 {published data only}

Skrlin J, Bacic Vrca V, Marusic S, Ciric‐Crncec M, Mayer L. Impact of ceftriaxone de‐restriction on the occurrence of ESBL‐positive bacterial strains and antibiotic consumption. Journal of Chemotherapy 2011;23:341‐4. CENTRAL

Solomon 2001 {published data only}

Solomon DH, Van Houten L, Glynn RJ, Baden L, Curtis K, Schrager H, et al. Academic detailing to improve use of broad‐spectrum antibiotics at an academic medical center. Archives of Internal Medicine 2001;161(15):1897‐902. CENTRAL

Standiford 2012 {published data only}

Standiford HC, Chan S, Tripoli M, Weekes E, Forrest GN. Antimicrobial stewardship at a large tertiary care academic medical center: cost analysis before, during, and after a 7‐year program. Infection Control and Hospital Epidemiology 2012;33:338‐45. CENTRAL

Stevenson 1988 {published data only}

Hampson JP, Corkhill JE, Murray A, Griffiths LR, Smith JC, Bartzokas CA. Potential financial benefits of a local antibiotic policy. Pharmaceutical Journal 1988;241:660‐2. CENTRAL
Stevenson RC, Blackman SC, Williams CL, Bartzokas CA. Measuring the saving attributable to an antibiotic prescribing policy. Journal of Hospital Infection 1988;11:16‐25. CENTRAL

Stocker 2010 {published data only}

Stocker M, Fontana M, el Helou S, Wegscheider K, Berger TM. Use of procalcitonin‐guided decision‐making to shorten antibiotic therapy in suspected neonatal early‐onset sepsis: prospective randomized intervention trial. Neonatology 2010;97:165‐74. CENTRAL

Stolz 2007 {published data only}

Stolz D, Christ‐Crain M, Bingisser R, Leuppi J, Miedinger D, Muller C, et al. Antibiotic treatment of exacerbations of COPD: a randomized, controlled trial comparing procalcitonin‐guidance with standard therapy. Chest 2007;131:9‐19. CENTRAL

Stolz 2009 {published data only}

Stolz D, Smyrnios N, Eggimann P, Pargger H, Thakkar N, Siegemund M, et al. Procalcitonin for reduced antibiotic exposure in ventilator‐associated pneumonia: a randomised study. European Respiratory Journal 2009;34:1364‐75. CENTRAL

Strom 2010 {published data only}

Strom BL, Schinnar R, Aberra F, Bilker W, Hennessy S, Leonard CE, et al. Unintended effects of a computerized physician order entry nearly hard‐stop alert to prevent a drug interaction: a randomized controlled trial. Archives of Internal Medicine 2010;170:1578. CENTRAL

Sun 2011 {published data only}

Sun TB, Chao SF, Chang BS, Chen TY, Gao PY, Shyr MH. Quality Improvements of antimicrobial prophylaxis in coronary artery bypass grafting. Journal of Surgical Research 2011;167:329‐35. CENTRAL

Suwangool 1991 {published data only}

Suwangool P, Moola‐Or P, Waiwatana A, Sitthi‐amorn C, Israsena S, Hanvanich M. Effect of a selective restriction policy on antibiotic expenditure and use: an institutional model. Journal of the Medical Association of Thailand 1991;74:272‐5. CENTRAL

Talpaert 2011 {published data only}

Talpaert MJ, Rao GG, Cooper BS, Wade P. Impact of guidelines and enhanced antibiotic stewardship on reducing broad‐spectrum antibiotic usage and its effect on incidence of Clostridium difficile infection. Journal of Antimicrobial Chemotherapy 2011;66:2168‐74. CENTRAL

Tangdén 2011 {published data only}

Tängdén T, Eriksson BM, Melhus A, Svennblad B, Cars O. Radical reduction of cephalosporin use at a tertiary hospital after educational antibiotic intervention during an outbreak of extended‐spectrum beta‐lactamase‐producing Klebsiella pneumoniae. Journal of Antimicrobial Chemotherapy 2011;66:1161‐7. CENTRAL

Toltzis 1998 {published data only}

Toltzis P, Yamashita T, Vilt L, Green M, Morrissey A, Spinner‐Block S, et al. Antibiotic restriction does not alter endemic colonization with resistant gram‐negative rods in a pediatric intensive care unit. Critical Care Medicine 1998;26(11):1893‐9. CENTRAL

Toltzis 2002 {published data only}

Toltzis P, Dul MJ, Hoyen C, Salvator A, Walsh M, Zetts L, et al. The effect of antibiotic rotation on colonization with antibiotic‐resistant bacilli in a neonatal intensive care unit. Pediatrics 2002;110:707‐11. CENTRAL

Toltzis 2014 {published data only}

Toltzis P, O'Riordan M, Cunningham DJ, Ryckman FC, Bracke TM, Olivea J, et al. A statewide collaborative to reduce pediatric surgical site infections. Pediatrics 2014;134:e1174‐80. CENTRAL

Trenholme 1989 {published data only}

Trenholme GM, Kaplan RL, Karakusis PH, Stine T, Fuhrer J, Landau W, et al. Clinical impact of rapid identification and susceptibility testing of bacterial blood culture isolates. Journal of Clinical Microbiology 1989;27(6):1342‐5. CENTRAL

Uçkay 2009 {published data only}

Uçkay I, Vernaz‐Hegi N, Harbarth S, Stern R, Legout L, Vauthey L, et al. Activity and impact on antibiotic use and costs of a dedicated infectious diseases consultant on a septic orthopaedic unit. Journal of Infection 2009;58:205‐12. CENTRAL

Valiquette 2007 {published data only}

Valiquette L, Cossette B, Garant M‐P, Diab H, Pépin J. Impact of a reduction in the use of high‐risk antibiotics on the course of an epidemic of Clostridium difficile‐associated disease caused by the hypervirulent NAP1/027 strain. Clinical Infectious Diseases 2007;45:S112‐21. CENTRAL

van Hees 2008 {published data only}

van Hees BC, de Ruiter E, Wiltink EH, de Jongh BM, Tersmette M. Optimizing use of ciprofloxacin: a prospective intervention study. Journal of Antimicrobial Chemotherapy 2008;61:210‐3. CENTRAL

Van Kasteren 2005 {published data only}

Mannien J, van Kasteren ME, Nagelkerke NJ, Gyssens IC, Kullberg BJ, Wille JC, et al. Effect of optimized antibiotic prophylaxis on the incidence of surgical site infection. Infection Control & Hospital Epidemiology 2006;27:1340‐6. CENTRAL
Van Kasteren ME, Mannien J, Kullberg BJ, de Boer AS, Nagelkerke NJ, Ridderhof M, et al. Quality improvement of surgical prophylaxis in Dutch hospitals: evaluation of a multi‐site intervention by time series analysis. Journal of Antimicrobial Chemotherapy 2005;56(6):1094‐102. CENTRAL

Volpe 2012 {published data only}

Volpe D, Harrison S, Damian F, Rachh P, Kahlon PS, Morrissey L, et al. Improving timeliness of antibiotic delivery for patients with fever and suspected neutropenia in a pediatric emergency department. Pediatrics 2012;130:e201‐10. CENTRAL

Walker 1998 {published data only}

Walker SE. Physicians' acceptance of a preformatted pharmacy intervention chart note in a community hospital antibiotic step down program. Journal of Pharmacy Technology 1998;14:141‐5. CENTRAL

Wang 2014 {published data only}

Wang HY, Chiu CH, Huang CT, Cheng CW, Lin YJ, Hsu YJ, et al. Blood culture‐guided de‐escalation of empirical antimicrobial regimen for critical patients in an online antimicrobial stewardship programme. International Journal of Antimicrobial Agents 2014;44(6):520‐7. CENTRAL

Wax 2007 {published data only}

Wax DB, Beilin Y, Levin M, Chadha N, Krol M, Reich DL. The effect of an interactive visual reminder in an anesthesia information management system on timeliness of prophylactic antibiotic administration. Anesthesia & Analgesia 2007;104:1462‐6. CENTRAL

Weinberg 2001 {published data only}

Weinberg M, Fuentes JM, Ruiz A I, Lozano FW, Angel E, Gaitan H, et al. Reducing infections among women undergoing cesarean section in Colombia by means of continuous quality improvement methods. Archives of Internal Medicine 2001;161(19):2357‐65. CENTRAL

Weiner 2009 {published data only}

Weiner SG, Brown SF, Goetz JD, Webber CA. Weekly E‐mail reminders influence emergency physician behavior: a case study using the Joint Commission and Centers for Medicare and Medicaid Services Pneumonia Guidelines. Academic Emergency Medicine 2009;16:626‐31. CENTRAL

Weiss 2013 {published data only}

Weiss CH, Dibardino D, Rho J, Sung N, Collander B, Wunderink RG. A clinical trial comparing physician prompting with an unprompted automated electronic checklist to reduce empirical antibiotic utilization. Critical Care Medicine 2013;41:2563‐9. CENTRAL
Weiss CH, Persell SD, Wunderink RG, Baker DW. Empiric antibiotic, mechanical ventilation, and central venous catheter duration as potential factors mediating the effect of a checklist prompting intervention on mortality: an exploratory analysis. BMC Health Services Research 2012;12:198. [DOI: 10.1186/1472‐6963‐12‐198]CENTRAL

Welker 2008 {published data only}

Welker JA, Huston M, McCue JD. Antibiotic timing and errors in diagnosing pneumonia. Archives of Internal Medicine 2008;168:351‐6. CENTRAL

Wenisch 2014 {published data only}

Wenisch JM, Equiluz‐Bruck S, Fudel M, Reiter I, Schmid A, Singer E, et al. Decreasing Clostridium difficile infections by an antimicrobial stewardship program that reduces moxifloxacin use. Antimicrobial Agents and Chemotherapy 2014;58 (9):5079‐83. CENTRAL

Willemsen 2010 {published data only}

Willemsen I, Cooper B, van Buitenen C, Winters M, Andriesse G, Kluytmans J. Improving quinolone use in hospitals by using a bundle of interventions in an interrupted time series analysis. Antimicrobial Agents and Chemotherapy 2010;54:3763‐9. CENTRAL

Wilson 1991 {published data only}

Wilson J, Gordon A, French S, Aslam M. The effectiveness of prescribers newsletters in influencing hospital drug expenditure. Hospital Pharmacy Practice 1991;1:33‐8. CENTRAL

Winters 2010 {published data only}

Winters BD, Thiemann DR, Brotman DJ. Impact of a restrictive antimicrobial policy on the process and timing of antimicrobial administration. Journal of Hospital Medicine 2010;5:E41‐5. CENTRAL

Wishaupt 2011 {published data only}

Wishaupt JO, Russcher A, Smeets LC, Versteegh FG, Hartwig NG. Clinical impact of RT‐PCR for pediatric acute respiratory infections: a controlled clinical trial. Pediatrics 2011;128:e1113‐20. CENTRAL

Woodward 1987 {published data only}

Woodward RS, Medoff G, Smith MD, Gray JLI. Antibiotic cost savings from formulary restrictions and physician monitoring in a medical‐school‐affiliated hospital. American Journal of Medicine 1987;83(5):817‐23. CENTRAL

Wyatt 1998 {published data only}

Wyatt JC, Paterson‐Brown S, Johanson R, Altman DG, Bradburn MJ, Fisk NM. Randomised trial of educational visits to enhance use of systematic reviews in 25 obstetric units. BMJ 1998;317(7165):1041‐6. CENTRAL

Yealy 2005 {published data only}

Hsu DJ, Stone RA, Obrosky DS, Yealy DM, Meehan TP, Fine JM, et al. Predictors of timely antibiotic administration for patients hospitalized with community‐acquired pneumonia from the cluster‐randomized EDCAP trial. American Journal of the Medical Sciences 2010;339:307‐13. CENTRAL
Yealy DM, Auble TE, Stone RA, Lave JR, Meehan TP, Graff LG, et al. Effect of increasing the intensity of implementing pneumonia guidelines: A randomized, controlled trial. Annals of Internal Medicine 2005;143:881‐94. CENTRAL

Yeo 2012 {published data only}

Yeo CL, Chan DSG, Earnest A, Wu TS, Yeoh SF, Lim R, et al. Prospective audit and feedback on antibiotic prescription in an adult hematology‐oncology unit in Singapore. European Journal of Clinical Microbiology & Infectious Diseases 2012;31:583‐90. CENTRAL

Yong 2010 {published data only}

Yong MK, Buising KL, Cheng AC, Thursky KA. Improved susceptibility of Gram‐negative bacteria in an intensive care unit following implementation of a computerized antibiotic decision support system. Journal of Antimicrobial Chemotherapy 2010;65:1062‐9. CENTRAL

Yoon 2014 {published data only}

Yoon YK, Yang KS, Lee SE, Kim HJ, Sohn JW, Kim MJ. Effects of Group 1 versus Group 2 carbapenems on the susceptibility of Acinetobacter baumannii to carbapenems: A before and after intervention study of carbapenem‐use stewardship. PLoS ONE 2014;9(6):e99101. CENTRAL

Young 1985 {published data only}

Young EJ, Sewell CM, Koza MA, Clarridge JE. Antibiotic resistance patterns during aminoglycoside restriction. American Journal of Medical Science 1985;290(6):223‐7. CENTRAL

Yu 2014 {published data only}

Yu K, Rho J, Morcos M, Nomura J, Kaplan D, Sakamoto K, et al. Evaluation of dedicated infectious diseases pharmacists on antimicrobial stewardship teams. American Journal of Health‐System Pharmacy 2014;71:1019‐28. CENTRAL

Zanetti 2003 {published data only}

Zanetti G, Flanagan HL, Cohn LH, Giardina R, Platt R. Improvement of intraoperative antibiotic prophylaxis in prolonged cardiac surgery by automated alerts in the operating room. Infection Control and Hospital Epidemiology 2003;24:13‐6. CENTRAL

References to studies excluded from this review

Ahronheim 2000 {published data only}

Ahronheim JC, Morrison RS, Morris J, Baskin S, Meier DE. Palliative care in advanced dementia: a randomized controlled trial and descriptive analysis. Journal of Palliative Medicine2000; Vol. 3, issue 3:265‐73. CENTRAL

Bruno‐Murtha 2005 {published data only}

Bruno‐Murtha LA, Brusch J, Bor D, Li W, Zucker D. A pilot study of antibiotic cycling in the community hospital setting. Infection Control and Hospital Epidemiology 2005;26:81‐7. CENTRAL

Burke 1997 {published data only}

Burke CE, Piper J, Holloway W. Order form for restricting vancomycin prescribing. American Journal of Health‐System Pharmacy 1997;54(16):1893, 1897. CENTRAL

Cook 2006 {published data only}

Cook PP, Catrou P, Gooch M, Holbert D. Effect of reduction in ciprofloxacin use on prevalence of meticillin‐resistant Staphylococcus aureus rates within individual units of a tertiary care hospital. Journal of Hospital Infection 2006;64:348‐51. CENTRAL

Crist 1987 {published data only}

Crist KD, Nahata MC, Ety J. Positive impact of a therapeutic drug‐monitoring program on total aminoglycoside dose and cost of hospitalization. Therapeutic Drug Monitoring 1987;9(3):306‐10. CENTRAL

Cunningham 2008 {published data only}

Cunningham TR, Geller ES, Clarke SW. Impact of electronic prescribing in a hospital setting: a process‐focused evaluation. International Journal of Medical Informatics 2008;77:546‐54. CENTRAL

Dellinger 2005 {published data only}

Dellinger EP, Hausmann SM, Bratzler DW, Johnson RM, Daniel DM, Bunt KM, et al. Hospitals collaborate to decrease surgical site infections. American Journal of Surgery 2005;190(1):9‐15. CENTRAL

Destache 1990 {published data only}

Destache CJ, Meyer SK, Bittner MJ, Hermann KG. Impact of a clinical pharmacokinetic service on patients treated with aminoglycosides: a cost‐benefit analysis. Therapeutic Drug Monitoring 1990;12(5):419‐26. CENTRAL

Ehrenkranz 1992 {published data only}

Ehrenkranz NJ, Nerenberg DE, Shultz JM, Slater KC. Intervention to discontinue parenteral antimicrobial therapy in patients hospitalized with pulmonary infections: effect on shortening patient stay. Infection Control and Hospital Epidemiology 1992;13(1):21‐32. CENTRAL

Ehrenkranz 1993 {published data only}

Ehrenkranz NJ, Nerenberg DE, Slater KC, Shultz JM. Intervention to discontinue parenteral antimicrobial therapy in hospitalized patients with urinary tract infection, skin and soft tissue infection, or no evident infection. Infection Control and Hospital Epidemiology 1993;14(9):517‐22. CENTRAL

Evans 1994 {published data only}

Evans RS, Classen DC, Pestotnik SL, Lundsgaarde HP, Burke JP. Improving empiric antibiotic selection using computer decision support. Archives of Internal Medicine. 1994;154(8):878‐84. CENTRAL

Foy 2004 {published data only}

Foy R, Penney GC, Grimshaw JM, Ramsay CR, Walker AE, Maclennan G, et al. A randomised controlled trial of a tailored multifaceted strategy to promote implementation of a clinical guideline on induced abortion care. BJOG: An International Journal of Obstetrics & Gynaecology 2004;111:726‐33. CENTRAL

Garcia‐San Miguel 2014 {published data only}

Garcia‐San Miguel L, Cobo J, Martinez JA, Arnau JM, Murillas J, Pena C, et al. 'Third day intervention': an analysis of the factors associated with following the recommendations on the prescribing of antibiotics. Enfermedades Infecciosas y Microbiología Clínica 2014;32:654‐61. CENTRAL

Gerding 1991 {published data only}

Gerding DN, Larson TA, Hughes RA, Weiler M, Shanholtzer C, Peterson LR. Aminoglycoside resistance and aminoglycoside usage: ten years of experience in one hospital. Antimicrobial Agents and Chemotherapy 1991;35(7):1284‐90. CENTRAL

Kolar 1999 {published data only}

Kolar M, Latal T. Implementation of a practical antibiotic policy in the Czech Republic. Infection Control and Hospital Epidemiology 1999;20(6):440‐3. CENTRAL
Monnet DL, Sørensen TL, Jepsen OB. Implementation of a practical antibiotic policy in the Czech Republic. Infect Control Hosp Epidemiol. 2000;21(1):7‐8. CENTRAL

Lan 2003 {published data only}

Lan CK, Hsueh PR, Wong WW, Fung CP, Lau YT, Yeung JY, et al. Association of antibiotic utilization measures and reduced incidence of infections with extended‐spectrum beta‐lactamase‐producing organisms. Journal of Microbiology, Immunology, and Infection 2003;36(3):182‐6. CENTRAL

Lee 2004 {published data only}

Lee SO, Lee ES, Park SY, Kim SY, Seo YH, Cho YK. Reduced use of third‐generation cephalosporins decreases the acquisition of extended‐spectrum beta‐lactamase‐producing Klebsiella pneumoniae. Infection Control and Hospital Epidemiology 2004;25(10):832‐7. CENTRAL

MacCosbe 1985 {published data only}

MacCosbe PE, Gartenberg G. Modifying empiric antibiotic prescribing: experience with one strategy in a medical residency program. Hospital Formulary 1985;20(9):986‐8, 993‐5, 999. CENTRAL

Marrie 2000 {published data only}

Marrie TJ, Lau CY, Wheeler SL, Wong CJ, Vandervoort MK, Feagan BG. A controlled trial of a critical pathway for treatment of community‐acquired pneumonia. CAPITAL Study Investigators. Community‐Acquired Pneumonia Intervention Trial Assessing Levofloxacin. JAMA 2000;283(6):749‐55. CENTRAL
Palmer CS, Zhan C, Elixhauser A, Halpern MT, Rance L, Feagan BG, et al. Economic assessment of the community‐acquired pneumonia intervention trial employing levofloxacin. Clinical Therapeutics2000; Vol. 22, issue 2:250‐64. CENTRAL

Martin 2005 {published data only}

Martin C, Ofotokun I, Rapp R, Empey K, Armitstead J, Pomeroy C, et al. Results of an antimicrobial control program at a university hospital. American Journal of Health‐System Pharmacy 2005;62(7):732‐8. CENTRAL

McGregor 2006 {published data only}

McGregor JC, Weekes E, Forrest GN, Standiford HC, Perencevich EN, Furuno JP, et al. Impact of a computerized clinical decision support system on reducing inappropriate antimicrobial use: a randomized controlled trial. Journal of the American Medical Informatics Association 2006;13(4):378‐84. CENTRAL

Nagao 2010 {published data only}

Nagao M, Iinuma Y, Saito T, Matsumura Y, Shirano M, Matsushima A, et al. Close cooperation between infectious disease physicians and attending physicians can result in better management and outcome for patients with Staphylococcus aureus bacteraemia. Clinical Microbiology & Infection 2010;16:1783‐8. CENTRAL

Naughton 2001 {published data only}

Naughton BJ, Mylotte JM, Ramadan F, Karuza J, Priore RL. Antibiotic use, hospital admissions, and mortality before and after implementing guidelines for nursing home‐acquired pneumonia. Journal of the American Geriatrics Society 2001;49:1020‐4. CENTRAL

Pastel 1992 {published data only}

Pastel DA, Chang S, Nessim S, Shane R, Morgan MA. Department of pharmacy‐initiated program for streamlining empirical antibiotic therapy. Hospital Pharmacy 1992;27(7):596‐603, 614. CENTRAL

Ronning 1998 {published data only}

Ronning OM, Guldvog B. Stroke unit versus general medical wards, II: neurological deficits and activities of daily living: a quasi‐randomized controlled trial. Stroke 1998;29(3):586‐90. CENTRAL

Sanazaro 1978 {published data only}

Sanazaro PJ, Worth RM. Concurrent quality assurance in hospital care. Report of a study by private initiative in PSRO. New England Journal of Medicine1978; Vol. 298, issue 21:1171‐7. CENTRAL

Takahashi 2010 {published data only}

Takahashi Y, Takesue Y, Nakajima K, Ichiki K, Wada Y, Tsuchida T, et al. Implementation of a hospital‐wide project for appropriate antimicrobial prophylaxis. Journal of Infection and Chemotherapy 2010;16:418‐23. CENTRAL

Thomas 2002 {published data only}

Thomas AR, Cieslak PR, Strausbaugh LJ, Fleming DW. Effectiveness of pharmacy policies designed to limit inappropriate vancomycin use: a population‐based assessment. Infection Control and Hospital Epidemiology 2002;23(11):683‐8. CENTRAL

Tiley 2003 {published data only}

Tiley SM, MacDonald JJ, Doherty PL, Ferguson JK, Fergusson JE. Active promotion of antibiotic guidelines: an intensive program. Communicable Disease Intelligence2003; Vol. 27 Suppl:13‐8. CENTRAL

Tsiata 2001 {published data only}

Tsiata C, Tsekouras V, Karokis A, Starakis J, Bassaris HP, Maragoudakis M, et al. Cost effectiveness of antibacterial restriction strategies in a tertiary care university teaching hospital. Disease Management and Health Outcomes 2001;9:23‐32. CENTRAL

Van Loon 2005 {published data only}

Van Loon HJ, Vriens MR, Fluit AC, Troelstra A, Van der Werken C, Verhoef J, et al. Antibiotic rotation and development of gram‐negative antibiotic resistance. American Journal of Respiratory and Critical Care Medicine 2005;171(5):480‐7. CENTRAL

Wahlstrom 2003 {published data only}

Wahlstrom R, Kounnavong S, Sisounthone B, Phanyanouvong A, Southammavong T, Eriksson B, et al. Effectiveness of feedback for improving case management of malaria, diarrhoea and pneumonia ‐ a randomized controlled trial at provincial hospitals in Lao PDR. Tropical Medicine and International Health 2003;8(10):901‐9. CENTRAL

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Arnold SR, Straus SE. Interventions to improve antibiotic prescribing practices in ambulatory care. Cochrane Database of Systematic Reviews 2005, Issue 4. [DOI: 10.1002/14651858.CD003539.pub2]

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Ash JS, Sittig DF, Dykstra RH, Guappone K, Carpenter JD, Seshadri V. Categorizing the unintended sociotechnical consequences of computerized provider order entry. International Journal of Medical Informatics 2007;76 Suppl 1:S21‐7.

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Avery AJ, Rodgers S, Cantrill JA, Armstrong S, Cresswell K, Eden M, et al. A pharmacist‐led information technology intervention for medication errors (PINCER): a multicentre, cluster randomised, controlled trial and cost‐effectiveness analysis. Lancet 2012;379:1310‐9.

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Charani 2011

Charani E, Edwards R, Sevdalis N, Alexandrou B, Sibley E, Mullett D, et al. Behavior change strategies to influence antimicrobial prescribing in acute care: a systematic review. Clinical Infectious Diseases 2011;53(7):651‐62.

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References to other published versions of this review

Davey 2005

Davey P, Brown E, Fenelon L, Finch R, Gould I, Hartman G, et al. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database of Systematic Reviews 2005, Issue 4. [DOI: 10.1002/14651858.CD003543.pub2]

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Davey P, Brown E, Charani E, Fenelon L, Gould IM, Holmes A, et al. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database of Systematic Reviews 2013, Issue 4. [DOI: 10.1002/14651858.CD003543.pub3]

Davey 2014

Davey P, Peden C, Brown E, Charani E, Michie S, Ramsay CR, et al. Interventions to improve antibiotic prescribing practices for hospital inpatients (updated protocol). Cochrane Database of Systematic Reviews 2014, Issue 8. [DOI: 10.1002/14651858.CD011236]

Characteristics of studies

Characteristics of included studies [ordered by study ID]

Abramowitz 1982

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: all adult patients in the hospital

CLINICAL PROBLEM: receiving treatment with target antibiotics

SETTING: single university hospital in the USA

Interventions

FORMAT, Interventions: educational meetings with dissemination of materials; audit and feedback; educational outreach by review and recommend change

Intervention Functions: education; enablement; persuasion

DELIVERER: pharmacist

COMPARISON: 9 months' pre‐intervention. Usual care

DESIRED CHANGE: reduce inappropriate

Outcomes

PRESCRIBING: Choice: decrease in use of cefoxitin and cefamandole

COST: total cost of 6 target antibiotics (calculated from data in Tables 1 and 2)

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

Not stated.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper (comparison of means, uncontrolled before‐after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine pharmacy systems database.

Free of other bias (ITS) ?

Low risk

Price of target antibiotics constant over the study period.

Adachi 1997

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients requiring antibiotic treatment
SETTING: single hospital in the USA

Interventions

FORMAT, Interventions: dissemination of educational materials; educational outreach by review and recommend change; reminders (physical ‐ newsletter)

Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: pharmacist
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: reduce vancomycin prescribing and increase appropriate use of vancomycin

COST: valid financial savings

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper (comparison of means, uncontrolled before and after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Unclear risk

Not clear, no information about changes in price of vancomycin over the study period.

Akenroye 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all paediatricians and nurses in the ED
PARTICIPANTS: all children with bronchiolitis
CLINICAL PROBLEM: acute bronchiolitis presenting to a paediatric ED
SETTING: 1 university hospital in the USA

Interventions

FORMAT, Interventions: audit and feedback; dissemination of educational materials; educational outreach by review and recommend change; reminders (physical ‐ posters and email)

Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: departmental physicians, nurses, and managers
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: exposure, % children treated with antibiotics

CLINICAL: balancing, % admission rate, % return ED visit rate, ED length of stay (minutes)

FINANCIAL: total cost per patient. No data about the intervention cost.

Notes

FINANCIAL SUPPORT: Funding: Boston Children’s Hospital Department of Medicine Quality Improvement Publication (QIPub) grant. Competing Interest: none declared

ADDITIONAL INFORMATION: care pathway is in a supplementary online file

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Electronic outcome data

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Electronic outcome data

Incomplete outcome data addressed (ITS) ?

Low risk

Electronic outcome data

Free of selected reporting (ITS) ?

Low risk

Electronic outcome data

Free of other bias (ITS) ?

Low risk

> 1 year of data pre‐ and postintervention

Aldeyab 2012

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all adult patients in the hospital
CLINICAL PROBLEM: patients requiring therapeutic or prophylactic antibiotics
SETTING: 1 university hospital in the UK

Interventions

FORMAT, Interventions: audit and feedback; restrictive ‐ expert approval

Intervention Functions: enablement, restriction

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of target antibiotics in DDD/100 OBD

MICROBIAL: Clostridium difficile infections/100 OBD

Notes

FINANCIAL SUPPORT: Funding: Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah grant no. 7‐968‐D1432. Competing interest: none declared

ADDITIONAL DATA: restriction policy is described in detail in an additional online file for this paper and in Conlon 2011.

Microbial Risk of Bias: LOW, case definition Low, planned intervention Low, other infection control Low

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Changes in CDI screening policy and cleaning policy occurred between Phases 1 and 2 (Figure 1).

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Electronic data from pharmacy and microbiology

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Electronic data from pharmacy and microbiology

Incomplete outcome data addressed (ITS) ?

Low risk

Electronic data from pharmacy and microbiology

Free of selected reporting (ITS) ?

Low risk

Electronic data from pharmacy and microbiology

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Aldeyab 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all adult patients in the hospital
CLINICAL PROBLEM: patients requiring therapeutic or prophylactic antibiotics
SETTING: 1 university hospital in the UK

Interventions

FORMAT: same as in Aldeyab 2012; this article provides additional microbial outcome data for impact on MRSA infections
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: same as in Aldeyab 2012

MICROBIAL: MRSA infections/100 OBD

Notes

FINANCIAL SUPPORT: same as in Aldeyab 2012

ADDITIONAL DATA: restriction policy is described in detail in an additional online file for Aldeyab 2012 and in Conlon 2011 (additional studies)

Microbial Risk of Bias: LOW, case definition Low, planned intervention Low, other infection control Low

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Data and segmented regression model of alcohol‐based hand rub included as a proxy measure for infection control practices.

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Electronic data from microbiology

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Electronic data from microbiology

Incomplete outcome data addressed (ITS) ?

Low risk

Electronic data from microbiology

Free of selected reporting (ITS) ?

Low risk

Electronic data from microbiology

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Ananda‐Rajah 2010

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the medical‐surgical ICU
PARTICIPANTS: all patients in the ICU
CLINICAL PROBLEM: reduction in use of broad‐spectrum antibiotics considered high risk for selection of MRSA
SETTING: 1 university hospital in Australia

Interventions

FORMAT, Interventions: educational outreach by review and recommend change

Intervention Functions: education, enablement, persuasion

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of broad‐spectrum antibiotics in DDD/1000 OBD

MICROBIAL: MRSA bacteraemia rate

Notes

FINANCIAL SUPPORT: none declared. Competing Interest: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: HIGH, case definition Low, planned intervention Low, other infection control High. Infection control interventions close to antibiotic stewardship interventions clearly documented in Figure 1.

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Other changes are clearly documented in Figure 1. This includes an outbreak of Acinetobacter infection co‐incident with the stewardship intervention, which resulted in appointment of 2 infection control practitioners and associated interventions. The additional staff could have influenced prescribing outcome.

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention is point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Pharmacy and microbiology routine data

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Pharmacy and microbiology routine data

Incomplete outcome data addressed (ITS) ?

Low risk

Pharmacy and microbiology routine data

Free of selected reporting (ITS) ?

Low risk

Pharmacy and microbiology routine data

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Annane 2013

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in participating ICUs
PARTICIPANTS: all patients in the ICUs with sepsis. Over a 3‐year period, 62/1250 screened patients were eligible for the study, of whom 31 were randomised to each arm
CLINICAL PROBLEM: sepsis
SETTING: 8 hospitals in France

Interventions

FORMAT, Interventions: structural ‐ rapid testing of PCT with decision support algorithm

Intervention Functions: enablement, environmental restructuring

DELIVERER: departmental physician
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 140 participants in total (70 in each arm) would be needed (details in Appendix 3)

Outcomes

PRESCRIBING: exposure, % receiving antibiotics at day 5

CLINICAL: mortality, length of ICU stay, length of hospital stay

MICROBIAL: colonisation with MRSA (nasal swab) and GNRB (rectal swabs)

Notes

FINANCIAL SUPPORT: Funding: commercial, Thermo Fisher B.R.A.H.M.S. France, a subsidiary of the maker of the PCT assay used in this study. Competing interests: none declared

ADDITIONAL INFORMATION: supplementary online file has PCT algorithm, authors provided full study protocol (in French)

Microbial Risk of Bias: MEDIUM (no data about infection control)

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer generated

Allocation concealment (selection bias)

Low risk

Central allocation

Blinding (performance bias and detection bias)
All outcomes

High risk

PCT levels not reported on control participants.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

No participants lost to follow‐up.

Selective reporting (reporting bias)

Low risk

No participants lost to follow‐up.

Other bias

High risk

Study stopped prematurely because of low recruitment.

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

PCT levels not reported on control participants.

Baseline characteristics similar?

Low risk

Table 1

Ansari 2003

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital

CLINICAL PROBLEM: antibiotics dispensed to hospital wards for administration for therapy or prophylaxis

SETTING: 1 university hospital in the UK

Interventions

FORMAT, Interventions: educational meetings; dissemination of educational materials; educational outreach by review and recommend change

Intervention Functions: education, enablement, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: total use of Alert Antibiotics in DDD/1000 OBD

FINANCIAL: cost of antibiotics adjusted for changes in price over the 4‐year study period. Cost of the Alert Antibiotic Monitoring intervention and of the setup and analysis of the ward antimicrobial supply database (Table 3)

Notes

FINANCIAL SUPPORT: no financial support. Competing Interests: none declared

ADDITIONAL DATA: email response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

"In 2000, the Antibiotic Subcommittee of Tayside University Hospitals Trust devised an Alert Antibiotic Policy to reduce inappropriate use of key antibiotics, targeted because they should be reserved for infections caused by organisms that are resistant to first line antimicrobials." There were no other changes in local or national policy likely to influence use of Alert Antibiotics.

Analysed appropriately (ITS) ?

Low risk

Done in original paper: segmented regression analysis with adjustment for autocorrelation and seasonality.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

"The aim of this study was to use routine data from the pharmacy stock control computer to evaluate this intervention". Sources and methods of data collection were the same before and after the intervention.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

"After evaluation of the intervention according to patient records and its shortcomings, we decided to use the pharmacy stock data. During the 4 year period of analysis no restriction policy for dispensing the Alert Antibiotics was implemented by the hospital pharmacy, therefore the pharmacy data about dispensed Alert Antibiotics would provide us with the best available independent indicator for evaluation of the intervention."

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

"Correcting for autocorrelation avoids underestimating standard errors
and overestimated significance of the effects of an intervention. For
estimating seasonal autocorrelation, the autoregression model needs to
evaluate correlations between error terms separated by multiples of
12 months. Accounting for seasonally correlated errors usually requires
at least 24 monthly data points."

Data about cost of antibiotics adjusted for price changes during study period.

Avorn 1988

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians at 1 teaching hospital
PARTICIPANTS: all patients with clinical problem
CLINICAL PROBLEM: patients receiving therapy with cefazolin, clindamycin, or metronidazole
SETTING: a 460‐bed teaching hospital in the USA

Interventions

FORMAT, Interventions: educational meetings; dissemination of educational materials; reminders ‐ circumstantial (order form triggered by receiving target antibiotic) and physical (posters)

Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: inappropriate dosing intervals of cefazolin, clindamycin, and metronidazole
FINANCIAL: estimated annual expenditure on the 3 drugs

Notes

FINANCIAL SUPPORT: Fund for Cooperative Innovation of Blue Cross of Massachusetts and the Massachusetts Hospital Association. Competing interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

No price changes in the target antibiotics during the study period.

Analysed appropriately (ITS) ?

Low risk

Done in original paper: segmented regression analysis.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Bailey 1997

Methods

STUDY DESIGN: RCT stratified by type of infection

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians at 2 teaching hospitals, excluding ICUs

PARTICIPANTS: a total of 102 inpatients, 51 intervention and 51 control

CLINICAL PROBLEM: patients receiving IV ABs for at least 3 days, but excluded if in ICU or with uncontrolled infection or close to discharge

SETTING: 2 tertiary‐care teaching hospitals in USA

Interventions

FORMAT, Interventions: educational outreach by review and recommend change

Intervention Functions: education, enablement, persuasion

DELIVERER: pharmacist

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: none reported

Outcomes

PRESCRIBING: patients switched from parenteral to oral antibiotics or discontinuation of 1 or more antibiotics and mean IV antibiotic days

COST: mean antibiotic costs

CLINICAL: 30‐day re‐admission (total and infection‐related) and in‐hospital mortality

Notes

FINANCIAL SUPPORT: Funding: Department of Pharmacy. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

"Physicians of patients considered candidates for intervention were randomised to be either contacted by the clinical pharmacist ... or to be observed"

Allocation concealment (selection bias)

Unclear risk

Not stated

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

Not stated

Incomplete outcome data (attrition bias)
All outcomes

Low risk

No problems found.

Selective reporting (reporting bias)

Low risk

No problems found.

Other bias

High risk

No power calculation. Prices of antibiotics unlikely to change over the 6‐month study period.

Baseline Outcomes similar?

Unclear risk

Not stated

Free of contamination?

Unclear risk

Not stated

Baseline characteristics similar?

Low risk

See Table 1 in study.

Bantar 2006

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital

CLINICAL PROBLEM: IV antibiotics, restriction applied to carbapenems

SETTING: a single university hospital in Argentina. Total use was compared for > 2 years before and after the intervention

Interventions

FORMAT, Intervention 1: educational outreach by review and recommend change; restrictive ‐ compulsory order form

Intervention Functions: education, enablement, persuasion, restriction

Intervention 2: unavailability of antibiotics during a national financial crisis

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive (choice)

Outcomes

PRESCRIBING: use of all IV antibiotics and carbapenems in DDD/1000 OBD

CLINICAL: all‐cause inpatient mortality

Notes

FUNDING: none. Competing Interests: 2 authors declared conflicts of interest for speaker and advisory board fees

ADDITIONAL INFORMATION: no response from authors

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Intervention 1 was independent of other changes. The "crisis" (following the intervention) was a national economic crisis and will be reported separately in the review.

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data were obtained from pharmacy systems.

Knowledge of the allocation adequately prevented(ITS)?

High risk

Prescribing data were processed by the investigators to convert grams to DDD and identify only IV antibiotics.

Incomplete outcome data addressed (ITS) ?

Low risk

Routine pharmacy data

Free of selected reporting (ITS) ?

Unclear risk

Processing of data has potential for selective outcome reporting.

Free of other bias (ITS) ?

Low risk

3 years' data pre‐ and 2 years' data postintervention

Barlow 2007

Methods

STUDY DESIGN: Controlled ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: all patients presenting with pneumonia were recruited prospectively

CLINICAL PROBLEM: adults with community‐acquired pneumonia

SETTING: 2 acute university hospitals in Scotland

Interventions

FORMAT, Interventions: audit and feedback; educational meetings; dissemination of educational materials; reminders ‐ physical by posters and email

Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: AMT

COMPARISON: control hospital with no intervention

DESIRED CHANGE: increase effective

Outcomes

PRESCRIBING: Choice: % appropriate antibiotics within 4 h of admission

COST: cost‐effectiveness, intervention cost, and estimated impact on mortality

Notes

FINANCIAL SUPPORT: Funding: NHS Education Scotland and Chief Scientist Office, Scotland. Competing Interests: none declared

ADDITIONAL DATA: email response from authors with additional information about intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Shape of effect pre‐specified (ITS) ?

Low risk

Unlikely to affect data collection (ITS) ?

Low risk

Knowledge of the allocation adequately prevented(ITS)?

High risk

Incomplete outcome data addressed (ITS) ?

Low risk

Free of selected reporting (ITS) ?

Low risk

Free of other bias (ITS) ?

High risk

Bassetti 2009

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the ICU (mixed medical/surgical)
PARTICIPANTS: all patients in the ICU
CLINICAL PROBLEM: requiring empirical antibiotic therapy
SETTING: 1 university hospital in Italy

Interventions

FORMAT, Interventions: educational outreach by review and recommend change; restrictive ‐ compulsory order form

Intervention Functions: education, enablement, persuasion, restriction

DELIVERER: specialist physicians (ID)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of cephalosporins in DDD/1000 OBD

MICROBIAL: MRSA

Notes

FINANCIAL SUPPORT: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: LOW

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Unlikely to affect data collection (ITS) ?

Low risk

Routine pharmacy data

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine pharmacy data

Incomplete outcome data addressed (ITS) ?

Low risk

Routine pharmacy data

Free of selected reporting (ITS) ?

Low risk

Routine pharmacy data

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention. Microbial Risk of Bias: case defintion done, planned intervention done, other infection control measures done.

Baysari 2013

Methods

STUDY DESIGN: unintended consequences, qualitative

Risk of Bias: not assessed (qualitative study)

Participants

PROVIDERS: 36 physicians
PARTICIPANTS: patients receiving antibiotic treatment
CLINICAL PROBLEM: patients receiving antibiotics that the hospital policy designated as requiring approval
SETTING: 1 hospital in Australia

Interventions

FORMAT, Intervention: audit and feedback; restriction by prior approval

Intervention Functions: enablement, persuasion, restriction

DELIVERER: AMT
DESIRED CHANGE: decrease excessive

Outcomes

UNINTENDED CONSEQUENCES: problems with antibiotic policy and approval process identified through semi‐structured interviews with prescribers who had received feedback letters

Notes

FINANCIAL SUPPORT: Funding: St Vincent’s Clinic Foundation Research Grant, annual Grant #3 and National Health and Medical Research Council program grant #568612. Competing Interests: none declared

ADDITIONAL DATA: email from authors with additional data about the antibiotic policy and feedback

Bell 2014

Methods

STUDY DESIGN: unintended consequences, ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in general, gynaecological, orthopaedic, urological, and vascular surgery wards
PARTICIPANTS: 12,883 patients undergoing elective surgery
CLINICAL PROBLEM: risk of postoperative AKI following policy change to gentamicin for prophylaxis
SETTING: 1 hospital in the UK

Interventions

FORMAT: Interventions: audit and feedback; educational meetings; dissemination of antibiotic policy; reminders (physical ‐ posters in operating theatres)
Intervention Functions: education, enablement, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive, the policy was intended to reduce Clostridium difficile infection

Outcomes

UNINTENDED CONSEQUENCES: % postoperative AKI before and after antibiotic policy change

Notes

FINANCIAL SUPPORT: Funding: Scottish Government Healthcare Associated Infection Task Force. Competing Interests: none declared

ADDITIONAL DATA: email response from authors but no additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Data from laboratory computer system (serum creatinine)

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from laboratory computer system

Incomplete outcome data addressed (ITS) ?

High risk

Completeness of pre‐ and postoperative creatinine data presented in full for all services (Table 2). There was a significant increase in testing after policy change in gynaecology.

Free of selected reporting (ITS) ?

Low risk

Data from laboratory computer system

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Belliveau 1996

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in hospital

PARTICIPANTS: all patients in hospital

CLINICAL PROBLEM: patients receiving vancomycin therapy

SETTING: 1 university hospital in the USA

Interventions

FORMAT, Interventions: educational meetings; dissemination of educational materials; educational outreach by academic detailing; reminders (physical ‐ posters and newsletter); restrictive ‐ expert approval

Intervention Functions: education, environmental restructuring, persuasion, restriction

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: vancomycin doses/1000 OBD

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

> 12 months' pre‐ and postrestriction data

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper (comparison of means with t‐test, uncontrolled before‐after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention. Outcome data were collected from all participants.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Benson 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients receiving therapeutic antibiotics
SETTING: 1 university hospital in the USA

Interventions

FORMAT, Interventions: audit and feedback; educational outreach by academic detailing

Intervention Functions: education, enablement, persuasion

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: antibiotic cost per patient day

Notes

FINANCIAL SUPPORT: none. Competing Interests; none declared

ADDITIONAL INFORMATION: no response from author

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Electronic data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Electronic data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Electronic data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Electronic data from pharmacy computer

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Berild 2002

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: physicians (paediatricians) in the hospital

PARTICIPANTS: all paediatric patients in the hospital

CLINICAL PROBLEM: children with infections requiring antibiotic therapy

SETTING: 1 paediatric university hospital in Norway

Interventions

FORMAT, Interventions: audit and feedback; educational meetings; dissemination of educational materials

Intervention Functions: education, enablement

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: total antibiotic usage and usage of 5 specific groups of antibiotics in DDD/100 OBD

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Done, 3 years' pre‐intervention and 2 years' postintervention data

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper (run charts, Figure 1, with no statistical analysis).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

Changes in antibiotic price were documented with their contribution to reduction in cost over the study period (Table 1 in study).

Borde 2014a

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians and pharmacists in the Medical Service
PARTICIPANTS: all adult patients in the Medical Service

CLINICAL PROBLEM: patients receiving antibiotics
SETTING: 1 university hospital in Germany

Interventions

FORMAT, Interventions: audit and feedback; educational meetings; dissemination of educational materials; educational outreach by review and recommend change; reminders ‐ circumstantial, on rounds

Intervention Functions: education, enablement, persuasion

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive, aim was to reduce use of 3rd‐generation cephalosporins and fluoroquinolones by 30% in 12 months

Outcomes

PRESCRIBING: Choice: drug use measured in RDD/100 OBD

FINANCIAL: cost of intervention and impact on prescribing cost

Notes

FINANCIAL SUPPORT: Funding: internal funds from the Department of Medicine and Federal Ministry of Health (BMG grant IIA5‐2011‐2511FSB340). Competing Interests: none declared

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Prescribing data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Prescribing data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Prescribing data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Prescribing data from pharmacy computer

Free of other bias (ITS) ?

Low risk

> 24 months' data pre‐ and postintervention

Borde 2014b

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients with Staphylococcus aureus bacteraemia
CLINICAL PROBLEM: compliance with a bundle of indicators of effective treatment and investigation
SETTING: 1 community hospital in Southern Germany

Interventions

FORMAT, Interventions: dissemination of educational materials; reminders ‐ circumstantial, on microbiology reports for positive blood cultures

Intervention Functions: education, enablement, environmental restructuring

DELIVERER: ID physician
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

PRESCRIBING: Choice: average score per participant, with 0.5 points for each of 4 prescribing indicators, maximum score 2.0 per participant

CLINICAL: not valid (mean mortality in pre‐ and postintervention phases)

Notes

FINANCIAL SUPPORT: Funding: internal funds from the Department of Medicine and Federal Ministry of Health (BMG grant IIA5‐2011‐2511FSB340). Competing Interests: none declared

ADDITIONAL DATA: the original paper reports average scores per participant for compliance, with 5 bundle elements of which only 2 were about antibiotic prescribing (Figure 2). The authors provided us with additional data about scores for the 2 prescribing elements in the bundle.

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

High risk

Prescribing outcomes were collected by the investigators.

Knowledge of the allocation adequately prevented(ITS)?

High risk

Prescribing outcomes were collected by the investigators.

Incomplete outcome data addressed (ITS) ?

Unclear risk

Data are presented as % compliance per quarter, but it is not clear whether complete data were collected from all participants.

Free of selected reporting (ITS) ?

Unclear risk

Data are presented as % compliance per quarter, but it is not clear whether complete data were collected from all participants.

Free of other bias (ITS) ?

High risk

Only 9 months' data postintervention

Borde 2015a

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians caring for medical emergency patients
PARTICIPANTS: all medical patients in the ED
CLINICAL PROBLEM: patients requiring antibiotic treatment
SETTING: 1 university hospital in Germany

Interventions

FORMAT, Interventions: audit and feedback; educational meetings; dissemination of educational materials; educational outreach by review and recommend change; reminders ‐ circumstantial, on rounds

Intervention Functions: education, enablement, persuasion

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive, aim was to reduce use of 3rd‐generation cephalosporins by 20% in 12 to 24 months

Outcomes

PRESCRIBING: Choice: drug use measured in RDD/100 OBD

Notes

FINANCIAL SUPPORT: Funding: internal funds from the Department of Medicine and Federal Ministry of Health (BMG grant IIA5‐2011‐2511FSB340). Competing Interests: none declared

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy computer

Free of other bias (ITS) ?

Low risk

> 24 months' data pre‐ and postintervention

Borde 2015b

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians and pharmacists in the Medical Service
PARTICIPANTS: all adult patients in the Medical Service

CLINICAL PROBLEM: patients receiving antibiotics
SETTING: 1 200‐bed community hospital

Interventions

FORMAT, Interventions: educational meetings; dissemination of educational materials; educational outreach by review and recommend change in ICU and for bacteraemic patients in other wards; reminders ‐ circumstantial, on rounds

Intervention Functions: education, enablement, persuasion

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive, aim was to reduce use of 3rd‐generation cephalosporins and fluoroquinolones by 30% in 12 months

Outcomes

PRESCRIBING: Choice: target drug use measured in RDD/100 OBD. Exposure: impact on total anti‐infective use was measured

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy computer

Free of other bias (ITS) ?

Low risk

> 12 months' data pre‐ and postintervention

Bouadma 2010

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the ICU
PARTICIPANTS: all patients in the ICU, 311 randomised to intervention and 319 to control
CLINICAL PROBLEM: patients requiring antibiotic treatment
SETTING: 5 hospitals in France, 4 university and 1 general

Interventions

FORMAT, Interventions: reminders ‐ circumstantial; structural ‐ procalcitonin testing with decision support by treatment algorithm

Intervention Functions: enablement, environmental restructuring

DELIVERER: departmental physicians (Anaesthesiology and Intensive Care)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 133 participants per study group (details in Appendix 3)

Outcomes

PRESCRIBING: Exposure: days of antibiotic exposure per 1000 patient days

CLINICAL: primary outcome measure 28‐day mortality, also 60‐day mortality, length of ICU stay, and length of hospital stay

Notes

FINANCIAL SUPPORT: Funding: Assistance Publique‐Hopitaux de Paris, France and B.R.A.H.M.S, Germany. Competing Interests: 4 authors declared conflicts of interest from several pharmaceutical companies

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer‐generated randomisation sequence

Allocation concealment (selection bias)

Low risk

Assignment concealed before allocation.

Blinding (performance bias and detection bias)
All outcomes

High risk

Assignment not concealed postallocation.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcome data reported on 98% of participants in control and intervention groups.

Selective reporting (reporting bias)

Low risk

Outcome data reported fully on all included participants.

Other bias

High risk

Patients assigned to the trial were < 50% of all patients receiving antibiotics (630/1315).

Baseline Outcomes similar?

High risk

No data

Free of contamination?

Low risk

Procalcitonin only reported on intervention participants.

Baseline characteristics similar?

Low risk

ITS

Bouza 2004

Methods

STUDY DESIGN: RCT

Risk of bias: HIGH

Participants

PROVIDERS: ICU staff

PARTICIPANTS: 297 patients with bloodstream infection in hospital, 109 control and 188 intervention

CLINICAL PROBLEM: bacteraemia/fungaemia (bloodstream infection)

SETTING: 1 university hospital in Spain

Interventions

FORMAT, Interventions: educational outreach by review and recommend change

Intervention Functions: education, enablement, persuasion

DELIVERER: microbiologists (specialist physicians)

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

POWER CALCULATION: no information about sample size

Outcomes

PRESCRIBING: Choice: proportion of days on which adequate treatment received

CLINICAL: Intended: length of stay, mortality

Notes

FINANCIAL SUPPORT: Funding: Red Española de Investigación de Patología Infecciosa (REIPI C03‐14) and Fondo de Investigaciones Sanitarias of Spain (FIS 02‐1049). Competing Interest: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"We randomly classified the patients ... into 3 different group by means of a computer assisted random list"

Allocation concealment (selection bias)

Unclear risk

No information

Blinding (performance bias and detection bias)
All outcomes

High risk

Not possible with this study design

Incomplete outcome data (attrition bias)
All outcomes

Unclear risk

Not stated

Selective reporting (reporting bias)

Unclear risk

Not stated

Other bias

High risk

Not done, adequate prescription was defined by 7 criteria, some of which required clinical judgement. The reliability of the primary outcome measure was not assessed.

Baseline Outcomes similar?

Unclear risk

Not stated

Free of contamination?

High risk

All doctors in the hospital were distributed across all 3 study groups.

Baseline characteristics similar?

Unclear risk

Not stated

Bouza 2007

Methods

STUDY DESIGN: RCT

Risk of bias: HIGH

Participants

PROVIDERS: ICU staff

PARTICIPANTS: 250 patients in the adult ICU, 167 intervention and 83 control

CLINICAL PROBLEM: ventilator‐associated pneumonia with bacteria identified on gram stain of first tracheal aspirate

SETTING: single general, teaching, and referral hospital in Spain

Interventions

FORMAT, Interventions: educational outreach by review and recommend change

Intervention Functions: education, enablement, persuasion

DELIVERER: microbiologists (specialist physicians)

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

POWER CALCULATION: no information about sample size

Outcomes

PRESCRIBING: Exposure: mean days of therapy

MICROBIAL: Clostridium difficile infection

CLINICAL:Balancing: median days of fever and mechanical ventilation

FINANCIAL: cost of antibiotics

Notes

Microbial Risk of Bias HIGH: no case definition, no details of other infection control measures

ADDITIONAL DATA: no response from authors to request for additional data

FINANCIAL SUPPORT: Red Española de Investigación de Patología Infecciosas (REIPI) and Fondo de Investigación Sanitaria (FIS). The Spanish Ministry of Health (BEFI BF03/00237, to M.V.T.). Competing Interest: none declared

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer generated

Allocation concealment (selection bias)

Low risk

Computer generated

Blinding (performance bias and detection bias)
All outcomes

High risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all participants.

Selective reporting (reporting bias)

Unclear risk

No primary outcome measure identified. Defined daily dose of antibiotic therapy free from selective reporting, but other outcomes (e.g. % adequate days of antibiotic therapy) were not.

Other bias

High risk

High microbial risk of bias

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

ETEST results only available for intervention group.

Baseline characteristics similar?

Low risk

Table 1

Bradley 1999

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: physicians in an adult haematology unit

PARTICIPANTS: all patients with clinical problem

CLINICAL PROBLEM: adult patients receiving treatment for haematological malignancy

SETTING: adult haematology unit in a university hospital in the UK

Interventions

FORMAT, Interventions: restrictive

Intervention Functions: restriction by removal

DELIVERER: specialist physician (microbiologist)

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of 4 principal IV antibiotics in patient days per month

MICROBIAL: probability of remaining free of colonisation by GRE by weeks of exposure on the ward from date of first admission

Notes

FINANCIAL SUPPORT: Funding: commercial, Wyeth Pharmaceuticals. Competing Interest: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Only 4 months' pre‐intervention data, so secular changes possible.

Analysed appropriately (ITS) ?

Low risk

Done in original paper: Kaplan‐Meier plot and log rank test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, screening protocol was the same throughout the study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, screening protocol was the same throughout the study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, screening protocol was the same throughout the study period.

Free of selected reporting (ITS) ?

Low risk

Done, screening protocol was the same throughout the study period.

Free of other bias (ITS) ?

Low risk

Microbiology Risk of Bias Criteria: Case definition: DONE, colonisation by screening; Planned intervention: DONE; Other infection control, isolation, and IC practices: DONE, same throughout study.

Bruins 2005

Methods

STUDY DESIGN: NRT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: 1833 patients with bacterial infection in hospital in 3 study periods. Period 1: 294 intervention, 320 control; Period 2: 303 intervention, 317 control; Period 3: 308 intervention, 328 control

CLINICAL PROBLEM: inappropriate antibiotic therapy

SETTING: 1 university hospital in the Netherlands

Interventions

FORMAT, Interventions: structural ‐ rapid microbiology laboratory testing

Intervention Functions: environmental restructuring

DELIVERER: specialist physician (microbiologist)

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

POWER CALCULATION: yes, 296 participants in each study arm (details in Appendix 3)

Outcomes

PRESCRIBING: % of participants who receive appropriate treatment in first 48 h. Turnaround times for microbiology tests and results

CLINICAL: intended clinical outcomes, total hospital mortality rate and length of hospital stay

COST: valid financial savings

Notes

FINANCIAL SUPPORT: Funding: commercial, bioMerieux and Stichting Zorg op Regionale ´ Grondslag (ZORG). Competing Interest: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

Quasi‐randomised. "Patients were randomised on the basis of the sum of the day and month of their date of birth ... even numbers assigned to the control group ... odd number to the intervention group"

Allocation concealment (selection bias)

High risk

Allocation not concealed.

Blinding (performance bias and detection bias)
All outcomes

High risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Selective reporting (reporting bias)

Low risk

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

Rapid reports only received by intervention group.

Baseline characteristics similar?

Low risk

Table 1

Buising 2008a

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: use of restricted antibiotics: cephalosporins, carbapenems, quinolones, glycopeptides, and aminoglycosides
SETTING: 1 university hospital in Australia

Interventions

FORMAT, Interventions: audit and feedback; educational outreach by review and recommend change; restrictive ‐ expert approval and removal

Intervention Functions: education, enablement, environmental, persuasion, restriction

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of restricted antibiotics in DDD/1000 OBD

MICROBIAL: ARGNB (Escherichia coli,Pseudomonas aeruginosa); ARGPB (MRSA)

Notes

FINANCIAL SUPPORT: Funding: National Health and Medical Research Council of Australia; Biotechnology Innovation Fund from the Commonwealth Government of Australia; Melbourne Health. Competing Interest: none declared

Microbial Risk of Bias: LOW (case definition, planned intervention, and other infection control measures all low risk)

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analysis is point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology systems

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology systems

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology systems

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology systems

Free of other bias (ITS) ?

Low risk

5 years' pre‐ and 2 years' postintervention data

Buising 2008b

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the ED
PARTICIPANTS: all patients with community‐acquired pneumonia in the ED
CLINICAL PROBLEM: rate of empiric antibiotic prescribing that was concordant with recommendations
SETTING: 1 university hospital in Australia

Interventions

FORMAT, Interventions 1: educational outreach by academic detailing; reminders ‐ physical, posters

Intervention Functions: education, environmental restructuring, persuasion

Intervention 2: structural ‐ computerised decision support

Intervention Functions: enablement, environmental restructuring
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: % prescribing concordant with recommendation

Notes

FINANCIAL SUPPORT: Funding: National Health and Medical Research Council of Australia. Competing Interest: none declared

ADDITIONAL DATA: email response from authors with further details about intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Junior staff who were targets of the intervention rotated every 3 months.

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data collection was identical in all 3 phases.

Knowledge of the allocation adequately prevented(ITS)?

High risk

The nurse and physicians who collected data were not blinded to allocation.

Incomplete outcome data addressed (ITS) ?

Low risk

Data were collected from all eligible participants.

Free of selected reporting (ITS) ?

Low risk

Data were collected from all eligible participants. The accuracy of data collection was checked in a 5% sample of participants.

Free of other bias (ITS) ?

High risk

1 year of data in pre‐ and Intervention 1 time series, but only 6 months' data for Intervention 2

Bunz 1990

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in hospital

PARTICIPANTS: all patients in hospital

CLINICAL PROBLEM: receiving metronidazole

SETTING: single university hospital in Canada

Interventions

FORMAT, Interventions: educational meetings; dissemination of educational materials; reminders ‐ circumstantial, on rounds; restrictive ‐ review and make change

Intervention Functions: education, enablement, restriction

DELIVERER: pharmacist

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: % doses of metronidazole prescribed 12‐hourly

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Although the pre‐ and postintervention phases were only a 6‐month period, data from 1 year prior to the intervention were used to control for any seasonal variation in prescribing patterns.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: run charts with no statistical analysis.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, the analysis included all prescriptions for metronidazole.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Burton 1991

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in hospital

PARTICIPANTS: 147 receiving aminoglycosides

CLINICAL PROBLEM: patients receiving IV aminoglycosides

SETTING: 1 hospital in the USA

Interventions

FORMAT, Interventions: educational outreach by review and recommend change

Intervention Functions: education, enablement, persuasion

DELIVERER: pharmacist

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

POWER CALCULATION: no information about sample size

Outcomes

PRESCRIBING: Choice: aminoglycoside dosing and serum concentration

CLINICAL: Intended: length of stay

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"Random numbers table used to assign 9 of 17 house staff teams to the intervention group. Patients allocated to intervention or control groups based on house staff team to which they were admitted. The other 8 teams were assigned as control groups"

Allocation concealment (selection bias)

Unclear risk

Not stated but unlikely: 9 house staff teams were in the intervention group, 8 control, groups swapped over after 4 months.

Blinding (performance bias and detection bias)
All outcomes

High risk

"Blinding as to patient status was not performed"

Incomplete outcome data (attrition bias)
All outcomes

Low risk

No problems found.

Selective reporting (reporting bias)

Low risk

No problems found.

Other bias

High risk

Unit of analysis error for length of stay. This was a cluster RCT, but length of stay was analysed at participant level.

Baseline Outcomes similar?

Unclear risk

Not measured before interventions.

Free of contamination?

High risk

Not done, 9 house staff teams were in the intervention group, 8 control, groups swapped over after 4 months.

Baseline characteristics similar?

Low risk

See Table 2 in paper.

Buyle 2010

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in hospital

PARTICIPANTS: all patients receiving IV fluoroquinolones

CLINICAL PROBLEM: switch from IV fluoroquinolones to oral

SETTING: 1 hospital in Belgium

Interventions

FORMAT, Interventions: educational meetings; dissemination of guideline; reminders ‐ circumstantial and physical (pre‐printed note placed in patient notes when the patient fulfilled criteria for IV to oral switch). NB: the circumstantial reminder was only implemented on some wards (abdominal surgery, gastro‐enterology, and plastic surgery) over 2 months, and there are no reliable data to estimate the effect of this component.

Intervention Functions: education, enablement (only for the circumstantial reminder), environmental restructuring (only for the circumstantial reminder)

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

Outcomes

PRESCRIBING: Choice: % IV/(IV + oral) fluoroquinolone usage

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interest: none declared

ADDITIONAL DATA: email from authors with further information about the intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data for ITS from pharmacy computer (Figure 1). Other data in Tables 2 and 3 not valid, UBA.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data for ITS from pharmacy computer (Figure 1). Other data in Tables 2 and 3 not valid, UBA.

Incomplete outcome data addressed (ITS) ?

Low risk

Data for ITS from pharmacy computer (Figure 1). Other data in Tables 2 and 3 not valid, UBA.

Free of selected reporting (ITS) ?

Low risk

Data for ITS from pharmacy computer (Figure 1). Other data in Tables 2 and 3 not valid, UBA.

Free of other bias (ITS) ?

Low risk

21 months' pre‐ and 24 months' postintervention

Calfee 2003

Methods

STUDY DESIGN: unintended consequences, case control

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in adult medical and surgical units
PARTICIPANTS: all patients in the units
CLINICAL PROBLEM: use of targeted antibiotics (3rd‐generation cephalosporins, piperacillin/tazobactam, aztreonam, carbapenems, parenteral clindamycin, oral and parenteral vancomycin, parenteral fluoroquinolones and macrolides, and fluconazole)
SETTING: 1 hospital in the USA

Interventions

FORMAT, Interventions: restrictive by review and make change, automatic stop order for prescriptions not meeting policy indications
Intervention Functions: restriction
DELIVERER: AMT
COMPARISON: case control study
DESIRED CHANGE: decrease excessive use of targeted drugs

Outcomes

UNINTENDED CONSEQUENCES: proportion of nosocomial infections reported solely on the basis of a treating physician’s diagnosis during the endemic and epidemic periods (Table 1)

Notes

ROBINS‐I RISK OF BIAS CRITERIA:

1. Confounding: Low, confounding unlikely

2. Selection of participants into the study: Unclear, insufficient detail about selection of cases for the endemic and epidemic period

3. Measurement classification of interventions: Low, intervention status well defined, recorded at the time of intervention, and unaffected by knowledge of the outcome or risk of the outcome

4. Deviation from intended interventions: Low, no switches to other interventions or evidence of intervention failure

5. Missing data: Unclear, outcomes are reported as % with no numerator or denominator data

6. Measurement of outcome: High, outcome measure objective, but outcome assessors were aware of the intervention status, and the study does not report the actual number of cases

7. Selection of the reported result: High, reported effect selected from multiple measurements within the outcome domain

FINANCIAL SUPPORT:Funding: no information. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Calil 2001

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: staff in a neonatal unit
PARTICIPANTS: all patients in the neonatal care unit

CLINICAL PROBLEM: requiring neonatal care

SETTING: 1 neonatal care unit in a university hospital in Brazil

Interventions

FORMAT: no valid prescribing data. Restrictive

DELIVERER: specialist physician

COMPARISON: usual carer

DESIRED CHANGE: decrease exessive

Outcomes

MICROBIAL: monthly incidence of Enterobacter cloacae infections

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

More than 1 year of data before and after intervention

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after) with logistic regression analysis of relationship between antibiotic prescribing and resistance.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Unclear risk

Not clear, no information about changes in sampling or testing protocol over study period.

Free of other bias (ITS) ?

High risk

Not done.

Microbial Risk of Bias Criteria: Case definition: infection, monthly infections with E cloacae; Unplanned intervention: other infection control measures: barrier precautions, isolation of participants, and personal IC procedures fully described and same in both phases.

Camins 2009

Methods

STUDY DESIGN: cluster RCT, service level

Risk of Bias: HIGH

Participants

PROVIDERS: all internal medicine teams in the hospital
PARTICIPANTS: 784 patients prescribed antibiotics in the hospital (390 intervention, 394 control), 12 clusters (internal medicine teams)

CLINICAL PROBLEM: patients receiving therapeutic piperacillin‐tazobactam, levofloxacin, or vancomycin

SETTING: 1 hospital in the USA

Interventions

Interventions: audit and feedback; dissemination of guidelines; educational outreach by review and recommend change

Intervention Functions: education, enablement, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease in excessive treatment

POWER CALCULATION: assuming a baseline proportion of inappropriate use for target antimicrobials of 35% (with inappropriate‐use data based on preliminary‐usage data from Grady Memorial Hospital), review of at least 330 antimicrobial prescriptions in each arm would allow for detection of a 10% reduction in inappropriate antimicrobial use.

Outcomes

PRESCRIBING: Choice: % appropriate

Notes

FINANCIAL SUPPORT: Emory Medical Care Foundation; National Institutes of Health (UL1RR024992 to BCC, K12 RR017643 to MDK and HMB, K23 AI054371 to MDK, and UL1 RR025008 to HMB). Competing Interests: BCC reports was on the speakers’ bureau for Wyeth Pharmaceuticals. All other authors report no conflicts of interest.

ADDITIONAL DATA: no additional data requested

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Each month, 6 internal medicine teams were randomly assigned to the intervention arm, and 6 teams were randomly assigned to the control group by means of a random number list.

Allocation concealment (selection bias)

High risk

Not concealed

Blinding (performance bias and detection bias)
All outcomes

High risk

Not blinded

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all participants.

Selective reporting (reporting bias)

Low risk

Outcomes reported on all participants.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

High risk

Doctors randomised to intervention were in the same hospital as control doctors.

Baseline characteristics similar?

Low risk

Carling 2003

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: NOT CLEAR
SETTING: 1 community teaching hospital in the USA

Interventions

FORMAT: no valid prescribing data. Educational outreach ‐ review and recommend change; educational meetings with dissemination of educational materials
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

MICROBIAL: prevalence of Clostridium difficile, ceftazidime‐resistant Enterobacteriaceae, and MRSA

FINANCIAL: cost of intervention

Notes

FINANCIAL SUPPORT: Funding: institutional support. Competing Interests: none declared

ADDITIONAL DATA: no additional data requested

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

3 years' pre‐intervention data

Analysed appropriately (ITS) ?

Low risk

Done in original paper: regression analysis with adjustment for autocorrelation. Analysis repeated by review team because of incomplete reporting of results.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Unclear risk

Not clear, no information about changes in sampling or testing protocol over study period.

Free of other bias (ITS) ?

Low risk

VRE isolation unlikely to have influenced C difficile or resistant gram‐negative bacteria. Microbial Risk of Bias Criteria: Planned intervention: DONE Implementation of antimicrobial management team in response to increase in use of target drugs. Case definition: DONE for C difficile infection (diarrhoea and toxin positive) or infection with clinical isolates of gram‐negative bacteria resistant to ceftazidime, or MRSA (CDC definition of nosocomial infection). Other infection control measures: DONE For C difficile contact precautions and procedures for cleansing equipment and patient care areas remained unchanged. Other infection control processes are not described in detail but may have changed during the study period (e.g. VRE isolation introduced after intervention). Data about VRE infections NOT RELIABLE: There were no cases in the pre‐intervention phase and none in the first 3 years postintervention, but there was an outbreak in the 4th and 5th postintervention years caused by admission of patients from other hospitals who were colonised with VRE.

Chan 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients
CLINICAL PROBLEM: use of restricted antibiotics (amikacin, 3rd‐ and 4th‐generation cephalosporins, carbapenems, fluoroquinolones, glycopeptides, and piperacillin/tazobactam)
SETTING: 1 university hospital in Taiwan

Interventions

FORMAT, Interventions: educational outreach by review and recommend change; restrictive ‐ expert approval required plus review and make change

Intervention Functions: education, enablement, persuasion, restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: DDD/1000 OBD of restricted antibiotics

MICROBIAL: isolation rates Clostridium difficile, MRSA, and multidrug‐resistant gram‐negative bacteria

Notes

ADDITIONAL DATA: no response from authors to request for additional data

FINANCIAL SUPPORT: Funding: Chang Gung Memorial Hospital (Taoyuan, Taiwan) (grant CMRPG340236). Competing Interests: none declared

Microbial Risk of Bias: HIGH (case definition clear, planned intervention but no data about infection control)

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

States in discussion that biggest limitation was lack of external controls, but that is common to all ITS studies.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Unclear risk

DDD data from pharmacy computer, the same pre‐ and postintervention

Knowledge of the allocation adequately prevented(ITS)?

Low risk

DDD data from pharmacy computer, the same pre‐ and postintervention

Incomplete outcome data addressed (ITS) ?

Low risk

DDD data from pharmacy computer, the same pre‐ and postintervention

Free of selected reporting (ITS) ?

Low risk

DDD data from pharmacy computer, the same pre‐ and postintervention

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Chan 2015

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients requring vancomycin
CLINICAL PROBLEM: patients requiring more than 2 doses of vancomycin treatment
SETTING: 1 university hospital in the USA

Interventions

FORMAT Interventions: restrictive ‐ expert approval

Intervention Functions: restriction
DELIVERER: AMT
COMPARISON: pre‐existing antimicrobial stewardship programme with audit and feedback. No valid data about impact of this programme (UBA).
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of vancomycin in DDD/1000 OBD

Notes

FINANCIAL SUPPORT: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Unlikely to affect data collection (ITS) ?

Low risk

Routine data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Routine data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Routine data from pharmacy computer

Free of other bias (ITS) ?

Low risk

21 months' pre‐ and 51 months' postintervention data

Chandy 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving antibiotics
CLINICAL PROBLEM: total antibiotic use in the hospital
SETTING: 1 university hospital in India

Interventions

FORMAT Interventions: dissemination of educational materials (guidelines)

Intervention Functions: education
DELIVERER: AMT
COMPARISON: pre‐dissemination
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: total antibiotic use in DDD/100 OBD

Notes

FINANCIAL SUPPORT: none. Competing Interests: none declared

ADDITIONAL INFORMATION: authors provided additional detail about the antibiotic policy and confirmed that feedback was not used in this intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Unlikely to affect data collection (ITS) ?

Low risk

Routine data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Routine data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Routine data from pharmacy computer

Free of other bias (ITS) ?

Low risk

> 18 months' data pre‐ and postintervention

Charbonneau 2006

Methods

STUDY DESIGN: Controlled ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in hospital

PARTICIPANTS: all patients who qualified for fluoroquinolone therapy

CLINICAL PROBLEM: infection with MRSA

SETTING: 1 university hospital in France

Interventions

FORMAT: no valid prescribing data. Restriction, educational meetings, and dissemination of educational materials

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

MICROBIAL: reduction of MRSA infections

Notes

FINANCIAL SUPPORT: Funding: Programme Hospitalier de Recherche Clinique. Competing Interests: none declared

ADDITIONAL DATA: no request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

1 year post‐ and 2 years' pre‐intervention data, so secular changes unlikely. Infection control protocols were unchanged pre‐ and postintervention.

Analysed appropriately (ITS) ?

Low risk

Done in original paper: the study is analysed as a CBA adjusting for confounders and slope and level. The ITS analyses are correct, but the results are not well reported.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Unclear risk

Not clear, no information about changes in sampling or testing protocol over study period.

Free of other bias (ITS) ?

Low risk

Microbial Risk of Bias Criteria: Planned intervention: DONE Case definition: DONE clear case definition of clinical infection: "A new case was defined as a case in a patient with no previous history of MRSA or ESBL‐EB colonization or infection who was infected with MRSA or ESBL‐EB no less than 48 h after hospital admission." Other infection control measures: DONE "The measures recommended by French national guidelines for the prevention of nosocomial infections were implemented in the 4 study hospitals several years before the study began"

Cheng 2009

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving IV antibiotics
CLINICAL PROBLEM: reduce inappropriate prescribing of broad‐spectrum IV antibiotics in hospital inpatients
SETTING: 1 university hospital in China

Interventions

FORMAT, Interventions: educational meetings with dissemination of guidelines; educational outreach by review and recommend change
Intervention Functions: education, enablement, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of targeted antibiotics in DDD/1000 OBD

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

Does not mention other changes apart from preceding Antimicrobial Stewardship Programme.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Routine pharmacy data used for outcome, so assume complete.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine pharmacy data used for outcome, so assume complete.

Incomplete outcome data addressed (ITS) ?

Low risk

Routine pharmacy data used for outcome, so assume complete.

Free of selected reporting (ITS) ?

Low risk

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Christ‐Crain 2004

Methods

STUDY DESIGN: cluster RCT

Risk of bias: MEDIUM

Participants

PROVIDERS: physicians in hospital
PARTICIPANTS: 234 patients (124 intervention, 119 control), 16 clusters (weeks randomly assigned to either standard or procalcitonin)

CLINICAL PROBLEM: suspected  lower respiratory tract infection

SETTING: 1 university hospital in Switzerland

Interventions

FORMAT, Interventions: dissemination of educational materials; reminders ‐ circumstantial and physical (procalcitonin algorithm) triggered by prescribing antibiotics; structural

Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: department physician

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 105 participants in each group

Outcomes

PRESCRIBING: Choice: relative risk of antibiotic exposure measured in percentage and patient‐days

CLINICAL: Balancing: length of stay; mortality

Notes

FINANCIAL SUPPORT: Funding: B.R.A.H.M.S (Hennigsdorf, Germany) and Orgenium Laboratories (Turku, Finland) provided assay material and partial support of this investigator‐initiated project. Freiwillige Akademische Gesellschaft Basel, Switzerland; internal from the Department of Internal Medicine and the Divisions of Endocrinology and Pneumology. Competing Interests: BM served as consultant and received payments from B.R.A.H.M.S (the manufacturer of procalcitonin assays) to attend meetings related to the trial and for travel expenses, speaking engagements, or research

ADDITIONAL DATA: email response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"We randomly assigned eligible patients ... according to a computer generated week wise randomisation scheme"

Allocation concealment (selection bias)

Unclear risk

"We randomly assigned eligible patients either standard antimicrobial therapy (standard group) or procalcitonin‐guided antimicrobial treatment (procalcitonin group) according to a computer‐generated week wise randomisation scheme". No information about concealment of allocation

Blinding (performance bias and detection bias)
All outcomes

Low risk

"Single blinded intervention trial"

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Antibiotic data from all treated participants

Selective reporting (reporting bias)

Low risk

Objective outcome measure in all participants

Other bias

Low risk

No other apparent biases found.

Baseline Outcomes similar?

Unclear risk

Not stated

Free of contamination?

Low risk

Although same doctors treated participants in non‐intervention weeks, they did not have data about procalcitonin results.

Baseline characteristics similar?

Low risk

Done, Tables 1 and 2 in the original paper

Christ‐Crain 2006

Methods

STUDY DESIGN: RCT

Risk of bias: MEDIUM

Participants

PROVIDERS: physicians in hospital
PARTICIPANTS: 302 patients (151 intervention, 151 control)

CLINICAL PROBLEM: suspected community‐acquired pneumonia

SETTING: 1 university hospital in Switzerland

Interventions

FORMAT, Interventions: dissemination of educational materials; reminders ‐ circumstantial and physical (procalcitonin algorithm) triggered by prescribing antibiotics; structural

Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: department physician

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 150 participants in each group

Outcomes

PRESCRIBING: Choice: relative risk of antibiotic exposure, total antibiotic use. Duration of antibiotic course

CLINICAL: Balancing: mortality and length of hospital stay

FINANCIAL: total antibiotic cost and cost per patient

Notes

FINANCIAL SUPPORT: Funding: B.R.A.H.M.S (Hennigsdorf, Germany), Pfizer (Schweiz AG), and Mepha (Schweiz AG) was used for assay material and salaries of technical personnel; internal from Departments of Internal Medicine and Emergency Medicine, the Stiftung Forschung Infektionskrankheiten (SFI), and Departments of Endocrinology and Pulmonary Medicine, University Hospital Basel, Switzerland. Competing Interests: 2 authors received payments from B.R.A.H.M.S AG, the manufacturer of the procalcitonin assay.

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

"Patients were randomly assigned to one of the two groups by sealed opaque envelopes", no information about generation of randomisation sequence

Allocation concealment (selection bias)

Low risk

"Sealed opaque envelopes"

Blinding (performance bias and detection bias)
All outcomes

Low risk

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Selective reporting (reporting bias)

Low risk

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

Same doctors in the intervention and control weeks, but they did not have access to procalcitonin results in the control weeks.

Baseline characteristics similar?

Low risk

Done, Table 1 in the original paper

Chu 2003

Methods

STUDY DESIGN: CBA

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: patients with clinical problem
CLINICAL PROBLEM: community‐acquired pneumonia
SETTING: a total of 36 (20 intervention, 16 control), non‐university community hospitals in USA

Interventions

FORMAT, Interventions: audit and feedback; educational meetings; dissemination of educational materials ‐ pack including guideline and literature review

Intervention Functions: education, enablement
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

PRESCRIBING: Choice: process measures sputum and blood cultures within 4 hours, antibiotics within 4 hours, first antibiotic in emergency room
CLINICAL: Intended: mortality and LOS

Notes

FINANCIAL SUPPORT: Funding: contract 500‐99‐P619 "Utilization and Quality Control Peer Review Organization for the State of Oklahoma" from the Centers for Medicare and Medicaid Services. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

Control cohort study (CBA)

Allocation concealment (selection bias)

High risk

Control cohort study (CBA)

Blinding (performance bias and detection bias)
All outcomes

High risk

Control cohort study (CBA)

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Objective primary outcome collected on all participants.

Selective reporting (reporting bias)

Low risk

Objective primary outcome collected on all participants.

Other bias

Low risk

No other apparent biases found.

Baseline Outcomes similar?

Low risk

Tables 1 and 2

Free of contamination?

Low risk

Intervention and control were at different sites.

Baseline characteristics similar?

Low risk

Tables 3 and 4

Clerc 2014

Methods

STUDY DESIGN: NRT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: "We planned to include around 100 patients in the intervention group". No power calculation provided. Recruited 106 intervention and 91 control participants.
CLINICAL PROBLEM: first episode of Staphylococcus aureus bacteraemia
SETTING: 1 university hospital in Switzerland

Interventions

FORMAT, Interventions: structural ‐ rapid laboratory testing for meticillin resistance
Intervention Functions: environmental restructuring
DELIVERER: specialist physician (ID and Microbiology)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: % compliance with guideline recommended use of vancomycin

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL INFORMATION: the authors confirmed that this intervention did not include feedback to participants

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Odd versus even hospital number

Allocation concealment (selection bias)

Unclear risk

"Mode of allocation was concealed from the clinicians", but unclear how this was achieved.

Blinding (performance bias and detection bias)
All outcomes

High risk

Open study

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Primary outcome reported on all participants.

Selective reporting (reporting bias)

Unclear risk

Primary outcome reported on all participants. Authors did a secondary analysis excluding participants with penicillin allergy, but this was not prespecified.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Unclear risk

Clinicians received results verbally and electronically, so it is likely that they were aware of the intervention, which may have influenced their management of other participants.

Baseline characteristics similar?

Low risk

Table 1

Climo 1998

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: all patients in the hospital
SETTING: a 703‐bed tertiary‐care university hospital in the USA

Interventions

FORMAT: no reliable prescribing data. Restriction by expert approval

DELIVERER: specialist physician
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

MICROBIAL: cases of Clostridium difficile‐associated diarrhoea per quarter (ITS data). Prevalence of clindamycin‐resistant C difficile

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Done, infection control measures fully described and same in both phases.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after) with t‐test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Unclear risk

Not clear, no information about changes in sampling or testing protocol over study period

Free of other bias (ITS) ?

High risk

NOT DONE Microbial Risk of Bias Criteria: Planned intervention: NOT DONE; Case definition: DONE infection, diarrhoea, and toxin positive Other infection control measures: DONE barrier precautions, isolation of participants with C difficile‐associated diarrhoea, and personal IC procedures fully described and same in both phases.

Connor 2007

Methods

STUDY DESIGN: unintended consequences, cohort study

Risk of Bias: LOW

Participants

PROVIDERS: all physicians prescribing vancomycin
PARTICIPANTS: 120 patients with vancomycin prescription approved for only 72 hours
CLINICAL PROBLEM: interruption of vancomycin treatment
SETTING: 1 hospital in the USA

Interventions

FORMAT, Interventions: reminders (circumstantial and physical) stickers in medical records on day 3 warning of impending stop order; restrictive: stop order if approval not obtained
Intervention Functions: enablement, environmental restructuring, restriction
DELIVERER: AMT
COMPARISON: participants with and without sticker
DESIRED CHANGE: decrease excessive

Outcomes

UNINTENDED CONSEQUENCES: interruption of vancomycin treatment

Notes

ROBINS‐I RISK OF BIAS CRITERIA:

1. Confounding: Low, confounding unlikely

2. Selection of participants into the study: Low, selection into the study unrelated to intervention (sticker in notes) or outcome

3. Measurement classification of interventions: Low, intervention status well defined, recorded at the time of intervention and unaffected by knowledge of the outcome

4. Deviations from intended interventions: Low, the study was designed to detect intervention failure (no warning sticker)

5. Missing data: Low, outcome data and intervention status complete on all 120 participants

6. Measurement of outcome: Low, outcome measure objective and unaffected by intervention status

7. Selection of the reported result: Low, reported effect predefined

FINANCIAL SUPPORT: Funding: none. Competing Interests: EL received research support from Merck Pharmaceuticals and Ortho‐McNeil Pharmaceuticals. All other authors reported no conflicts of interest.

Cook 2011a

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving antibiotics
CLINICAL PROBLEM: use of all prophylactic and therapeutic antibiotics
SETTING: 1 university hospital in the USA

Interventions

FORMAT, Interventions: educational outreach by review and recommend change
Intervention Functions: education, enablement, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: total use of all antibiotics in DDD/1000 OBD

MICROBIAL: Clostridium difficile and MRSA infections/1000 OBD

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: PPC is a member of the speakers’ bureau of Pfizer, Astellas, and Merck. PPC has received research funding from GlaxoSmithKline, Merck, Gilead, Pfizer, and Bristol‐Myers Squibb. All other authors have none to declare.

ADDITIONAL DATA: email response from authors with additional data about intervention

Microbial Risk of Bias HIGH: case definition low; planned intervention, other infection control high ‐ new policy for screening and isolation of MRSA introduced just before prescribing intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Routine data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Routine data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Routine data from pharmacy computer

Free of other bias (ITS) ?

Low risk

2 years' pre‐ and postintervention data

Cook 2011b

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving antibiotics
CLINICAL PROBLEM: patients receiving ciprofloxacin for treatment of any infection
SETTING: 1 university hospital in the USA

Interventions

FORMAT, Intervention 1 component: educational outreach by review and recommend change
Intervention 1 functions: education, enablement, persuasion

Intervention 2 component: restrictive by expert approval

Intervention 2 function: restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of ciprofloxacin in DDD/1000 OBD

MICROBIAL: infections with ARGNB ‐ % carbapenem resistant Pseudomonas aeruginosa

Notes

FINANCIAL SUPPORT: Funding: commercial, grant from Merck & Co., Inc. Competing Interests: PC is a member of the speakers’ bureau of Merck and Astellas. He has received research support from Merck, Gilead, and Pfizer.

ADDITIONAL DATA: email response from authors with additional data about intervention

Microbial Risk of Bias HIGH case definition low; planned intervention, other infection control high ‐ change in screening and isolation for MRSA just before prescribing intervention may have impacted on transmission of P aeruginosa

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Routine data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Routine data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Routine data from pharmacy computer

Free of other bias (ITS) ?

Low risk

5 years' pre‐ and 4 years' postintervention data

Cortoos 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all adult patients with community‐acquired pneumonia
CLINICAL PROBLEM: compliance with guideline for community‐acquired pneumonia
SETTING: 1 university hospital in the Netherlands

Interventions

FORMAT: Intervention 1: dissemination of educational materials

Intervention 1 function: education

Intervention 2: reminders ‐ physical, questionnaire about guideline compliance, distributed once
Intervention 2 functions: environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: % guideline compliance

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL INFORMATION: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

This and all other ROB criteria are for interventions 1 and 2 only. Intervention 3 and 4 could not be evaluated because they are too close together and also coincided with an influenza epidemic. Neither intervention 3 nor intervention 4 meets the EPOC minimum criteria for ITS. There are insufficient data to adjust for seasonal effects, and the target condition (pneumonia) has large seasonal variation.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

High risk

Data collection was different in the postintervention phase (see below).

Knowledge of the allocation adequately prevented(ITS)?

Unclear risk

Compliance to therapy was assessed with a "computerised algorithm". However, the criteria for guideline adherence presented in the supplementary materials (Table S2) would require chart review, unless the hospitals had very sophisticated electronic patient records, which is not stated. The fact that patients were excluded because of "incomplete files" suggests that chart review was required, so knowledge of the allocated interventions could not be adequately prevented.

Incomplete outcome data addressed (ITS) ?

Unclear risk

The 477 included participants had complete data for assessment of outcomes. 5 patients were excluded because of incomplete patient records.

Free of selected reporting (ITS) ?

Low risk

Free of other bias (ITS) ?

Unclear risk

Insufficient data to account for seasonal effects. Although information about guideline compliance is reported for 2 hospitals, the ITS in Figure 1 only has data from 1 hospital (UZL). The data for the second hospital (ZOL) are actually a UBA and have been excluded.

Danaher 2009

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 52 patients (14 intervention, 38 control)

CLINICAL PROBLEM: excessive prescribing of antibiotics

SETTING: 1 military teaching hospital in USA

Interventions

FORMAT, Interventions: educational outreach by review and recommend change
Intervention Functions: education, enablement, persuasion

FORMAT: Persuasive: educational outreach ‐ review and recommend change

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: "Since this was an explanatory study, no a priori estimates of effect size were available to perform power and sample size calculations." The goal was to have 180 participants in the trial.

Outcomes

PRESCRIBING: Choice: antibiotic use (DDDs and days of treatment)

CLINICAL: Balancing: clinical outcomes, mortality, and re‐admission

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer generated

Allocation concealment (selection bias)

Unclear risk

21 of 73 patients considered for enrolment were excluded, but it is not clear if this was pre‐ or postrandomisation. The number of participants in the study group was 14, versus 38 in the control group, with no justification for the unequal numbers.

Blinding (performance bias and detection bias)
All outcomes

Low risk

Primary outcome data from pharmacy computer

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all participants.

Selective reporting (reporting bias)

Low risk

Outcomes reported on all participants.

Other bias

High risk

Aim was to enrol 180 patients, but only 72 patients were identified, and 21 of them were excluded.

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

High risk

Education intervention with study and control in same hospital

Baseline characteristics similar?

Low risk

Dancer 2013

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: requiring antibiotic prophylaxis or treatment
SETTING: 1 district general hospital in the UK

Interventions

FORMAT: Interventions: restrictive
Intervention Functions: restriction by removal from all wards except for ED and ICU and by therapeutic substitution ("empirical prescription of ceftriaxone and ciprofloxacin for systemic sepsis and surgical prophylaxis was changed to amoxicillin, gentamicin and metronidazole")
DELIVERER: AMT
COMPARISON: multifaceted intervention introduced 7 months before restriction and remaining in place throughout restrictive period. Components: audit and feedback; educational outreach by review and recommend change; educational meetings and reminders on microbiology reports. There is only 2 months' data before the multifaceted intervention, so it is not possible to estimate its effect.
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of cephalosporins and ciprofloxacin in DDD/1000 OBD

MICROBIAL: CDI, MRSA, and resistant gram‐negative bacteria

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: SD received financial support for attending conferences by Janssen‐Cilag, Pfizer, and Novartis

ADDITIONAL DATA: authors provided additional details about the intervention, including information about regular feedback to participants that was not in the original paper

Microbial Risk of Bias LOW case definition Low, planned intervention Low, other infection control practices Low

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

9 months' data pre‐restriction includes an additional persuasive intervention 7 months' pre‐restriction; effect cannot be assessed because of insufficient pre‐intervention data.

Analysed appropriately (ITS) ?

Low risk

Analysed by correlation and time‐lag modelling, but re‐analysed as segmented regression analysis.

Shape of effect pre‐specified (ITS) ?

Low risk

Unlikely to affect data collection (ITS) ?

Low risk

Routine data from microbiology and pharmacy computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine data from microbiology and pharmacy computers

Incomplete outcome data addressed (ITS) ?

Low risk

Routine data from microbiology and pharmacy computers

Free of selected reporting (ITS) ?

Low risk

Routine data from microbiology and pharmacy computers

Free of other bias (ITS) ?

High risk

Only 9 months' pre‐intervention data

de Champs 1994

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: physicians on a paediatric ICU
PARTICIPANTS: all patients on paediatric ICU
CLINICAL PROBLEM: neonates requiring intensive care including empirical antibiotic treatment
SETTING: paediatric ICU in a university hospital in France

Interventions

FORMAT: No valid prescribing data. Restrictive: change in antibiotic policy from gentamicin to amikacin

DELIVERER: specialist physician
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

MICROBIAL: monthly incidence of infection with multiresistant Enterobacter cloacae

Notes

FINANCIAL SUPPORT: Funding: grant from D.R.E.D. (Direction de la Recherche et des Etudes Doctorales). Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Only 7 months' pre‐intervention data, so secular/seasonal changes possible. Very complex case definition with no information about how this was applied reliably across the pre‐ and postintervention periods.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after) with t‐test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Unclear risk

Case definition included clinical interpretation.

Knowledge of the allocation adequately prevented(ITS)?

Unclear risk

NOT CLEAR because of case definition

Incomplete outcome data addressed (ITS) ?

Unclear risk

Availability of all data required for the case definition not documented.

Free of selected reporting (ITS) ?

Unclear risk

Not clear, no information about changes in sampling or testing protocol over study period.

Free of other bias (ITS) ?

High risk

Microbial outcome risk of bias: Unplanned intervention: implementation of change in response to emergence of gentamicin‐resistant E cloacae; Case definition:infection from clinical or screening isolates combined with 7 clinical criteria and 5 additional laboratory criteria assessed by a resident paediatrician and a consultant microbiologist and verified by a consultant paediatrician. Reliability of this outcome measure not clear. Other infection control measures: well documented, no changes during the study period

Dean 2001

Methods

STUDY DESIGN: CBA

Risk of Bias: HIGH

Participants

PROVIDERS: all inpatient and outpatient services in the state of Utah
PARTICIPANTS: 22,985 Medicare beneficiaries aged 65 or older with 28,661 episodes of community‐acquired pneumonia, of which 7719 were hospitalised
CLINICAL PROBLEM: community‐acquired pneumonia
SETTING: 23 hospitals (and 60 outpatient clinics), all in Utah, USA

Interventions

FORMAT: no valid prescribing data. Reminder; educational outreach ‐ academic detailing; and educational meetings or dissemination of educational material

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

CLINICAL: Intended: 30‐day mortality and length of stay

Notes

FINANCIAL SUPPORT: supported by HealthInsight and Intermountain Healthcare. The analyses upon which this publication is based were performed under contract number 500 –96‐P604, entitled “Utilization and Quality Control Peer Review Organization for the State of Utah”, sponsored by the Health Care Financing Administration (HCFA), Department of Health and Human Services. This article is a direct result of the Health Care Quality Improvement Program initiated by HCFA, which has encouraged identification of quality improvement projects derived from analysis of patterns of care, and therefore required no special funding on the part of the contractor. Conflict of interest: no information

ADDITIONAL DATA: authors provided additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

CBA

Allocation concealment (selection bias)

High risk

CBA

Blinding (performance bias and detection bias)
All outcomes

High risk

CBA

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Objective outcome measure collected on all participants.

Selective reporting (reporting bias)

Low risk

Objective outcome measure collected on all participants.

Other bias

Low risk

No other apparent biases found.

Baseline Outcomes similar?

Low risk

Table 1

Free of contamination?

Unclear risk

NOT CLEAR, some hospitals had both intervention and control physicians. Intermountain Healthcare provides 50% of regional health care delivery in Utah. In rural IHC hospitals, 90% of pneumonia admissions were cared for by IHC‐affiliated physicians, whereas in urban IHC hospitals only 44% of pneumonia admissions were cared for by IHC‐affiliated physicians. Non‐affiliated physicians caring for patients at IHC hospitals may have been influenced by guideline implementation at these hospitals.

Baseline characteristics similar?

Low risk

Table 1

Dean 2006

Methods

STUDY DESIGN: CBA

Risk of bias: HIGH

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: a total of 17,728 patients aged 66 years or older

CLINICAL PROBLEM: admitted with community‐acquired pneumonia

SETTING: 35 hospitals in Utah, USA (16 from Intermountain Healthcare and 19 from other systems)

Interventions

FORMAT: no valid prescribing data. Reminder; educational outreach by academic detailing; and educational meetings with dissemination of educational materials

DELIVERER: specialist physician

COMPARISON: usual care

DESIRED CHANGE: increase effective

Outcomes

CLINICAL: Intended: 30‐day mortality, LOS, and 30‐day re‐admission

Notes

FINANCIAL SUPPORT: this study was funded by the Deseret Foundation and HealthInsight, Salt Lake City. The authors have no relevant conflicts of interest to report.

ADDITIONAL DATA: authors provided additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

CBA

Allocation concealment (selection bias)

High risk

CBA

Blinding (performance bias and detection bias)
All outcomes

High risk

CBA

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Electronic record linkage used.

Selective reporting (reporting bias)

Low risk

30‐day mortality was primary outcome.

Other bias

Low risk

Objective primary outcome measure

Baseline Outcomes similar?

Low risk

Table 3

Free of contamination?

Low risk

NOT CLEAR, some hospitals had both intervention and control physicians. The 100,000 annual inpatient admissions of Intermountain Healthcare represent almost one‐half of Utah hospital admissions. Intermountain Healthcare has an employed physician group and several non‐Medicare health maintenance organisation insurance plans, but many non‐employed physicians and non‐health maintenance organisation patients also utilise its facilities. Non‐affiliated physicians caring for patients at Intermountain Healthcare hospitals may have been influenced by guideline implementation at these hospitals.

Baseline characteristics similar?

Unclear risk

Not stated

Dempsey 1995

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients with clinical problem
CLINICAL PROBLEM: patients with nursing home‐acquired pneumonia
SETTING: 1 hospital in the USA

Interventions

FORMAT: no valid prescribing data. Audit and feedback; reminders; and educational meetings with dissemination of educational materials

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

CLINICAL: Intended: length of stay

FINANCIAL: charge per case of nursing home‐acquired pneumonia

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

< 1 year data pre‐ and postintervention, so seasonal trends cannot be excluded.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Patient administration system

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Patient administration system

Incomplete outcome data addressed (ITS) ?

Unclear risk

No explicit statement about complete follow‐up

Free of selected reporting (ITS) ?

Low risk

Free of other bias (ITS) ?

Low risk

Ding 2013

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians
PARTICIPANTS: 78 patients with acute exacerbations of idiopathic pulmonary fibrosis (39 intervention, 39 control)
CLINICAL PROBLEM: management of acute exacerbations
SETTING: 1 hospital in China

Interventions

FORMAT, Interventions: structural ‐ introduction of procalcitonin testing with decision support algorithm
Intervention Functions: enablement, environmental restructuring

DELIVERER: respiratory physicians
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Exposure: % participants treated and duration of antibiotic treatment

CLINICAL: Balancing: mortality, length of stay, duration of mechanical ventilation

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response to request from authors

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer‐generated numbers

Allocation concealment (selection bias)

Low risk

Computer‐generated numbers

Blinding (performance bias and detection bias)
All outcomes

High risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all participants.

Selective reporting (reporting bias)

Low risk

Outcomes reported on all participants.

Other bias

High risk

No power calculation

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

Procalcitonin results only available for intervention participants.

Baseline characteristics similar?

Low risk

Table 1

Dranitsaris 2001

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: physicians assigned to the 7 services
PARTICIPANTS: 309 patients with clinical problem (162 intervention, 147 control)
CLINICAL PROBLEM: adult patients with infections requiring IV cefotaxime
SETTING: 2 hospitals in Canada

Interventions

FORMAT: Interventions: educational outreach ‐ review and recommend change

Intervention Functions: enablement, persuasion

DELIVERER: pharmacist
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 330 participants, 165 in each group. Details in Appendix 3

Outcomes

PRESCRIBING: Choice: percentage of cefotaxime prescriptions that were consistent with guideline for both indication and dosage
SECONDARY: mean duration of therapy and cost per treatment course

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"Randomised on a one to one basis via a computer generated list"

Allocation concealment (selection bias)

Low risk

Randomisations carried out in central pharmacy and "telephone on a consecutive basis".

Blinding (performance bias and detection bias)
All outcomes

High risk

Not done, acknowledged as a limitation by authors on page 179.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

See Table 3; all participants included

Selective reporting (reporting bias)

Low risk

See Table 3; all participants included

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

High risk

Control participants were managed by the same physicians as intervention participants.

Baseline characteristics similar?

Low risk

Table 1

Dua 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians involved in vascular surgery
PARTICIPANTS: all patients undergoing vascular surgery
CLINICAL PROBLEM: surgical‐site infection following vascular surgery
SETTING: USA, multiple hospitals (stratified, random sample of 20% of all non‐federal inpatient hospital admissions throughout the USA)

Interventions

FORMAT: no valid prescribing data. Surgical Care Improvement Project core measures with financial incentives implemented in 2006
DELIVERER: specialist phsicians
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: no data

CLINICAL: inpatient surgical‐site infection

Notes

FINANCIAL SUPPORT: no funding. Competing Interests: none declared

ADDIDIONAL DATA: authors responded to request but had no additional relevant data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

No data about antibiotic prescribing

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Unclear risk

Outcome relied on ICD discharge coding to identify surgical‐site infection, may have been influenced by financial incentives to meet SCIP targets.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Electronic outcome data

Incomplete outcome data addressed (ITS) ?

High risk

Outcome data were restricted to inpatient coding, but most surgical‐site infections likely to present postdischarge.

Free of selected reporting (ITS) ?

Low risk

Electronic outcome data

Free of other bias (ITS) ?

Low risk

> 1 year of pre‐ and postintervention data

Dull 2008

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians, pharmacists, and nurses in surgical department
PARTICIPANTS: all patients undergoing elective surgery
CLINICAL PROBLEM: choice, timing, and duration of antibiotic prophylaxis
SETTING: 7 hospitals in the USA

Interventions

FORMAT: Interventions: audit and feedback; educational meetings with dissemination of educational materials; educational outreach by academic detailing; reminders (physical, posters, intranet, and faxes to physicians)
Intervention Functions: education, enablement, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: % participants with prophylaxis discontinued within 24 h of surgery

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Electronic outcome data

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Electronic outcome data

Incomplete outcome data addressed (ITS) ?

Low risk

Electronic outcome data

Free of selected reporting (ITS) ?

Low risk

Electronic outcome data

Free of other bias (ITS) ?

High risk

10 months' pre‐ and 12 months' postintervention data

Duvoisin 2014

Methods

STUDY DESIGN: unintended consequences, cohort study

Risk of Bias: LOW

Participants

PROVIDERS: all physicians
PARTICIPANTS: 222 infants with early‐onset neonatal sepsis
CLINICAL PROBLEM: early onset sepsis
SETTING: 1 hospital in Switzerland

Interventions

FORMAT, Interventions: restrictive by review and make change targeted at ordering of CBC and CRP tests
Intervention Functions: restriction
DELIVERER: specialist physician (ID)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive use of diagnostic tests

Outcomes

UNINTENDED CONSEQUENCES: time to first antibiotic dose and complications (requirement for catecholamine treatment and/or mechanical ventilation, meningitis, or death)

Notes

ROBINS‐I RISK OF BIAS CRITERIA:

1. Confounding: Low, confounding unlikely

2. Selection of participants into the study: Low, selection into the study unrelated to intervention or outcome

3. Measurement classification of interventions: Low, intervention status well defined, recorded at the time of intervention and unaffected by knowledge of the outcome

4. Deviations from intended interventions: Low, the study demonstrated large reduction in CBC (30%) and CRP (91%)

5. Missing data: Low, outcome data and intervention status complete on all 222 participants

6. Measurement of outcome: Low, outcome measure objective and unaffected by intervention status

7. Selection of the reported result: Low, reported outcomes predefined and measured from routine data

FINANCIAL SUPPORT: Funding: SICPA Foundation and the Société Académique Vaudoise. Competing Interests: none declared

ADDITIONAL DATA: email from authors with additional data about intervention

Elligsen 2012

Methods

STUDY DESIGN: CITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the critical care team
PARTICIPANTS: all critical care patients in the hospital

CLINICAL PROBLEM: decrease use of broad‐spectrum antibiotics in critical care patients

SETTING: 1 tertiary‐care centre in Ontario, Canada

Interventions

FORMAT: Interventions: educational outreach by review and recommend change
Intervention Functions: education, enablement, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of targeted broad‐spectrum antibiotics (days of therapy/1000 OBD)

Notes

FINANCIAL SUPPORT: Funding: Canadian Institutes of Health Research, Ontario Ministry of Health, and Long Term Care Academic Health Services Centre Innovation Award. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Done. October to August both pre‐ and postintervention

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Done, point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

High risk

No, the intervention was open to all participants and prescribers, difficult to conceal.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, Figures 1 and 2

Free of other bias (ITS) ?

Low risk

Done, no other apparent biases

Esposito 2011

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: all paediatric physicians
PARTICIPANTS: 319 children with pneumonia were enrolled and randomly assigned 1:1 to the treatment groups, but, as consent was withdrawn during the study in 9 cases (5 intervention and 4 control), the final analysis was based on 310 children (155 intervention and control)
CLINICAL PROBLEM: children hospitalised with community‐acquired pneumonia
SETTING: 1 university hospital in Italy

Interventions

FORMAT: Interventions: structural ‐ rapid testing for procalcitonin and decision support algorithm
Intervention Functions: enablement, environmental restructuring
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 76 participants in each group. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: % started on antibiotics and % children treated for > 10 days

CLINICAL: length of stay, duration of fever, antibiotic adverse effects

Notes

FINANCIAL SUPPORT: Funding: Italian Ministry of Health (Bando Giovani Ricercatori 2007). Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer generated

Allocation concealment (selection bias)

Low risk

Sealed envelopes

Blinding (performance bias and detection bias)
All outcomes

Low risk

PCT levels only reported on intervention participants.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

319 randomised, consent was withdrawn during the study in 9 cases (3% participants, 5 in the PCT group and 4 in the control group). Outcomes reported on all participants (Tables 2‐3). All 310 children came to the planned follow‐up visits.

Selective reporting (reporting bias)

Low risk

Outcomes reported on all 310 participants (Tables 2‐3). All 310 children came to the planned follow‐up visits.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

PCT levels only reported on intervention participants.

Baseline characteristics similar?

Low risk

Table 1

Everitt 1990

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: physicians in Obstetrics & Gynaecology
PARTICIPANTS: patients (women) with clinical problem
CLINICAL PROBLEM: Caesarean section
SETTING: 1 university hospital in the USA

Interventions

FORMAT: Interventions: educational meetings with dissemination of guidelines; reminders (circumstantial, on the structured order form for intravenous antibiotics, which was triggered for every order for IV antibiotics); restriction by expert approval and by removal
Intervention Functions: education, enablement, environmental restructuring, restriction

DELIVERER: department physician

COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: relative use of cefazolin or cefoxitin in Caesarean sections that received < 5 g of either drug perioperatively
FINANCIAL: estimated financial savings

Notes

FINANCIAL SUPPORT: Funding: Beth Israel Hospital, Boston, Massachusetts and Fund for Cooperative Innovation of Blue Cross of Massachusetts and the Massachusetts Hospital Association. Competing Interests: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Only 9 months pre‐intervention data, so secular/seasonal changes possible.

Analysed appropriately (ITS) ?

Low risk

Done in original paper, segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

Antibiotic costs adjusted to 1986 prices over the whole study period.

Farinas 2012

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 1185 patients receiving at least 3 days of IV antibiotics (571 intervention, 614 control)
CLINICAL PROBLEM: adherence to recommendations for change of therapy
SETTING: 1 university hospital in Spain

Interventions

FORMAT: no valid prescribing outcome data. Educational outreach (review and recommend change)
DELIVERER: specialist (ID) physicians
COMPARISON: usual care
DESIRED CHANGE: increase appropriate antibiotic treatment

SAMPLE SIZE: 571 intervention, 614 control

POWER CALCULATION: no power calculation. No adjustment for intracluster correlation

Outcomes

PRESCRIBING: Choice but no valid outcome data (% adherence with recommendations, but no data about antibiotic use in terms of choice, route, or duration of treatment)

CLINICAL: Balancing: length of stay and % treatment failure

Notes

FINANCIAL SUPPORT: Funding: Fondo de Investigaciones Sanitarias (FIS PI06/90094), and Instituto de Formación e Investigación Marqués de Valdecilla (IFIMAV) (API 06/03). Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer

Allocation concealment (selection bias)

High risk

Randomisation stratified by clinical units, not blinded. Participants were randomised by groups (stratified randomisation by clinical units) to intervention or non‐intervention using the EPIDAT 3.1 programme (Dirección Xeral de Saúde Pública, Xunta de Galicia & Organización Panamericana de la Salud. Santiago de Compostela, Coruña, Spain, 2003).

Blinding (performance bias and detection bias)
All outcomes

High risk

Randomisation not blinded

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all participants.

Selective reporting (reporting bias)

Unclear risk

The primary outcome (clinical failure) was complex and not entirely objective.

Other bias

High risk

Unit of analysis error, no adjustment for intracluster correlation

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

19 participants in the control group were excluded because they had ID consultation.

Baseline characteristics similar?

Low risk

Table 1

Fine 2003

Methods

STUDY DESIGN: cluster RCT, service level

Risk of bias: HIGH

Participants

PROVIDERS: all physicians in hospitals

PARTICIPANTS: 608 patients with community‐acquired pneumonia (263 intervention, 325 control), 7 clusters (sites)

CLINICAL PROBLEM: duration of IV antibiotic therapy and LOS

SETTING: 7 nonprofit hospitals in Pittsburgh, Pennsylvania, USA

Interventions

FORMAT: Interventions: dissemination of educational materials, educational outreach by review and recommend change; reminders (circumstantial, physical, detail sheets in physician notes for patients with community‐acquired pneumonia and verbal, telephone calls); restrictive; structural
Intervention Functions: education, enablement, environmental restructuring, persuasion, restriction

DELIVERER: AMT 

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 600 participants in total. Details in Appendix 3

Outcomes

PRESCRIBING: Choice: duration of IV antibiotic therapy

CLINICAL: intended clinical outcomes, mortality, re‐admission

Notes

FINANCIAL SUPPORT: Funding: Agency for Healthcare Research and Quality and the National Institute of Allergy and Infectious Diseases (HS08282), Robert Wood Johnson Foundation. Competing Interests: no statement

ADDITIONAL DATA: authors provided additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

Physician groups were randomly assigned after stratification for practice type, group size, and patient volume, but details not clear.

Allocation concealment (selection bias)

High risk

Blinding (performance bias and detection bias)
All outcomes

Low risk

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Selective reporting (reporting bias)

Low risk

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data about LOS prior to intervention

Free of contamination?

Low risk

Baseline characteristics similar?

Low risk

Fitzpatrick 2008

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital

CLINICAL PROBLEM: prescribing of cefuroxime and quinolones

SETTING: 1 hospital in the UK

Interventions

FORMAT: Interventions: dissemination of guideline
Intervention Functions: education

DELIVERER: pharmacist

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of cefuroxime and ciprofloxacin (DDD/Finished Consultant Episode ratio)

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

No mention of any other changes, although little information given.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Done. Intervention point was clear.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done. Outcomes are objective.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done. Figures 1 and 2

Free of other bias (ITS) ?

Low risk

Done. No other bias apparent.

Fowler 2007

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: physicians in the hospital
PARTICIPANTS: patients 80 years and older

CLINICAL PROBLEM: Clostridium difficile infection in the elderly

SETTING: 3 acute medical wards for the elderly in 1 university hospital in the UK

Interventions

FORMAT: Interventions: audit and feedback, dissemination of guideline; reminders (physical, laminated pocket version of guideline)

Intervention Functions: education, enablement, environmental restructuring

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

Outcomes

PRESCRIBING: Choice: monthly use of target antibiotics

MICROBIAL: monthly count of cases of CDI

Notes

FINANCIAL SUPPORT: no funding. Competing Interests: none declared

ADDITIONAL DATA: email response from authors but no additional data

Microbial Risk of Bias LOW: Planned intervention: Low Case definition: Low, National definition. Other infection control measures: Low

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Ongoing audit and feedback

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Done. Point of analysis is point of the intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

High risk

No, not possible

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems so unlikely to be incomplete.

Free of selected reporting (ITS) ?

Low risk

Done, Figures 3 and 4

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Franz 2004

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: physicians in neonatal units
PARTICIPANTS: 1291 neonates < 72 hours of age were randomised (656 intervention, 635 control)

CLINICAL PROBLEM: suspected bacterial infection

SETTING: 8 centres in 5 countries (Australia, Austria, Belgium, Germany, Sweden)

Interventions

FORMAT, Interventions: dissemination of guideline; structural, introduction of testing for C‐reactive protein and interleukin‐8 with decision support algorithm
Intervention Functions: education, enablement, environmental restructuring

DELIVERER: department physician

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, total of 1150 participants. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: number of newborn infants who received antibiotic therapy

Notes

FINANCIAL SUPPORT: Funding: grant P.575 from the Center for Applied Clinical Studies of the University of Ulm and Swedish Research Council. DPC (Los Angeles, CA) provided the Immulite automated analysers and the kits for determination of IL‐8 and sponsored the initial meeting of the investigators. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"Randomly assigned to 1 or 2 diagnostic algorithms using sealed opaque envelopes"

Allocation concealment (selection bias)

Low risk

Blinding (performance bias and detection bias)
All outcomes

Low risk

Done, IL‐8 results were only provided to physicians in the intervention group.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Selective reporting (reporting bias)

Low risk

Other bias

Low risk

Baseline Outcomes similar?

High risk

No data

Free of contamination?

Low risk

Baseline characteristics similar?

Low risk

Fraser 1997

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: medical, surgery, intensive care, haematology, and oncology
PARTICIPANTS: patients with the clinical problem
CLINICAL PROBLEM: adult inpatients receiving 1 or more of 10 designated parenteral antibiotics for 3 or more consecutive days
SETTING: single teaching hospital in the USA

Interventions

FORMAT: Interventions: educational outreach by review and recommend change; reminders (circumstantial, physical, written suggestions placed in the notes of participants receiving IV antibiotics)
Intervention Functions: enablement, environmental restructuring, persuasion
DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

SAMPLE SIZE CALCULATION: no information

Outcomes

PRESCRIBING: Choice: days receiving IV antibiotic therapy per participant, DDDs of IV antibiotics per participant. Antibiotic charges (USD) per participant

CLINICAL: Balancing: clinical response at 3 days after completion of antibiotics; retreatment with antibiotics within 7 days; inpatient mortality; re‐admission within 30 days of discharge

FINANCIAL: savings on drug costs in USD

Notes

FINANCIAL SUPPORT: Funding: commercial (Bayer Pharmaceuticals) and the Maine Medical Center Research Committee. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"Patients randomised ... using an unblocked computer generated random number table"

Allocation concealment (selection bias)

High risk

Not possible; "The patient population was assigned to 1 of 4 medical service groups based on where they were treated at randomizations"

Blinding (performance bias and detection bias)
All outcomes

High risk

Not possible

Incomplete outcome data (attrition bias)
All outcomes

Low risk

For primary outcomes, not secondary

Selective reporting (reporting bias)

Low risk

Based on microbial response and other clinical parameters

Other bias

Low risk

No problems noted.

Baseline Outcomes similar?

Unclear risk

No information about baseline outcomes pretrial in the allocated groups.

Free of contamination?

High risk

Doctors likely to have cared for participants in all groups.

Baseline characteristics similar?

Low risk

Table 1

Fridkin 2002

Methods

STUDY DESIGN: CBA

Risk of Bias: HIGH

Participants

PROVIDERS: a total of 50 ICUs located in 20 hospitals

PARTICIPANTS: patients in the ICU

CLINICAL PROBLEM: vancomycin use, prevalence of VRE

SETTING: hospitals in the USA participating in the ICU surveillance component of National Nosocomial Infection Surveillance

Interventions

FORMAT: 5 interventions were used by 3 to 19 hospitals (some hospitals used more than 1). 3 interventions were hospital‐wide and 2 were unit‐specific.

Hospital‐wide interventions (22 ICUs)

Intervention 1: educational meetings with dissemination of educational materials, 9 ICUs. Intervention function: education.

Intervention 2: audit and feedback, 19 ICUs. Intervention function: enablement.

Intervention 3: restriction, 3 ICUs. Intervention function: restriction.

Unit‐specific interventions (11 ICUs)

Intervention 4: educational meetings with dissemination of educational materials. Intervention function: education.

Intervention 5: restriction, 3 ICUs. Intervention function: restriction.

DELIVERER: AMT

COMPARISON: national benchmark data

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: DDDs of vancomycin

MICROBIAL: percentages of VRE and MRSA

Notes

FINANCIAL SUPPORT: Funding: CDC Emerging Infections Program. Competing Interests: no information

ADDITIONAL DATA: email response from authors but no additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

CBA ‐ not randomised

Allocation concealment (selection bias)

High risk

CBA ‐ not randomised

Blinding (performance bias and detection bias)
All outcomes

High risk

CBA, allocation not blinded

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Not clear: “Susceptibility reports from isolates obtained as part of infection‐control surveillance were excluded.” Criteria for exclusion of isolates are not described and may not have been consistent across all hospitals.

Selective reporting (reporting bias)

Low risk

Not clear: “Susceptibility reports from isolates obtained as part of infection‐control surveillance were excluded.” Criteria for exclusion of isolates are not described and could have led to reporting bias.

Other bias

Unclear risk

NOT CLEAR Microbial Risk of Bias Criteria: Case definition: percentage VRE or percentage MRSA in clinical isolates; Planned intervention: DONE; Other infection control isolation: NOT CLEAR; IC practices: NOT CLEAR Data were collected about infection control changes in response to feedback of data, but the paper does not report any results.

Baseline Outcomes similar?

Unclear risk

Not stated

Free of contamination?

Low risk

Interventions were at different hospitals from control sites.

Baseline characteristics similar?

Unclear risk

Not stated

Friedberg 2009

Methods

STUDY DESIGN: unintended consequences, cohort study

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in EDs
PARTICIPANTS: 13,042 adult patients
CLINICAL PROBLEM: presenting with respiratory symptoms
SETTING: 385 hospitals in the USA

Interventions

FORMAT, Interventions: audit and feedback, public reporting of antibiotic timing measure as 1 of 10 national quality indicators; financial, institution incentive
Intervention Functions: enablement, incentive
DELIVERER: Hospital Quality Alliance
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

UNINTENDED CONSEQUENCES: rates of pneumonia diagnosis, antibiotic use, and waiting times to see a physician

Notes

ROBINS‐I RISK OF BIAS CRITERIA:

1. Confounding: Unclear, analysis says it was adjusted for confounding of the effect of intervention but insufficient detail

2. Selection of participants into the study: Low, selection into the study unrelated to intervention or outcome

3. Measurement classification of interventions: Low, intervention status well defined, recorded at the time of intervention and unaffected by knowledge of the outcome or risk of the outcome

4. Deviations from intended interventions: Low, no switches to other interventions or evidence of intervention failure

5. Missing data: Unclear, outcome data reported as % with no numerator/denominator (Table 2)

6. Measurement of outcome: High, the effect estimate is based on regression analysis of annual data for 3 years pre‐ and 2 years postintervention (i.e. only 2 postintervention time points). The authors say that "based on the NHAMCS sample, there were an estimated 40 million (95% confidence interval, 39 to 42 million) ED visits to hospitals by adults with respiratory symptoms between 2001 and 2005." In Table 1, around 10% of these patients had a diagnosis of CAP, so they were not short of data! They should surely have split their data into more time points.

7. Selection of the reported result: Low, single analysis of the intervention‐outcome relationship

FINANCIAL SUPPORT:Funding: Primary Care Teaching and Education Fund (internal), Health Resources and Services Administration, and Agency for Healthcare Research and Quality. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Fukuda 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all adult inpatients receiving target antibiotics for 14 days or more
CLINICAL PROBLEM: de‐escalation of treatment in patients who received carbapenems, cephalosporins, or quinolones for at least 14 days
SETTING: 1 community hospital in Japan

Interventions

FORMAT: Interventions: educational outreach by review and recommend change
Intervention Functions: enablement, persuasion

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive and decrease cost

Outcomes

PRESCRIBING: Choice: cost of target antibiotics (USD/1000 OBD)

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Outcome data from pharmacy computer

Free of other bias (ITS) ?

High risk

Only 6 month pre‐intervention data, so cannot adjust for seasonal effects.

Gerding 1985

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all prescribers in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: requiring aminoglycoside treatment
SETTING: 1 Veterans Administration hospital in the USA. UBA data about resistance from 14 other similar hospitals

Interventions

FORMAT: no valid prescribing data. Restrictive.

DELIVERER: specialist physician

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

MICROBIAL: resistance to gentamicin and aminoglycoside use

Notes

FINANCIAL SUPPORT: Funding: commercial, Bristol Laboratories and the Veterans Administration. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: MEDIUM, case definition Low, planned intervention Low, other infection control Unclear, no information

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

Only 4 months' pre‐intervention data, so secular/seasonal changes possible. No information about infection control measures.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analyses was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Routine data

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine data

Incomplete outcome data addressed (ITS) ?

Low risk

Routine data

Free of selected reporting (ITS) ?

Low risk

Routine data

Free of other bias (ITS) ?

Unclear risk

NOT CLEARMicrobial Outcome Risk of Bias: Planned intervention: DONE Implementation in response to emergence of gentamicin resistance over the previous 5 years; Case definition: DONE Infection from clinical isolates; Other infection control measures: NOT CLEAR, no information provided.

Goldstein 2009

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians
PARTICIPANTS: all adult patients in the hospital
CLINICAL PROBLEM: patients requiring IV antibiotics
SETTING: 1 university hospital in the USA

Interventions

FORMAT: Interventions: dissemination of formulary

Intervention Function: education

After 9 months there was an additional restrictive intervention (autosubstitution of ampicillin sulbactam by ertapenem), but this was not targeted at imipenem use, and no data are provided about prescribing or microbial outcomes for ampicillin sulbactam.
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: imipenem use in DDD

MICROBIAL: % susceptibility to imipenem in clinical isolates of Pseudomonas aeruginosa

Notes

FINANCIAL SUPPORT: Funding: commercial Merck (manufacturers of ertapenem). Competing Interests: Ellie JC Goldstein is on the advisory boards of Merck, is in the speakers' bureau of Merck, and received research support from Merck; Shuang Lu is employed by Merck Research Laboratories and may own stock or stock options. Anne R Meibohm was formerly employed by Merck Research Laboratories and may own stock or stock options.

ADDITIONAL DATA: email response from authors to request for additional data

Microbial Risk of Bias LOW: case definition low risk, planned intervention low risk, other infection control measures low risk, no change

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of other bias (ITS) ?

High risk

Only 6 months' pre‐intervention data for intervention 1 and 9 months' for intervention 2

Grohs 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians
PARTICIPANTS: all adult patients
CLINICAL PROBLEM: requiring treatment with IV 3rd‐generation cephalosporin
SETTING: 1 university hospital in France

Interventions

FORMAT: Intervention: distribution of antibiotic policy

Intervention Function: education
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: ceftriaxone use in DDD/1000 OBD

MICROBIAL: number of participants carrying high level AmpC beta‐lactamase

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: HIGH case definition low, planned intervention low, other infection control measures unclear (no data)

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from microbiology and pharmacy computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from microbiology and pharmacy computers

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from microbiology and pharmacy computers

Free of selected reporting (ITS) ?

Low risk

Outcome data from microbiology and pharmacy computers

Free of other bias (ITS) ?

High risk

Short time series, annual data with only 5 pre‐ and 7 postintervention data points

Gulmezoglu 2007

Methods

STUDY DESIGN: cluster RCT, hospital level

Risk of Bias: HIGH

Participants

PROVIDERS: obstetric teams
PARTICIPANTS: 1000 consecutively delivered women in obstetric units, 40 clusters (hospitals)
CLINICAL PROBLEM: women undergoing Caesarean section
SETTING: 22 hospitals in Mexico City and 18 in Thailand

Interventions

FORMAT: Interventions: educational meetings and dissemination of brochures; reminders (physical, posters and brochures)
Intervention Functions: education, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: increase effective

POWER CALCULATION: yes, 40 hospitals. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: % women receiving antibiotic prophylaxis for Caesarean section

Notes

FINANCIAL SUPPORT: Funding: UNDP/UNFPA/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP). Competing Interests: 4 authors were editors of The WHO Reproductive Health Library since its inception in 1997 to date of publication.

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Random number generator used (detailed in other article).

Allocation concealment (selection bias)

Low risk

Allocation by hospital

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

No mention of this

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Field workers collected from hospital data and were able to consult mothers for any missing data.

Selective reporting (reporting bias)

Low risk

Field workers collected from hospital data and were able to consult mothers for any missing data.

Other bias

High risk

End of study in Thai control hospital was conducted at a later stage due to other healthcare‐related activities going on.

Baseline Outcomes similar?

Unclear risk

Appear to be different but unclear

Free of contamination?

Low risk

Allocation by hospital

Baseline characteristics similar?

Unclear risk

No data

Gums 1999

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: a total of 272 patients
CLINICAL PROBLEM: patients receiving inappropriate antibiotic therapy judged on culture results, risk of toxicity or drug interaction, drug cost, and duration of treatment
SETTING: single 275‐bed community hospital in the USA

Interventions

FORMAT: Interventions: educational outreach by review and recommend change; reminders (circumstantial and physical, placed in notes of patients who were receiving antibiotics)
Intervention Functions: enablement, environmental restructuring, persuasion

DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: no justification provided for the sample size

Outcomes

PRESCRIBING: Choice: cost of antibiotic therapy

CLINICAL: Balancing: length of stay

FINANCIAL: charges for antibiotics, laboratory and radiology services, total patient charges. Implementation cost based on days per week required for Pharmacy and Infectious Diseases staff.

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL INFORMATION: no response from authors

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

Method of sequence generation not clear; "eligible patients were blindly randomised to the intervention or control group"

Allocation concealment (selection bias)

High risk

Not possible to conceal allocation because all intervention participants had a consultation, whereas no control participants did.

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

Unclear, despite objective primary outcome measure (LOS), it is not clearly stated that record linkage was without knowledge of allocation.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

No problems found, data were analysed from 93% of randomised participants.

Selective reporting (reporting bias)

Low risk

No problems found.

Other bias

Low risk

No other apparent biases found.

Baseline Outcomes similar?

Low risk

Done for primary outcome

Free of contamination?

Low risk

Participants were randomised to receive a consultation from an ID specialist (intervention) or no consultation (control), so no contamination likely.

Baseline characteristics similar?

Low risk

Done, Table 1 of the original paper

Gupta 1989

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: patients with clinical problem
CLINICAL PROBLEM: patients receiving cefazolin
SETTING: 1 university hospital in Canada

Interventions

FORMAT: Interventions: dissemination of memo; reminders (physical, newsletter); restrictive by review and make change
Intervention Functions: education, environmental restructuring, persuasion, restriction

DELIVERER: pharmacist

COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: % of cefazolin doses prescribed at < 8‐hour intervals

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Only 3 months' pre‐intervention data, so secular/seasonal changes possible.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper, Х2 test on mean before‐after.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Hadi 2008

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: residents in internal medicine department
PARTICIPANTS: patients with clinical problem

CLINICAL PROBLEM: antibiotics use in patients with a fever

SETTING: 5 wards in internal medicine department of teaching hospital in Indonesia

Interventions

FORMAT: Interventions: educational meetings with dissemination of guidelines; educational outreach by academic detailing; reminders (physical, pocket book version of guideline)
Intervention Functions: education, environmental restructuring, persuasion
DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

Outcomes

PRESCRIBING: Exposure: % patients treated and total antibiotic consumption (DDD/100 patient days)

Notes

FINANCIAL SUPPORT: Funding: Royal Netherlands Academy of Arts and Sciences, Scientific Programme Indonesia‐Netherlands (SPIN). Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

No, seasonal variation

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Done, point of analysis is point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data was collected by trained data collectors.

Knowledge of the allocation adequately prevented(ITS)?

High risk

No, blinding was not possible.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, states they assured completeness of data by collecting while patients were still in the department.

Free of selected reporting (ITS) ?

Low risk

Done, Figure 2

Free of other bias (ITS) ?

Low risk

Done, all biases addressed.

Halm 2004

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospitals
PARTICIPANTS: all patients with clinical problem

CLINICAL PROBLEM: adults with community‐acquired pneumonia

SETTING: 4 university hospitals, New York, USA

Interventions

FORMAT: Interventions: educational meetings with dissemination of guidelines; reminders (circumstantial and physical, on computer order system for antibiotics and pocket version of guideline)
Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: percentage of patients treated with guideline‐recommended antibiotics

Notes

FINANCIAL SUPPORT: Funding: Mount Sinai‐New York University Health System, the North Shore‐Long Island Jewish Health System, and the Robert Wood Johnson Foundation Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

NOT DONE, subjective outcome measure, not blinded

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after) with χ2 test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data collection same pre‐ and postintervention.

Knowledge of the allocation adequately prevented(ITS)?

High risk

NOT DONE, subjective outcome measure, not blinded

Incomplete outcome data addressed (ITS) ?

Unclear risk

Not stated whether outcome data collected on all participants.

Free of selected reporting (ITS) ?

Unclear risk

Not stated whether outcome data collected on all participants.

Free of other bias (ITS) ?

High risk

NOT DONE, the only reliable data for analysis are about compliance with the antibiotic policy, which was 80% at baseline. Serious risk of ceiling effect.

Hess 1990

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: receiving cefazolin therapy
SETTING: a 719‐bed tertiary‐care medical centre in the USA

Interventions

FORMAT: Interventions: dissemination of guideline; educational outreach by review and recommend change
Intervention Functions: education, enablement, persuasion
DELIVERER: pharmacist

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: cefazolin expenditure per patient day

FINANCIAL: savings in drug costs

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

12 months' data pre‐ and postintervention

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper, no statistical analysis, and only comparison was between mean (uncontrolled) before and after.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Unclear risk

On page 588 the authors state that "a proportion of these savings can be attributed to a decrease in acquisition cost", but they do not say how much.

Himmelberg 1991

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: physicians in the hospital
PARTICIPANTS: patients in the hospital
CLINICAL PROBLEM: patients receiving restricted antibiotics
SETTING: a tertiary‐care teaching hospital in the USA

Interventions

FORMAT: Interventions: restrictive, removal of restriction

Intervention Functions: restriction

DELIVERER: specialist physician
COMPARISON: 6 months in the restriction period were compared with 6 months after restriction was lifted.
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: number of courses and cost of restricted drugs

FINANCIAL: cost of drugs

Notes

FINANCIAL SUPPORT:Funding: commercial, Pfizer Roerig and the Upjohn companies. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Data collected in same months in 2 consecutive years.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after) with t‐test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Hitti 2012

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the ED
PARTICIPANTS: all patients with sepsis in the ED
CLINICAL PROBLEM: sepsis
SETTING: 1 hospital in Beirut, Lebanon

Interventions

FORMAT, Interventions: structural
Intervention Functions: environmental restructuring, antibiotics required for sepsis treatment were stored in an Automated Dispensing Cabinet in the ED instead of having to be ordered from pharmacy
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: time to first antibiotic dose in minutes measured both from arrival in the ED and from ordering the antibiotic

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention is point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Retrospective data collection using the same methods throughout

Knowledge of the allocation adequately prevented(ITS)?

High risk

Data were collected from case records, and allocation was not concealed.

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data reported on all 110 included participants.

Free of selected reporting (ITS) ?

Low risk

Exclusion rates similar pre‐ (13/69) and post‐ (11/65) intervention.

Free of other bias (ITS) ?

High risk

Data only collected for 7 months pre‐ and 8 months postintervention, so secular trends possible.

Hochreiter 2009

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in ICU
PARTICIPANTS: all patients with the clinical problem
CLINICAL PROBLEM: duration of antibiotic therapy in 110 patients with suspected bacterial infections (57 intervention, 53 control)
SETTING: surgical intensive care ward in 1 hospital in Germany

Interventions

FORMAT, Interventions: reminders (circumstantial and physical, procalcitonin‐based decision support algorithm); structural (introduction of procalcitonin testing)
Intervention Functions: enablement, environmental restructuring, persuasion

DELIVERER: department (ICU) physician
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: no information provided

Outcomes

PRESCRIBING: Exposure: duration of all antibiotic therapy in days

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: SS has served as consultant and received payments from B.R.A.H.M.S AG for speaking engagements. All other authors declare no conflicts of interest.

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

No explanation of randomisation process

Allocation concealment (selection bias)

Unclear risk

Details of allocation process not provided.

Blinding (performance bias and detection bias)
All outcomes

High risk

Open trial

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Done, Table 1 and text regarding excluded patients

Selective reporting (reporting bias)

Unclear risk

No explicit statement, so selective outcome reporting is possible.

Other bias

Low risk

Done, all biases addressed.

Baseline Outcomes similar?

Unclear risk

No baseline outcome measurement

Free of contamination?

Low risk

Done, procalcitonin results not available for controls.

Baseline characteristics similar?

Low risk

Done, mainly similar (IC days slightly different)

Huber 1982

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in hospital
CLINICAL PROBLEM: appropriateness of inpatient prescribing of cephalexin
SETTING: 1 university hospital in the USA

Interventions

FORMAT, Interventions: restrictive by expert approval and removal
Intervention Functions: restriction

DELIVERER: pharmacists
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: cephalexin dosing units

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

> 2 years' data pre‐ and postintervention

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: no statistical analysis of time series, presented as chart.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Hulgan 2004

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: physicians in the hospital
PATIENTS: all patients with clinical problem

CLINICAL PROBLEM: use of IV and oral quinolones

SETTING: university hospital in the USA

Interventions

FORMAT, Interventions: reminders (circumstantial and physical, computerised decision support system integrated into an existing provider order entry system)
Intervention Functions: enablement, environmental restructuring, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive use of IV quinolones

Outcomes

PRESCRIBING: Choice: number of orders for oral quinolone

FINANCIAL: savings on drug costs in USD

Notes

FINANCIAL SUPPORT: Funding: NIH Training Grant T32 AI 07474‐08 and Vanderbilt Clinical Research Scholar Award K12 RR17697 (TH). Competing Interests: DAT and RAM receive authorship royalties through Vanderbilt University from the commercial distribution of WizOrder. STR has received consulting fees from McKesson Information Solutions, which has licensed WizOrder for commercial distribution. None of the other authors has related disclosures or potential conflicts of interest.

ADDITIONAL DATA: email response from authors with additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Objective outcome measure

Analysed appropriately (ITS) ?

Low risk

Done in original paper: segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was increase in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

1 year of data pre‐ and postintervention

Free of other bias (ITS) ?

Low risk

Objective primary outcome, cost analysis adjusted to 2003 prices.

Inaraja 1986

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving antibiotics
CLINICAL PROBLEM: patients receiving antibiotics
SETTING: 1 447‐bed university hospital in Spain

Interventions

Interventions: educational outreach by review and recommend change; restrictive antibiotic policy but mode of restriction not clear
Intervention Functions: enablement, persuasion, restriction

DELIVERER: pharmacist

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: cephalosporin use measured with costs as a percentage of cephalosporins plus penicillins plus aminoglycosides

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

Only 12 months' data (9 months' pre‐ and 3 months' postintervention), so cannot control for seasonal effects.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Jensen 2011

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in ICUs
PARTICIPANTS: All adult patients in ICUs for > 24 hrs
CLINICAL PROBLEM: suspected sepsis
SETTING: 9 multidisciplinary ICUs across Denmark

Interventions

FORMAT:Interventions: reminders (circumstantial and physical, drug‐escalation algorithm and intensified diagnostics based on daily procalcitonin measurements); structural (rapid procalcitonin testing)
Intervention Functions: enablement, environmental restructuring, persuasion
DELIVERER: deparmental physicians (ICU)
COMPARISON: usual care
DESIRED CHANGE: increase effective

SAMPLE SIZE: yes, total 1200 participants. Details in Appendix 3

1200 participants were randomised and included in the analysis.

Outcomes

PRESCRIBING: Choice: time to first antibiotic dose; number (%) ICU days spent with at least 3 antibiotics

CLINICAL: intended 28‐day mortality; unintended (balancing) days in ICU; relative risk of renal impairment

Notes

FINANCIAL SUPPORT: Funding: Danish State, the Lundbeck Foundation, the Toyota Foundation, the A.P. Møller Foundation, the Horboe Foundation, and the Capitol Region of Denmark. Competing Interests: Dr. Jensen received speaker fee and travel reimbursement from B.R.A.H.M.S Diagnostica and an unrestricted grant from the organisation for sample transport and analysis. The remaining authors have not disclosed any potential conflicts of interest.

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Randomisation was performed 1:1 using a computerised algorithm created by the database manager.

Allocation concealment (selection bias)

Low risk

Investigators were masked to assignment before randomisation. Concealed block size, pre‐stratified for site of recruitment, initial Acute Physiology and Chronic Health Evaluation, and age (entered in an encrypted screening form in a password‐protected website)

Blinding (performance bias and detection bias)
All outcomes

Low risk

Investigators, treating physicians, and the co‐ordinator were unaware of outcomes during the study.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all randomised participants.

Selective reporting (reporting bias)

Low risk

Outcomes reported on all randomised participants.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

PCT measures only reported for intervention participants.

Baseline characteristics similar?

Low risk

Table 1

Jobson 2015

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians and nurses in the paediatric ED
PARTICIPANTS: all children with central lines
CLINICAL PROBLEM: time to first antibiotic dose in children with fever
SETTING: 1 university hospital in the USA

Interventions

FORMAT: Interventions: audit and feedback at individual and group level; educational meetings, dissemination of educational materials; educational outreach by academic detailing at individual and group level; reminders (circumstantial (on electronic health record), physical (cards attached to computers, weekly email newsletter), and verbal); structural (placing antibiotics in front‐line Pyxis stock)
Intervention Functions: education, enablement, environmental restructuring, persuasion
DELIVERER: departmental physicians
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

PRESCRIBING: Choice: % of participants receiving first antibiotic dose within 60 minutes

Notes

FINANCIAL SUPPORT: Funding: no external. Competing Interests: none declared

ADDITIONAL DATA: authors provided additional data about intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Statistical process control chart

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Primary outcome was time to first antibiotic dose from patient administration system.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Primary outcome was time to first antibiotic dose from patient administration system.

Incomplete outcome data addressed (ITS) ?

Low risk

Primary outcome was time to first antibiotic dose from patient administration system.

Free of selected reporting (ITS) ?

Low risk

Primary outcome was time to first antibiotic dose from patient administration system.

Free of other bias (ITS) ?

High risk

Only 8 months' pre‐intervention data, so seasonal effects cannot be excluded.

Jump 2012

Methods

STUDY DESIGN: CITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians and nurses in the hospitals
PARTICIPANTS: all patients in the hospitals
CLINICAL PROBLEM: patients requiring antibiotics or with suspected Clostridium difficile infection
SETTING: 1 long‐term care facility (intervention) and 1 hospital (control) in the USA

Interventions

FORMAT: Interventions: audit and feedback; educational outreach by review and recommend change
Intervention Functions: education, enablement, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: days of therapy with all antibiotics/1000 OBD

MICROBIAL: +ve C difficile tests per 1000 OBD

Notes

FINANCIAL SUPPORT: Funding: National Institutes of Health (grants R03‐AG040722 to RLPJ, K23‐DK087919 to PED, and R01‐AI063517 to RAB), Veterans Affairs Merit Review Program, Veterans Integrated Service Network 10 Geriatric Research Education and Clinical Center (VISN 10 GRECC). Competing Interests: RLPJ reports that she has consulted for GOJO and Pfizer and has received grant support ViroPharma. RAB reports that he has consulted for AstraZeneca and has received grant support from AstraZeneca, Ribx, Pfizer, and Steris. CJD reports that he has consulted for BioK, Optimer, and GOJO and has received grant support from ViroPharma, Merck, and Pfizer. All other authors report no conflicts of interest.

ADDITIONAL DATA: email with additional data; further information about the intervention is given in Jump 2013.

Microbial Risk of Bias: HIGH. Case definition low; Planned intervention low; Other infection control high, no data about infection control other than that the intervention also increased isolation of participants with C difficile infection. Moreover, the intervention discouraged repeat testing of participants with known C difficile infection, which may have biased the microbial outcome.

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computers

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Kallen 2009

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients requiring therapeutic antibiotics
SETTING: 1 community hospital in the USA

Interventions

FORMAT: Intervention: restrictive by removal from all wards

Intervention Function: restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease use of fluoroquinolones in order to contain an outbreak of Clostridium difficile infection

Outcomes

PRESCRIBING: Choice: use of fluoroquinolones, DDD/100 OBD

MICROBIAL: C difficile infections

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

Microbial Risk of Bias: HIGH, case definition yes, planned intervention no (part of response to outbreak), other infection control measures no (several important changes made at the same time as prescribing intervention)

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

No, as this was during an outbreak

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy computer

Free of other bias (ITS) ?

High risk

< 1 year data postintervention, fluoroquinolones reintroduced

Kanwar 2007

Methods

STUDY DESIGN: unintended consequences, cohort study

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the ED
PARTICIPANTS: 518 adult patients
CLINICAL PROBLEM: hospital admission diagnosis of CAP
SETTING: 1 hospital in the USA

Interventions

FORMAT, Interventions: audit and feedback; financial, institution incentive
Intervention Functions: enablement, incentive
DELIVERER: Blue Cross‐Blue Shield of Michigan incentive program
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

UNINTENDED CONSEQUENCES: confirmation of admission diagnosis by chest X‐ray, mean antibiotic administration per patient admitted with CAP

Notes

NRSI RISK OF BIAS CRITERIA:

1. Confounding: Low, confounding of the effect of intervention unlikely in this study

2. Selection of participants into the study: Low, selection into the study unrelated to intervention or outcome

3. Measurement class of interventions: Low, intervention status well defined, recorded at the time of intervention and unaffected by knowledge of the outcome or risk of the outcome

4. Departures from intended interventions: Low, no switches to other interventions or evidence of intervention failure

5. Missing data: Low, outcome data and intervention status reported on all 518 patients

6. Measurement of outcome: Low, outcome measure objective and measured from patient administration system

7. Selection of the reported result: Low, single, prespecified analysis of the intervention‐outcome relationship

FINANCIAL SUPPORT: Funding, none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Kerremans 2008

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: 1498 patients with bacterial infections (746 intervention, 752 control)

CLINICAL PROBLEM: antibiotic use in adult patients with bacterial infections

SETTING: 1 university hospital in the Netherlands

Interventions

FORMAT: Intervention: structural (rapid microbiology laboratory testing)
Intervention Functions: environmental restructuring

DELIVERER: specialist physician

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 1500 participants in total. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: total antibiotic use (average DDDs per patient)

CLINICAL: Intended: mortality

Notes

FINANCIAL SUPPORT: Funding: Dutch Association of University Hospitals (‘VAZ‐Doelmatigheidproject’ no. 99207). bioMerieux provided additional funding through an unrestricted grant. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Done, computer‐generated randomisation

Allocation concealment (selection bias)

High risk

No, states concealment was impossible.

Blinding (performance bias and detection bias)
All outcomes

High risk

No formal blinding attempted.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Done, Figure 1

Selective reporting (reporting bias)

Low risk

Done, all outcomes reported.

Other bias

Low risk

No other apparent issues

Baseline Outcomes similar?

Unclear risk

No baseline measurement of outcome

Free of contamination?

Low risk

Done

Baseline characteristics similar?

Low risk

Done, Table 1

Kerremans 2009

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: 211 patients with positive blood cultures (93 intervention, 108 control)

CLINICAL PROBLEM: antibiotic use in adult patients with bacterial infections

SETTING: 1 tertiary‐care university medical centre in the Netherlands

Interventions

FORMAT: Intervention: structural ‐ other (out‐of‐hours blood culture incubator intended to reduce laboratory turnaround time)

Intervention Function: environmental restructuring

DELIVERER: specialist physician

COMPARISON: usual care

DESIRED CHANGE: increase effective

POWER CALCULATION: no information. In the Discussion, the authors say "our sample size was too small to study the impacts of time to positivity (Gram stain), identification, and susceptibility testing separately on outcome".

Outcomes

PRESCRIBING: Choice: time to first antibiotic regimen change

CLINICAL: Intended: mortality and length of stay

Notes

FINANCIAL SUPPORT: Funding: Becton Dickinson provided the outside BACTEC incubator used in this study. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer‐generated list by independent epidemiologist

Allocation concealment (selection bias)

High risk

Allocation not concealed

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

1 episode of missing data in each arm of study

Selective reporting (reporting bias)

Low risk

Complete outcomes reported.

Other bias

Low risk

Baseline Outcomes similar?

Low risk

States no significant differences at baseline.

Free of contamination?

Low risk

Rapid reporting only occurred for intervention participants.

Baseline characteristics similar?

Low risk

States no significant differences at baseline.

Khan 2003

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: all patients in hospital
CLINICAL PROBLEM: Clostridium difficile‐associated diarrhoea
SETTING: an 800‐bed non‐teaching hospital in the UK

Interventions

FORMAT: no valid prescribing data. Restriction with educational meetings and dissemination of guideline.

DELIVERER: specialist physician
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

MICROBIAL: incidence of C difficile‐associated diarrhoea

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

> 1 year data in each of the 3 phases

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: no statistical analysis, mean cases per quarter compared between periods.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done: "The standard operating procedure for selection and processing stool specimens did not change over the study period. All stool specimens from inpatients with liquid or bloody diarrhoea and those receiving antibiotic therapy were tested for C. difficile toxin. C. difficile toxin was detected by cytotoxic activity on a fibroblast cell line, with specific neutralization by Clostridium sordelli antiserum"

Free of other bias (ITS) ?

High risk

NOT DONE for the intervention that was intended to reduce C difficile infection in Phase 3 Microbial Outcome Risk of Bias: Planned intervention: NOT DONE for unplanned intervention Phase 3 Case definition: DONE C difficile infection; all stool specimens from inpatients with liquid or bloody diarrhoea and those receiving antibiotic therapy were tested for C difficile toxin. Other infection control measures: DONE, well described and same in all 3 phases

Kim 2008

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving therapeutic antibiotics
CLINICAL PROBLEM: outbreak of ESBL infections
SETTING: 1 hospital in Korea

Interventions

FORMAT: Interventions: audit and feedback; restrictive by expert approval
Intervention Functions: enablement, restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive, use of cephalosporins to contain outbreak of ESBL

Outcomes

PRESCRIBING: use of cephalosporins (DDD/1000 OBD)

MICROBIAL: isolates of ESBL and new patients with ESBL infection

Notes

FINANCIAL SUPPORT: Funding: City of Seoul grant #10920 and KICOS project grant (Battelle Institute, Korea University). Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias HIGH. Case definition Low, planned intervention High (response to outbreak of ESBL), other infection control Unclear (no detail, and authors state that they did not take this into account in their analysis)

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Not in original paper but re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of other bias (ITS) ?

Low risk

Knudsen 2014

Methods

STUDY DESIGN: CITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians, nurses, and pharmacists in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: the intervention was intended to reduce infections caused by ESBL‐ and AmpC‐producing gram‐negative bacteria
SETTING: 1 university hospital (intervention) and 4 additional hospitals (control) in Denmark

Interventions

FORMAT: Interventions: audit and feedback; educational meetings; dissemination of guidelines; educational outreach by review and recommend change; reminders (physical, intranet and pocket guidelines; circumstantial, verbal by pharmacy technicians and infection control nurses)
Intervention Functions: education, enablement, environmental restructuring, persuasion.

The intervention also included the same components targeted at infection control measures (hand hygiene and isolation).
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: cefuroxime use in DDD/1000 OBD

MICROBIAL: cases per 1000 OBD per month

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: the authors provided multiple additional files of information about the intervention, including examples of the feedback newsletters (in Danish).

Microbial Risk of Bias: LOW, case definition low, planned intervention low, other infection control measures low

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

The antimicrobial stewardship intervention was simultaneous with an intervention to improve infection control practice (personal protection and isolation).

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computuers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from pharmacy and microbiology computuers

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computuers

Free of selected reporting (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computuers

Free of other bias (ITS) ?

Low risk

> 1 year of data pre‐ and postintervention. Microbial risk of bias low

Kristoffersen 2009

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 210 patients with suspected lower respiratory tract infection (103 intervention, 107 control)
CLINICAL PROBLEM: antibiotic consumption and length of stay in patients with suspected lower respiratory tract infections
SETTING: 3 hospitals in Denmark

Interventions

FORMAT: Interventions: dissemination of guideline; reminders (circumstantial and physical, decision support algorithm triggered by PCT test result); structural, introduction of PCT testing
Intervention Functions: education, enablement, environmental restructuring

DELIVERER: specialist physician

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 107 participants in each group. Details in Appendix 3

Outcomes

PRESCRIBING: Choice and exposure: antibiotics prescribed and duration of antibiotic treatment

CLINICAL: Balancing: length of stay and mortality

Notes

FINANCIAL SUPPORT: Funding: Danish Medical Research Council and the Danish Lung Association Study ID: NCT00415753, 271‐05‐0765. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer generated

Allocation concealment (selection bias)

Low risk

Concealed until PCT test results available

Blinding (performance bias and detection bias)
All outcomes

Low risk

Objective outcome measure: length of stay from routine data system

Incomplete outcome data (attrition bias)
All outcomes

Low risk

States that 3 patients died, 2 in PCT and 1 in control

Selective reporting (reporting bias)

Low risk

Objective outcome measure: length of stay from routine data system

Other bias

Low risk

Adequately powered

Baseline Outcomes similar?

Unclear risk

No beseline outcome measures

Free of contamination?

Low risk

PCT results only available for intervention participants.

Baseline characteristics similar?

Low risk

Mostly similar apart from those with cancer (7 in PCT and 0 in control), although this was adjusted for using sensitivity analysis.

Kritchevsky 2008

Methods

STUDY DESIGN: cluster RCT, hospital level

Risk of Bias: MEDIUM

Participants

PROVIDERS: physicians responsible for antimicrobial prophylaxis
PARTICIPANTS: patients undergoing cardiac surgery, hip and knee replacements, and hysterectomy, 44 clusters (hospitals)

CLINICAL PROBLEM: Preoperative antimicrobial prophylaxis

SETTING: 44 acute care hospitals in the USA

Interventions

FORMAT: Interventions: educational meetings with dissemination of guideline; educational outreach by academic detailing
Intervention Functions: education, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: increase effective

POWER CALCULATION: yes, 40 hospitals sampling 100 cases per measurement period. Details in Appendix 3

Outcomes

PRESCRIBING: Choice and exposure: 5 performance measures of antimicrobial prophylaxis (timing, receipt, duration, selection, and single preoperative dose)

Notes

FINANCIAL SUPPORT: Funding: grant R01 HS11331‐01A1 from the Agency for Healthcare Research and Quality and Centers for Disease Control and Prevention. Competing Interests: none declared

ADDITIONAL DATA: authors provided additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computerised random number generator

Allocation concealment (selection bias)

Low risk

By institution

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

Does not say if it was blinded or not

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Trained data collectors, completeness assured by project staff.

Selective reporting (reporting bias)

Low risk

All outcomes reported.

Other bias

High risk

High risk of selection bias, as hospitals nominated themselves to be included into the study.

Baseline Outcomes similar?

Low risk

See Table 3

Free of contamination?

Low risk

By institution

Baseline characteristics similar?

Low risk

See Table 2

Kumana 2001

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PATIENTS: all patients in the hospital

CLINICAL PROBLEM: patients receiving glycopeptides (teicoplanin or vancomycin)

SETTING: 1 hospital in Hong Kong

Interventions

FORMAT: Interventions: audit and feedback; educational meetings with dissemination of guidelines
Intervention Functions: education, enablement

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: DDD per month of glycopeptides

CLINICAL: Balancing: cohort study of patients who died following Staphylococcus aureus bacteraemia

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Done, 32 months' pre‐ and 11 months' postintervention, so secular or seasonal effects unlikely.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before and after) with χ2 test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

11 months' postintervention data, 32 months' pre‐intervention data

Free of other bias (ITS) ?

Low risk

Reliable primary outcome

Lacroix 2014

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: 30 physicians
PARTICIPANTS: 271 children with fever (131 intervention, 140 control)
CLINICAL PROBLEM: fever without source
SETTING: 1 university hospital in Switzerland

Interventions

FORMAT: Interventions: reminders (circumstantial and physical, decision support lab score derived from PCT, C‐reactive protein, and urine dipstick); structural, introduction of PCT testing
Intervention Functions: enablement, environmental lab score derived from PCT, C‐reactive protein, and urine dipstick
DELIVERER: departmental physicians
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 140 participants taking into account dropouts. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: % patients receiving antibiotics

CLINICAL: re‐admission and time to clinical resolution

Notes

FINANCIAL SUPPORT: Funding: commercial, bioMérieux for data management, statistical analysis, and loan of the procalcitonin assay. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Excel‐generated random numbers table

Allocation concealment (selection bias)

Low risk

Sealed envelopes

Blinding (performance bias and detection bias)
All outcomes

Low risk

Outcome measured from routine data.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Incomplete outcome data on 3 of 134 control and 4 of 140 intervention children.

Selective reporting (reporting bias)

Low risk

Outcomes reported on all remaining children.

Other bias

Low risk

The trial ended after completion of a sufficient number of children at the expected timing.

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

No lab score released for control children.

Baseline characteristics similar?

Low risk

Table 2

Lafaurie 2012

Methods

STUDY DESIGN: CITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving antibiotics
CLINICAL PROBLEM: use of fluoroquinolones
SETTING: 1 university hospital in France (intervention) with control data from 700 hospitals in the Coordinating Centres for Nosocomial Infection Control

Interventions

FORMAT: Interventions: audit and feedback; educational meeting with dissemination of guideline; educational outreach by review and recommend change
Intervention Functions: education, enablement, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: fluoroquinolone use in DDD/1000 OBD

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: HIGH, case definition Low, planned intervention Low, other infection control High, increase in use of alcohol‐based handrub throughout study period

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Low risk for prescribing outcome

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of anaysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of other bias (ITS) ?

Low risk

> 1 year of data pre‐ and postintervention

Landgren 1988

Methods

STUDY DESIGN: CBA

Risk of Bias: HIGH

Participants

PROVIDERS: all surgeons at the hospitals
PARTICIPANTS: all patients with clinical problem
CLINICAL PROBLEM: patients receiving surgical antibiotic prophylaxis
SETTING: 12 hospitals in Australia

Interventions

FORMAT: Interventions: audit and feedback; educational meetings with dissemination of guidelines; educational outreach by academic detailing; reminders (physical, posters)
Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: pharmacist
COMPARISON: 6 hospitals were used as control in year 1, then intervention and control hospitals were crossed over in year 2
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice and exposure: appropriate duration and timing of prophylaxis

FINANCIAL: drug cost savings in AUD

Notes

FINANCIAL SUPPORT: Funding: Commonwealth Department of Health. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

CBA; "hospitals were paired being matched as far as possible for type size and surgical load"

Allocation concealment (selection bias)

High risk

Not done, CBA

Blinding (performance bias and detection bias)
All outcomes

High risk

Not stated; all hospitals in same Australian state, CBA so not possible

Incomplete outcome data (attrition bias)
All outcomes

Unclear risk

No statement

Selective reporting (reporting bias)

Low risk

Objective primary outcome measure on all patients

Other bias

Low risk

No other apparent biases found.

Baseline Outcomes similar?

Low risk

Done, pre‐intervention data for primary outcome similar in intervention and control hospitals.

Free of contamination?

Low risk

Intervention and control sites were different hospitals.

Baseline characteristics similar?

Unclear risk

Only information is about characteristics of hospital (teaching, rural, etc.), no data about case mix and unlikely to change over study period.

Landman 1999

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients requiring antibiotic treatment
SETTING: university hospital in the USA

Interventions

FORMAT: no valid prescribing outcome data. Restriction.

DELIVERER: specialist physician
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

MICROBIAL: Incidence (new cases per 1000 discharges per month) of ceftazidime‐resistant Klebsiella pneumoniae, MRSA, and cefotaxime‐resistant Acinetobacter species (ITS data)

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias MEDIUM: case definition: Low; planned intervention: Low; infection control practices: High. At the start of the intervention, contact precautions were changed to include patients with Clostridium difficile infection.

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Reliable primary outcome

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after) with t‐test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Unclear risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Unclear risk

Not clear, no information about protocols for clinical sampling or testing

Free of other bias (ITS) ?

High risk

Change in infection control practices at start of intervention

LaRosa 2007

Methods

STUDY DESIGN: unintended consequences, cross‐sectional and cohort study

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 15,440 patients (cross‐sectional) and 360 patients (cohort)
CLINICAL PROBLEM: receiving restricted antibiotics
SETTING: 1 hospital in the USA

Interventions

FORMAT, Interventions: restrictive by prior approval
Intervention Functions: restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

UNINTENDED CONSEQUENCES: delay in ordering of restricted antibiotics

Notes

ROBINS‐I RISK OF BIAS CRITERIA:

1. Confounding: Low, confounding of the effect of intervention unlikely in this study

2. Selection of participants into the study: Low, selection into the study unrelated to intervention or outcome

3. Measurement of interventions: Low, intervention status well defined, recorded at the time of intervention and unaffected by knowledge of the outcome or risk of the outcome

4. Departures from intended interventions: Low, no switches to other interventions or evidence of intervention failure

5. Missing data: Low, outcome data and intervention status complete for both cross‐sectional and cohort study

6. Measurement of outcome: Low, outcome measures objective and ascertained from patient administration system

7. Selection of the reported result: Low, single analysis of prespecified outcomes

FINANCIAL SUPPORT: Funding: Centers for Education and Research on Therapeutics grant (U18‐HS10399) from the Agency for Healthcare Research and Quality (AHRQ), the Mentored Patient‐Oriented Research Career Development Award (K23‐AI‐060887‐01) of the NIH from the National Institute of Allergy and Infectious Diseases, Public Health Service grant (DK‐02987‐01) of the NIH, and an Improving Patient Safety Through Reduction in Medication Errors grant (P01‐HS11530‐01) from the AHRQ.

Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Lautenbach 2003

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians at the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: requiring antibiotic treatment
SETTING: 1 university hospital in the USA

Interventions

FORMAT: Intervention: restrictive by expert approval, not clear if there was also removal
Intervention Functions: restriction

DELIVERER: AMT
COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: vancomycin use in DDD per 1000 patient days

MICROBIAL: proportion of enterococci resistant to vancomycin

Notes

FINANCIAL SUPPORT: Funding: Public Health Service (grant DK‐02987‐01) of the National Institutes of Health (to EL). This study was also supported in part by an Agency for Healthcare Research and Quality Centers for Education and Research on Therapeutics co‐operative agreement (U18‐HS10399). Competing Interests: no information

ADDITIONAL DATA: authors provided additional prescribing data to enable segmented regression analysis

Microbial Risk of Bias HIGH: Case definition: Low. Planned intervention: High: unplanned intervention in response to emergence of VRE over the previous 3 years. Other infection control measures: Low

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Shape of effect pre‐specified (ITS) ?

Low risk

Unlikely to affect data collection (ITS) ?

Low risk

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Incomplete outcome data addressed (ITS) ?

Low risk

Free of selected reporting (ITS) ?

Low risk

Free of other bias (ITS) ?

High risk

Microbial outcome risk of bias: HIGH .

Lawes 2012

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: Staphylococcus aureus bacteraemia and use of antibiotics considered to be high risk for Clostridium difficile infection
SETTING: 1 university hospital in the UK

Interventions

FORMAT: Interventions: dissemination of new antibiotic policy 3 months before the structural intervention; restrictive: the new antibiotic policy included requirement for expert approval; structural: introduction of universal screening for MRSA
Intervention Functions: education, environmental restructuring, restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: no valid data for re‐analysis in the paper, but the authors' ARIMA time series analysis includes the effect of the change in antibiotic policy on the microbial outcomes

MICROBIAL: S aureus bacteraemias, MRSA, and MSSA

Notes

FINANCIAL SUPPORT: Funding: Scottish government Health Directorate. Competing Interests: IG has received personal and grant financial support from companies manufacturing diagnostics and therapeutics for MRSA. BE has received grant financial support from Novartis. Other authors: none

ADDITIONAL DATA: authors provided additional data

Microbial Risk of Bias MEDIUM: case definition High, MRSA screening introduced at the same time as change in antibiotic policy, planned intervention Low, other infection control Low for isolation and personal infection control

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

The change in antibiotic policy was 9 months after the introduction of MRSA screening. The authors' analysis suggests an independent effect from the policy change.

Analysed appropriately (ITS) ?

Low risk

ARIMA time series analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Routine patient administration systems

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine patient administration systems

Incomplete outcome data addressed (ITS) ?

Low risk

Routine patient administration systems

Free of selected reporting (ITS) ?

Low risk

Routine patient administration systems

Free of other bias (ITS) ?

Low risk

Other microbial ROB criteria low

Layios 2012

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the ICUs
PARTICIPANTS: 389 patients in the ICUs for > 48 h and with PCT measured (211 intervention, 178 control)
CLINICAL PROBLEM: duration of antibiotic treatment
SETTING: 5 ICUs in 1 university hospital in Belgium

Interventions

FORMAT: Interventions: reminders (circumstantial and physical, decision support algorithm triggered by PCT test result); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring

DELIVERER: specialist physician (ICU and respiratory)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 250 participants in each group. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: antibiotic consumption as % ICU days and DDD/100 OBD

CLINICAL: mortality, length of ICU stay, days on ventilator

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

"patients were prospectively randomized", but no information about how

Allocation concealment (selection bias)

Unclear risk

"patients were prospectively randomized", but no information about how

Blinding (performance bias and detection bias)
All outcomes

Low risk

Procalcitonin only reported for intervention participants.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all participants.

Selective reporting (reporting bias)

Low risk

Outcomes reported on all participants.

Other bias

High risk

Study did not achieve recruitment required by power calculation.

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

Procalcitonin only reported for intervention participants.

Baseline characteristics similar?

Low risk

Table 1

Lee 1995

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: physicians
PATIENTS: a total of 480 patients reviewed during study period

CLINICAL PROBLEM: patients receiving ceftriaxone

SETTING: a hospital in the USA

Interventions

FORMAT: Interventions: educational meetings with dissemination of guidelines; reminders (circumstantial and physical, letters sent to physicians when intervention needed plus posters)
Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: grams of ceftriaxone and cefotaxime

FINANCIAL: cost of intervention (0.5 FTE ID physician and savings on drug costs)

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy computer

Free of other bias (ITS) ?

High risk

> 1 year data pre‐ and postintervention, but only 4 postintervention time points (quarterly data)

Lee 2007

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all staff in the hospital
PARTICIPANTS: all patients receiving cephalosporins
CLINICAL PROBLEM: high endemic rate of ESBL infections
SETTING: 1 university children's hospital in Korea

Interventions

FORMAT: Intervention: educational outreach by review and recommend change
Intervention Functions: enablement, persuasion

DELIVERER: specialist physicians (paediatric ID)

COMPARISON: pre‐intervention

DESIRED CHANGE: decrease in use of extended‐spectrum cephalosporins to reduce ESBL infections

Outcomes

PRESCRIBING: Choice: days on target antibiotics/1000 OBD

MICROBIAL: ESBL strains as % total isolates

Notes

FINANCIAL SUPPORT: Funding: Wyeth Research. Competing Interests: none declared.

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias LOW: case definition yes, planned intervention yes, stable ESBL for 3 years pre‐intervention, other infection control yes

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Infection control policies unchanged throughout (page 631).

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Decrease

Unlikely to affect data collection (ITS) ?

Low risk

Data about prescribing and microbial outcomes were from routine, electronic data systems.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data about prescribing and microbial outcomes were from routine, electronic data systems.

Incomplete outcome data addressed (ITS) ?

Low risk

Data about prescribing and microbial outcomes were from routine, electronic data systems.

Free of selected reporting (ITS) ?

Low risk

Data about prescribing and microbial outcomes were from routine, electronic data systems.

Free of other bias (ITS) ?

Low risk

4 years' data pre‐ and 3 years' data postintervention, so can account for temporal trends.

Lee 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the units
PARTICIPANTS: all patients in the units
CLINICAL PROBLEM: requiring therapeutic antibiotics
SETTING: internal medicine (2 units) at 1 university hospital in Canada

Interventions

FORMAT: Interventions: audit and feedback; educational meetings (monthly with residents) with dissemination of educational materials
Intervention Functions: education, enablement, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: DDD/1000 OBD of target antibiotics

FINANCIAL: intervention cost and savings (cost of all antibiotics)

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: authors provided additional data about the intervention and for the meta‐regression

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcomes were measured from electronic pharmacy data.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcomes were measured from electronic pharmacy data.

Incomplete outcome data addressed (ITS) ?

Low risk

Outcomes were measured from electronic pharmacy data.

Free of selected reporting (ITS) ?

Low risk

Outcomes were measured from electronic pharmacy data.

Free of other bias (ITS) ?

Low risk

> 12 months' data pre‐ and postintervention

Lesprit 2013

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in medical and surgical wards
PARTICIPANTS: 753 patients receiving antibiotics (376 intervention, 377 control)
CLINICAL PROBLEM: duration of treatment in patients receiving 1 of the targeted antibiotics for at least 3 days
SETTING: 1 university hospital in France

Interventions

FORMAT: Intervention: educational outreach by review and recommend change

Intervention Functions: enablement, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 253 participants in each group. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: duration of all antibiotic treatment

CLINICAL: Balancing: mortality, ICU admission, new course of antibiotic treatment, length of stay

FINANCIAL: intervention cost and savings (supplementary file)

MICROBIAL: secondary infection and/or colonisation with multidrug‐resistant bacteria in the 6 months following randomisation

Notes

FINANCIAL SUPPORT:Funding: none. Competing Interests: none declared

ADDITIONAL DATA: supplementary file online with data about financial and microbial outcomes, no response from authors to request for additional data

Microbial Risk of Bias: case defintion low, planned intervention low, other infection control unclear, no information

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Eligible patients were allocated to either the intervention or the control group using a computer‐generated randomisation list, which was maintained independently of the IDP.

Allocation concealment (selection bias)

Low risk

Concealment of the allocation was maintained, as the physician in charge of the patient and the IDP were involved only after randomisation.

Blinding (performance bias and detection bias)
All outcomes

High risk

Blinding was not possible.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

No participants were lost to follow‐up.

Selective reporting (reporting bias)

Low risk

Outcomes reported on all participants.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

IDP only visited intervention participants.

Baseline characteristics similar?

Low risk

Table 1

Leverstein‐van Hall 2001

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: Departments of Neurology and Neurosurgery

PARTICIPANTS: all patients in the departments
CLINICAL PROBLEM: colonisation with gentamicin‐resistant Enterobacteriaceae
SETTING: 1 858‐bed university hospital in the Netherlands

Interventions

FORMAT: no valid prescribing data, restriction by expert approval and removal

DELIVERER: specialist physician

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

MICROBIAL: prevalence of gentamicin‐resistant Enterobacteriaceae in weekly screening stool swabs

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

NOT DONE, major changes in infection control 4 weeks before the antibiotic restriction. Separate effect cannot be estimated because no screening before change in infection control.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: no statistical analysis, time series data presented as run chart.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Screening protocol was the same pre‐ and postintervention.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Screening protocol was the same pre‐ and postintervention.

Incomplete outcome data addressed (ITS) ?

Unclear risk

NOT CLEAR, no explicit statement about complete screening samples for all participants

Free of selected reporting (ITS) ?

Unclear risk

NOT CLEAR, no explicit statement about complete screening samples for all participants

Free of other bias (ITS) ?

High risk

Microbial Outcome Risk of Bias Criteria: Case definition: DONE colonisation by screening; Planned intervention: NOT DONE, in response to increase in GRE; Other infection control practices: NOT DONE changes 4 weeks before antibiotic restriction; Isolation: isolation of gentamicin‐resistantEnterobacteriaceae‐positive patients in either side‐rooms or cohorted with other positive patients; IC practices: increase in education plus several new hygiene practices: disposable washing gloves, elbow‐directed soap dispensers; new room‐cleaning protocol. Hygiene was emphasised and more stringent barrier precautions.

Liebowitz 2008

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital

CLINICAL PROBLEM: incidences of MRSA

SETTING: 1 general hospital in the UK

Interventions

FORMAT: Intervention: educational meetings with dissemination of guideline; reminders, verbal on rounds

Intervention Function: education, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

Outcomes

PRESCRIBING: Choice: DDDs per 1000 OBD each month

MICROBIAL: Episodes of MRSA blood isolates per 1000 OBD each month

Notes

FINANCIAL SUPPORT: Funding: unrestricted educational grant from Wyeth. Competing Interests: LDL received honoraria for lectures from Bayer and Bard.

ADDITIONAL DATA: no response from authors to request for additional data

Microbial ROB HIGH; case definition Low, planned intervention Low, other infection control High, no information about infection control other than screening for MRSA

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

18 months' pre‐ and 15 months' postintervention data

Analysed appropriately (ITS) ?

Low risk

Segmented regresssion analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analysis is point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Pharmacy data used pre‐ and postintervention.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Pharmacy data used pre‐ and postintervention.

Incomplete outcome data addressed (ITS) ?

Low risk

Pharmacy data used pre‐ and postintervention.

Free of selected reporting (ITS) ?

Low risk

Pharmacy data used pre‐ and postintervention.

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Linkin 2007

Methods

STUDY DESIGN: unintended consequences, cohort study

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 200 patients
CLINICAL PROBLEM: requests for restricted antibiotic to the Antimicrobial Stewardship Program
SETTING: 1 hospital in the USA

Interventions

FORMAT: Interventions: restrictive
Intervention Functions: restriction
DELIVERER: AMT
COMPARISON: patients with appropriate vs inappropriate requests
DESIRED CHANGE: decrease excessive

Outcomes

UNINTENDED CONSEQUENCES: accuracy of laboratory and clinical information provided in calls to the Antimicrobial Stewardship Program

Notes

ROBINS‐I RISK OF BIAS CRITERIA:

1. Confounding: Low, the effects of inaccurate communication and each of the potential confounders on the risk of inappropriate antimicrobial recommendations were evaluated in bivariable analyses

2. Selection of participants into the study: Low, selection into the study unrelated to intervention or outcome

3. Measurement of interventions: Low, antimicrobial recommendations were evaluated for appropriateness by a 3‐person panel of infectious diseases experts blinded to the accuracy of information communicated during the Antimicrobial Stewardship Program call

4. Departures from intended interventions: Low, no switches to other interventions or evidence of intervention failure

5. Missing data: High, panelists could not agree on appropriateness of treatment for 37 patients. Outcome data complete for the 163 included patients

6. Measurement of outcome: Low, outcome measures objective and ascertained from patient administration system

7. Selection of the reported result: High, multiple secondary analyses were performed using the main study outcome

FINANCIAL SUPPORT: Funding: National Institutes of Health, Agency for Healthcare Research and Quality, and University of Pennsylvania. Competing Interests: none declared.

ADDITIONAL DATA: no response from authors to request for additional data

Liu 2013

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: Department of Emergency Medicine, ICU staff

PARTICIPANTS: adults (age > 18) with sepsis
CLINICAL PROBLEM: sepsis without 7 exclusion criteria (cultures positive with Pseudomonas aeruginosa,Acinetobacter baumannii,Mycobacterium tuberculosis or any fungi, viral or parasitic infection, chronic localised inflammation, antibacterial therapy for > 48 h, immunosuppression, cancer, or refusal to consent)
SETTING: ICU in 1 university hospital in China

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm triggered by measurement of PCT); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring

DELIVERER: specialist physician

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Exposure: duration of all antibiotic treatment

CLINICAL: Balancing: 28‐day mortality, length of hospital stay, length of ICU stay, recurrence within 28 days

Notes

Translated from Chinese

FUNDING: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Random number table method

Allocation concealment (selection bias)

Unclear risk

No information about concealment

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

No information about blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcome reported on all participants.

Selective reporting (reporting bias)

Low risk

Outcome reported on all participants.

Other bias

High risk

The study had 7 exclusion criteria that are not all clearly defined, so there is a high risk of selection bias, especially as allocation was probably not concealed.

Baseline Outcomes similar?

Unclear risk

No data about baseline outcomes

Free of contamination?

Low risk

PCT results only for intervention participants.

Baseline characteristics similar?

Low risk

Table 1, age, gender, APACHE score, comorbidities

Long 2014

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians
PARTICIPANTS: 216 consecutive patients hospitalised with exacerbations of acute asthma
CLINICAL PROBLEM: antibiotic treatment of acute asthma
SETTING: 1 university hospital in China

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm triggered by measurement of PCT); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring

DELIVERER: departmental physicians (Internal and Geriatric Medicine)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 90 participants per group. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: % treated with antibiotics

CLINICAL: Balancing: length of hospital stay; clinical, laboratory, and spirometry outcomes at discharge; and results of spirometry at the 12‐month follow‐up examination, as well as the results of the Asthma Control Test

Notes

FINANCIAL SUPPORT: Funding: Shanghai Fifth People’s Hospital Science Foundation and Minhang District Natural Science Foundation of Shanghai. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"Allocation to either intervention was conducted according to computer‐generated random numbers produced by an independent statistician."

Allocation concealment (selection bias)

Low risk

"After randomization, an opaque, sealed, sequentially numbered envelope containing the PCT or control protocol was prepared for each subject according to group assignment"

Blinding (performance bias and detection bias)
All outcomes

High risk

Blinding was not possible.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all 180 randomised participants.

Selective reporting (reporting bias)

Low risk

Antibiotic use reported for all 180 participants.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

Procalcitonin only reported on intervention participants.

Baseline characteristics similar?

Low risk

Tables 1 and 2

Madaras‐Kelly 2006

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all prescribers and staff

PATIENTS: all inpatients

CLINICAL PROBLEM: patients receiving antibiotic treatment and patients with MRSA infections

SETTING: university‐affiliated veterans hospital in the USA

Interventions

FORMAT: Interventions: educational meetings, in‐service training sessions with dissemination of guideline; reminders (circumstantial, electronic, triggered by prescribing target drugs)
Intervention Functions: education, enablement, environmental restructuring

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: change in use of levofloxacin, ciprofloxacin, and other antibiotics

MICROBIAL: MRSA infection rate (number/1000 OBD)

Notes

FINANCIAL SUPPORT: This article is the result of work supported with resources and the use of facilities at the Boise Veterans Affairs Medical Center, and is partially funded by an unrestricted educational grant from Wyeth Pharmaceuticals. Conflict of interest: no information

ADDITIONAL DATA: email response from authors but no additional data

Microbial ROB: MEDIUM. Case definition Low, Planned intervention Low, Other infection control High, prescribing intervention coincident with infection control interventions

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

Data collected for 11 months postintervention. Season included as a variable in the model, and summer found to be associated with lower MRSA infection rate. Coincident with infection control intervention for norovirus outbreak, infection control variables included in the model and significantly associated with lower MRSA rate.

Analysed appropriately (ITS) ?

Low risk

Done in original paper: segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Unclear risk

Not clear, no information about protocols for sampling or testing for MRSA over the study period

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Objective data about MRSA

Incomplete outcome data addressed (ITS) ?

Low risk

Identification of cases was the same in the pre‐ and postintervention phases.

Free of selected reporting (ITS) ?

Low risk

In addition to the primary outcome of MRSA infections, the figure shows percentage of MRSA for all Staphylococcus aureus isolates with a reduction coincident with the intervention.

Free of other bias (ITS) ?

High risk

NOT DONE data are MRSA infection rates in 6‐month time periods based on very small numbers of cases (80 cases in 3½ years).

Microbial Outcome Risk of Bias: Case definition: MRSA infection. Screening for nosocomial infections was performed through daily review of hospital admissions and discharges, intravenous antibiotic use by patients admitted to the emergency department, and laboratory reports with case confirmation by review of medical records. “An infection was assumed to be caused by MRSA if cultures of blood, intravenous line, sputum, urine, tissue, or stool obtained at the time of symptom development yielded MRSA.” Planned intervention: YES. Intervention introduced in July 2003 in response to May 2003 SHEA recommendations that institutions where MRSA is endemic should consider limiting the use of broad‐spectrum antibiotics, especially fluoroquinolones. Other infection control: NOT DONE. Antibiotic intervention coincident with environmental decontamination and hand hygiene campaign because of norovirus outbreak. Data about some infection control variables showed no change after start of intervention.

Magedanz 2012

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: physicians in the hospital
PARTICIPANTS: all patients in hospital

CLINICAL PROBLEM: antibiotic use in cardiology hospital, primary target fluorquinolone use

SETTING: 1 cardiology hospital in Brazil

Interventions

FORMAT: Interventions: educational outreach by review and recommend change
Intervention Functions: enablement, persuasion

DELIVERER: Intervention 1 ID physician (2 h per day), Intervention 2 AMT (physician plus pharmacist, 4 h per day)

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

Outcomes

PRESCRIBING: Choice: monthly consumption (DDDs/100 OBD) of antibiotics, primary target fluoroquinolones

FINANCIAL: hours of time to implement the intervention

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

States in discussion that most changes not related to any other external factor.

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention is point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from electronic pharmacy records

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from electronic pharmacy records

Incomplete outcome data addressed (ITS) ?

Low risk

Data from electronic pharmacy records

Free of selected reporting (ITS) ?

Low risk

Data from electronic pharmacy records

Free of other bias (ITS) ?

Low risk

> 12 months' data in each of the 3 study phases

Maravic‐Stojkovic 2011

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in cardiac surgery
PARTICIPANTS: 205 patients undergoing cardiac surgery
CLINICAL PROBLEM: antibiotic treatment after surgery
SETTING: 1 university hospital in Serbia

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm triggered by measurement of PCT); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring
DELIVERER: departmental physicians (ICU and cardiology)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: unclear, target effect size decrease from 45% of antibiotic use in the standard group to 22% in the procalcitonin group, but no data about sample size

Outcomes

PRESCRIBING: Exposure: % treated with antibiotics

CLINICAL: ICU stays, hospital stay, rehospitalisation, incidence of infections, severe non‐infection complications, and mortality rate with 1‐year follow‐up

FINANCIAL: cost of antibiotics and PCT tests

Notes

FINANCIAL SUPPORT: no information provided

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer‐generated randomisation scheme

Allocation concealment (selection bias)

Unclear risk

No information about concealment

Blinding (performance bias and detection bias)
All outcomes

High risk

Blinding not possible

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all 205 participants.

Selective reporting (reporting bias)

Low risk

Antibiotic treatment reported on all participants.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

PCT only measured on intervention participants.

Baseline characteristics similar?

Low risk

Tables 1 and 2

Marwick 2013

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in medical and surgical wards
PARTICIPANTS: all patients in medical and surgical wards
CLINICAL PROBLEM: suspected sepsis (systemic inflammatory response and clinical suspicion of infection)
SETTING: 1 university hospital in Scotland

Interventions

FORMAT: Interventions: audit and feedback; educational meetings with dissemination of guidelines; reminders (physical, posters in the wards and monthly email to doctors)
Intervention Functions: education, enablement, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

PRESCRIBING: Choice: time to first antibiotic dose

Notes

FINANCIAL SUPPORT: Funding: Scottish Government Chief Scientist Office (CSO) Clinical Academic Training Fellowship (CAF/07/06). Competing Interests: salary costs for 2 investigators from CSO, no others declared

ADDITIONAL DATA: email response from authors to request for additional data with additional detail from a PhD thesis

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

There was a national intervention (Scottish Patient Safety Program) that included reducing time to rescue of deteriorating patients throughout the pre‐ and postintervention phases.

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Objective primary outcome measure (time to first antibiotic dose) collected by single person (CM).

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Objective primary outcome measure (time to first antibiotic dose) collected by single person (CM).

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data collected on all participants.

Free of selected reporting (ITS) ?

Low risk

Outcome data collected on all participants.

Free of other bias (ITS) ?

Low risk

Data collected over winter months in pre‐ and postintervention period.

Masia 2008

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 278 patients receiving antibiotics, 146 intervention, 132 control
CLINICAL PROBLEM: prescription of target antibiotics
SETTING: 1 university hospital in Spain

Interventions

FORMAT: Interventions: educational outreach by review and recommend change
Intervention Functions: education, enablement
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 140 participants in each group

Outcomes

PRESCRIBING: Choice: use of target drugs in DDD

CLINICAL: length of stay, mortality, re‐admissions

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Eligible prescriptions were allocated daily to either the intervention or the control group using a computer‐generated randomisation list.

Allocation concealment (selection bias)

Low risk

Concealment of allocation was pharmacy controlled. Instruction in allocation concealment was provided.

Blinding (performance bias and detection bias)
All outcomes

High risk

Blinding was not possible.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcome data reported on all randomised participants.

Selective reporting (reporting bias)

Low risk

Outcome data reported on all randomised participants.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

High risk

The authors say: "To minimize contamination bias, that is, any change in antibiotic prescription practice in the control group, only the infectious diseases physicians and hospital pharmacists were informed about the implementation of the program." However, they were placing written recommendations in case notes for intervention patients, and physicians caring for those patients would also be caring for control patients.

Baseline characteristics similar?

Low risk

Table 1

May 2000

Methods

STUDY DESIGN: Controlled ITS

Risk of bias: MEDIUM

Participants

PROVIDERS: staff of Trauma & Burns ICU (TBICU), Medical ICU (MICU), and Surgical ICU (SICU)
PATIENTS: all patients in these ICUs

CLINICAL PROBLEM: adults needing intensive care

SETTING: single > 500‐bed university hospital in the USA

Interventions

FORMAT: Intervention: dissemination of guideline

Intervention Function: education

DELIVERER: department physician

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of vancomycin, 3rd‐generation cephalosporins, and piperacillin tazobactam per 1000 patient days

MICROBIAL: MRSA infections and VRE infections per 1000 patient days

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Microbial ROB HIGH: Case definition: Low. Planned intervention: High for intervention ward (response to increasing VRE in previous 2 years). However, steady increase not an outbreak and VRE data presented for other wards with no intervention. Other infection control: High, no information about isolation or infection control practices before or after the intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Only 9 months' data pre‐intervention, so secular/seasonal effects possible. No information about infection control practices before or after the intervention

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: χ2 test, uncontrolled before‐after with Poisson regression analysis of VRE rates.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, objective outcome measure

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Objective outcome measure, VRE infections

Incomplete outcome data addressed (ITS) ?

Low risk

Done, objective outcome measure

Free of selected reporting (ITS) ?

Unclear risk

Not clear, no information about protocol for sampling or testing over study period

Free of other bias (ITS) ?

Low risk

>1 year of data pre‐ and post‐intervention

McElnay 1995

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: all patients in hospital
CLINICAL PROBLEM: all patients receiving antibiotics
SETTING: 370‐bed District General Hospital in the UK

Interventions

FORMAT: Interventions: educational meetings and dissemination of new antibiotic policy; educational outreach by academic detailing, "education of junior medical staff on the rationale behind the antibiotic selection was also carried out by clinical pharmacists" (p208); restrictive by compulsory order form and removal
Intervention Functions: education, persuasion, restriction

DELIVERER: department physician
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: dosage units of target antibiotic

FINANCIAL: expenditure on antibiotics

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

12 months' data pre‐ and postintervention

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

Antibiotic costs were adjusted to 1989 prices.

McGowan 1976

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients requiring antibiotic treatment
SETTING: single university hospital in USA

Interventions

FORMAT: Intervention: restrictive by expert approval and probably by review and make change

Intervention Function: restriction

DELIVERER: specialist physician

COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: grams of chloramphenicol (thousands), data are also presented for other drugs (ampicillin, nafcillin, and cloxacillin)

Notes

FINANCIAL SUPPORT: Funding: grants 5R01‐A1‐23, 2T01‐AJ‐08, and IT01‐Ai‐447 from the National Institute of Allergy and Infectious Diseases. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Data over 8 years, 4 years pre‐ and 4 years postintervention

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

McLaughlin 2005

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: staff from 12 medical wards
PATIENTS: all patients in the wards

CLINICAL PROBLEM: adults requiring IV antibiotic therapy

SETTING: single university hospital in the UK

Interventions

FORMAT: Interventions: educational meetings with dissemination of protocol for IV to oral switch; educational outreach by academic detailing; reminders (circumstantial, sticker in charts of patients receiving IV antibiotics and physical, posters in wards and at nursing stations)
Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: modification of existing management (faster switch from IV to oral administration of antibiotics)

Outcomes

PRESCRIBING: Choice: appropriateness of timing of IV to oral switch

Notes

FINANCIAL SUPPORT: Funding: Greater Glasgow Health Board. Competing Interests: no information

ADDITIONAL DATA: authors provided additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Not done, data were only collected for 4 weeks before and after the intervention, so secular changes could have accounted for any differences.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after) with χ2 test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Unclear risk

Not stated

Knowledge of the allocation adequately prevented(ITS)?

High risk

Incomplete outcome data addressed (ITS) ?

Unclear risk

No information about reliability or completeness of primary outcome

Free of selected reporting (ITS) ?

Unclear risk

No information about reliability or completeness of primary outcome

Free of other bias (ITS) ?

High risk

Only 4 weekly time points pre‐ and postintervention

McNulty 1997

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the elderly care unit
PARTICIPANTS: all patients in the elderly care unit
CLINICAL PROBLEM: Clostridium difficile in the elderly care unit
SETTING: elderly care unit in 1 District General Hospital (non‐teaching) in the UK

Interventions

FORMAT: Interventions: dissemination of new antibiotic policy; restrictive by removal and by review and make change
Intervention Functions: education, enablement, environmental restructuring, persuasion, restriction

DELIVERER: pharmacist
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: monthly cost of cefuroxime (ITS data)

MICROBIAL: cases of CDI per month (ITS data)

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Microbial ROB HIGH: Case definition: Low, CDI, definition unchanged during the study periods. Unplanned intervention: High, antibiotic restriction was implemented in response to increasing cases of CDI in the preceding 7 months despite increased infection control. Other infection control measures: High, changes to environmental cleaning and reminders about hand hygiene implemented 3 months before the start of intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Analysed appropriately (ITS) ?

Low risk

Shape of effect pre‐specified (ITS) ?

Low risk

Unlikely to affect data collection (ITS) ?

Low risk

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Incomplete outcome data addressed (ITS) ?

Low risk

Free of selected reporting (ITS) ?

Low risk

Free of other bias (ITS) ?

Low risk

Mercer 1999

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: physicians
PARTICIPANTS: all patients with clinical problem
CLINICAL PROBLEM: patients receiving ceftriaxone
SETTING: a 360‐bed community hospital in the USA

Interventions

FORMAT: Interventions: dissemination of guidelines; educational outreach by academic detailing; educational outreach by review and recommend change; reminders (physical, posters in clinical areas); restrictive by compulsory order form, expert approval required, removal and review and make change
Intervention Functions: education, environmental restructuring, restriction

DELIVERER: specialist physician (ID)

COMPARISON: usual care

DESIRED CHANGE: reduction in established management (reduction in antibiotic costs)

Outcomes

PRESCRIBING: Choice: cost of antibiotics (USD) as an indicator of use

COSTS: cost of antibiotics

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Full year before and after

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

Antibiotic costs were adjusted to 1995 prices and excluded ancillary or administrative charges.

Meyer 1993

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients receiving antibiotics
SETTING: 1 university hospital in the USA

Interventions

FORMAT: Interventions: restrictive by expert approval required
Intervention Functions: restriction
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of ceftazidime, imipenem, and ceftriaxone reported as number of approvals for these drugs

MICROBIAL: incidence of ceftazidime‐resistant Klebsiella pneumoniae as the rate per 1000 average daily census

Notes

FINANCIAL SUPPORT: Funding: BMA Medical Foundation. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Microbial ROB: HIGH Case definition Low, Unplanned intervention High, Other infection control High

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Infection control intervention simultaneous with antibiotic intervention. 14 months' pre‐ and 11 months' postintervention, so secular change unlikely.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: run chart with no statistical analysis.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

High risk

Pre‐intervention data were incomplete.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period. Criteria for sampling and testing were unchanged over the study period.

Free of other bias (ITS) ?

High risk

NOT DONE. Microbial Outcome Risk of Bias Criteria: Planned intervention: NOT DONE, unplanned intervention. Case definition: DONE, microbial outcome was colonisation by surveillance screening. Clinical infection was diagnosed by CDC definition but not used as an outcome. Infection or colonisation by case note review. Other infection control measures: NOT DONE, barrier precautions were instituted on colonised and infected patients at the same time that ceftazidime restriction was implemented.

Meyer 2007

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: physicians in the neurosurgical ICU
PARTICIPANTS: patients with pneumonia

CLINICAL PROBLEM: antibiotic treatment for pneumonia in neurosurgical ICU

SETTING: neurosurgical ICU in 1 hospital in Germany

Interventions

FORMAT: Interventions: educational meeting with neurosurgeons and dissemination of guideline
Intervention Functions: education

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive, in the new guideline the duration of antibiotic therapy for nosocomial pneumonia was reduced from 14 to 7 days, while for community‐acquired pneumonia the period fell from 10 to 5 days

Outcomes

PRESCRIBING: Exposure: total antibiotic use and cost/1000 OBD

FINANCIAL: changes in total antibiotic cost

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome from pharmacy database pre‐ and postintervention.

Knowledge of the allocation adequately prevented(ITS)?

Unclear risk

No mention of blinding

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome from pharmacy database pre‐ and postintervention.

Free of selected reporting (ITS) ?

Low risk

Outcome from pharmacy database pre‐ and postintervention.

Free of other bias (ITS) ?

Low risk

> 1 year of data pre‐ and postintervention

Meyer 2009

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all patients in an adult surgical ICU
PARTICIPANTS: all staff in the ICU
CLINICAL PROBLEM: use of 3rd‐generation cephalosporins for treatment and prophylaxis of specific infections plus duration of prophylaxis for fractures
SETTING: 1 surgical ICU in a teaching hospital in Germany

Interventions

FORMAT: Interventions: dissemination of guidelines and educational meetings in departments of surgery and anaesthesiology
Intervention Functions: education

DELIVERER: multidisciplinary AMT

COMPARISON: pre‐intervention outcomes

DESIRED CHANGE: reduction in use of cephalosporins and resistance in gram‐negative bacteria

Outcomes

PRESCRIBING: Choice: use of cephalosporins in DDD/1000 OBD

MICROBIAL: resistance to cephalosporins and piperacillin in gram‐negative bacteria isolated from clinical and surveillance cultures

Notes

FINANCIAL SUPPORT: Funding: Federal Ministry of Education and Research (01Kl 9907). Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Microbial ROB: HIGH Case definition Low; Planned intervention Low; Other infection control Unclear, no clear information about isolation or personal‐protection policies

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computers

Free of other bias (ITS) ?

Low risk

Data for > 2 years' pre‐ and postintervention, so secular trends accounted for.

Meyer 2010

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the ICU
PARTICIPANTS: all patients with clinical problem

CLINICAL PROBLEM: reducing length of antibiotic prophylaxis for cerebrospinal shunts

SETTING: ICU department in 1 teaching hospital in Germany

Interventions

FORMAT: Intervention: educational meeting and dissemination of new policy. In autumn 2003, a comprehensive teaching session on antibiotic prophylaxis in cerebrospinal shunts was organised by the infection control and neurosurgery teams. This resulted in a revised recommendation of single‐shot prophylaxis with cefuroxime for shunt catheters, beginning in January 2004. Prior to implementation of this recommendation, cefuroxime was administered for the whole duration of external cerebrospinal fluid drainage, which could be up to 2 to 3 weeks.

Intervention Functions: education, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive, shorten duration of prophylaxis

Outcomes

PRESCRIBING: Exposure: total antibiotic use in DDD/1000 OBD

Notes

FINANCIAL SUPPORT: Funding: Federal Ministry of Education and Research (01Kl 9907). Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

Says they could not control for changes over time and that an antimicrobial stewardship programme was implemented

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharamacy computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharamacy computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharamacy computers

Free of selected reporting (ITS) ?

Low risk

Data from pharamacy computers

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Micek 2004

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: ICU physicians

PATIENTS: 302 adults in the ICU (154 intervention, 148 control)

CLINICAL PROBLEM: VAP requiring antibiotics

SETTING: single ICU in a teaching hospital in the USA

Interventions

FORMAT: Interventions: educational outreach by review and recommend change
Intervention Functions: enablement, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Exposure: duration of all antibiotic therapy

Notes

FINANCIAL SUPPORT: Funding: part commercial, Barnes‐Jewish Hospital Foundation and an unrestricted grant from Elan Pharmaceuticals. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

"Patients were randomly assigned", but no details of how the sequence was generated

Allocation concealment (selection bias)

Unclear risk

Not stated

Blinding (performance bias and detection bias)
All outcomes

High risk

Not possible

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcome data were missing from 4 (2.6%) patients in the intervention group and 8 (5.4%) patients in the control group.

Selective reporting (reporting bias)

Low risk

Done, outcomes were obtained from routine data systems.

Other bias

High risk

The policy was only implemented at weekends or on holidays when 1 of the 2 investigators was available in the hospital.

Baseline Outcomes similar?

Unclear risk

No data about duration of therapy before the intervention

Free of contamination?

High risk

Physicians managing patients in the control group would have seen reminders for the intervention group.

Baseline characteristics similar?

Low risk

Table 1

Mittal 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the Department of Paediatrics
PARTICIPANTS: all children < 2 years old with bronchiolitis
CLINICAL PROBLEM: antibiotic use as part of a new Clinical Practice Guideline to improve management of bronchiolitis
SETTING: 1 university hospital in the USA

Interventions

FORMAT: Interventions: audit and feedback, educational meeting with dissemination of guideline; reminders (verbal (on rounds, so may have been circumstantial) and physical (pocket‐size guideline, screensavers))
Intervention Functions: education, enablement, persuasion
DELIVERER: departmental physicians (paediatrics and respiratory)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: % treated with antibiotics

CLINICAL: length of stay, re‐admission

Notes

FINANCIAL SUPPORT: Funding: no external. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Antibiotic use was 1 of 10 recommendations in the guideline; the other 9 would have impacted on clinical outcomes.

Analysed appropriately (ITS) ?

Low risk

Statistical process control charts

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

All outcome data from hospital patient administration system

Knowledge of the allocation adequately prevented(ITS)?

Low risk

All outcome data from hospital patient administration system

Incomplete outcome data addressed (ITS) ?

Low risk

All outcome data from hospital patient administration system

Free of selected reporting (ITS) ?

Low risk

All outcome data from hospital patient administration system

Free of other bias (ITS) ?

Low risk

Data collected over 3 winters, 1 pre‐ and 2 postintervention.

Mol 2005

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: physicians in the Department of Internal Medicine
PATIENTS: all patients in the wards

CLINICAL PROBLEM: receiving antibiotic therapy

SETTING: 1 university hospital in the Netherlands

Interventions

FORMAT: 1st Intervention: audit and feedback; educational meetings with dissemination of guideline
1st Intervention Functions: education, enablement
2nd Intervention: audit and feedback; educational meetings with dissemination of guideline; educational outreach by academic detailing

2nd Intervention Functions: education, enablement, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: % compliance with guideline; antibiotic cost

FINANCIAL: antibiotic cost

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Done in original paper: segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was increase in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Data collection method was same throughout study.

Knowledge of the allocation adequately prevented(ITS)?

High risk

Subjective outcome without blinded assessment

Incomplete outcome data addressed (ITS) ?

Unclear risk

Not stated whether compliance was assessed in all patients.

Free of selected reporting (ITS) ?

Unclear risk

Not stated whether compliance was assessed in all patients.

Free of other bias (ITS) ?

Low risk

The kappa value for the primary outcome measure was 0.71, which is below the level set by EPOC, but for the reasons given in the text we feel is adequate for assessment of compliance with an antibiotic guideline. Drug costs were adjusted to April 2001 prices.

Newland 2012

Methods

STUDY DESIGN: CITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: all patients in children's hospital
CLINICAL PROBLEM: inappropriate use of antimicrobials; a group of broad‐spectrum, or “select”, antibiotics 2 calendar days after they were initiated by the clinician
SETTING: 1 children's hospital in the USA (intervention) with data from 25 similar hospitals of the Child Health Corporation of America as control

Interventions

FORMAT: Interventions: educational outreach by review and recommend change.

NB the authors describe their intervention as "audit and feedback", but there was no feedback of data over time about progress to goal, just review with feedback about individual patients
Intervention Functions: enablement, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: total antibiotic use (days of therapy/1000 patient days)

Notes

FINANCIAL SUPPORT: Funding: Agency for Healtcare Quality and Reseach (grant U18‐HS10399). Competing Interests: none declared

ADDITIONAL DATA: authors provided additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

Unclear, there were some infection control initiatives running.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Yes, point of analysis is point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Yes, data collection was the same pre‐ and postintervention.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Yes, objective outcomes

Incomplete outcome data addressed (ITS) ?

Low risk

Routine data, so could assume complete.

Free of selected reporting (ITS) ?

Low risk

Yes, all relevant outcomes reported.

Free of other bias (ITS) ?

Low risk

Yes, all biases addressed.

Nobre 2008

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the ICU
PARTICIPANTS: 282 patients with suspected sepsis, 79 randomised (39 intervention, 40 control)
CLINICAL PROBLEM: duration of antibiotic treatment in patients with sepsis
SETTING: 1 ICU in 1 university hospital in Switzerland

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm with each PCT test); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring
DELIVERER: departmental physician (ICU)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, a total of at least 66 participants. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: duration of treatment in days

CLINICAL: Balancing: mortality, relapse of infection, length of ICU stay, length of hospital stay

Notes

FINANCIAL SUPPORT: Funding: commercial B.R.A.H.M.S AG (USD 50,000). Competing Interests: 2 authors received speaker honoraria from B.R.A.H.M.S AG.

ADDITIONAL DATA: online supplementary file with addtional infromation about stopping rules in PCT group. No response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

The randomisation was performed using a computer‐based random number generation.

Allocation concealment (selection bias)

Low risk

Allocation was issued using opaque, sealed, numbered envelopes.

Blinding (performance bias and detection bias)
All outcomes

High risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Selective reporting (reporting bias)

High risk

8/39 (20%) patients excluded from intervention versus 3/40 (7%) from control; 4 patients excluded from intervention for "complicated infections", which is likely to have biased the results on duration of antibiotic treatment.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

PCT only measured for intervention group.

Baseline characteristics similar?

Low risk

Table 1

Nuila 2008

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in hospital
PARTICIPANTS: all patients receiving antibiotics

CLINICAL PROBLEM: reduce cases of Clostridium difficile‐associated disease in hospital by restricting use of parenteral antibiotics

SETTING: 1 teaching hospital in the USA

Interventions

FORMAT: no valid prescribing data. Restriction and educational outreach ‐ review and recommend change

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

Outcomes

MICROBIAL: incidence of Clostridium difficile‐associated disease

Notes

FINANCIAL SUPPORT: Funding: Merit Review Funding and Department of Veterans Affairs. Competing Interests: none declared

ADDITIONAL DATA: email from authors but no additional data

Microbial ROB: MEDIUM: Case definition Low, Planned intervention Low, Other infection control High

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

MRSA control programme introduced simultaneously.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Routine data from microbiology computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine data from microbiology computer

Incomplete outcome data addressed (ITS) ?

Low risk

Routine data from microbiology computer

Free of selected reporting (ITS) ?

Low risk

Routine data from microbiology computer

Free of other bias (ITS) ?

High risk

Only 6 months' data postintervention

Microbial Outcome Risk of Bias Criteria: Case definition: DONE, CDC definition of C difficile. Planned intervention: DONE. Other infection control measures: NOT DONE, MRSA control programme introduced simultaneously.

Oliveira 2013

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians
PARTICIPANTS: 355 ICU patients assessed for inclusion, 94 patients randomised
CLINICAL PROBLEM: 94 patients with suspected sepsis randomised (49 intervention, 45 control)
SETTING: 1 university hospital ICU in Brazil

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm with each PCT test); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring
DELIVERER: specialist physician (Infectious Diseases)
COMPARISON: usual care, patients monitored with C‐reactive protein
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 58 participants per group. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: duration of treatment in days

CLINICAL: mortality, recurrence of infection, ICU length of stay, hospital length of stay, nosocomial infection

Notes

FINANCIAL SUPPORT: Funding: Minas Gerais Research Foundation (Fundação de Amparo à Pesquisa do Estado de Minas Gerais). Competing Interests: 1 author received payment for lectures from bioMérieux. No others declared.

ADDITIONAL DATA: online Microsoft Word document with additional information about the criteria for stopping antibiotics, no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Randomisation was performed using a table of computer‐generated random numbers.

Allocation concealment (selection bias)

Low risk

Sealed, opaque envelopes were used for the randomisation.

Blinding (performance bias and detection bias)
All outcomes

High risk

Not blinded

Incomplete outcome data (attrition bias)
All outcomes

Low risk

1 patient excluded from intervention and 2 from control. Outcomes measured on all other randomised participants.

Selective reporting (reporting bias)

Low risk

Duration of antibiotics measured from patient administration system.

Other bias

Unclear risk

"Patients showing reduction in SOFA and no sign of active infection were to receive no more than 7 days of antibiotic therapy. We used the

biomarker‐guided protocols to further reduce this duration (i.e., to less than seven days)". This suggests that the ID physicians imposed a ceiling of 7 days' treatment for these patients for both intervention and control groups.

Study did not achieve required recruitment.

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

PCT only measured for intervention group.

Baseline characteristics similar?

Low risk

Table 1

Oosterheert 2005

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: hospital physicians

PATIENTS: inpatients with LRTI, 107 randomised (55 intervention, 52 control)

CLINICAL PROBLEM: admitted to hospital for treatment of LRTI

SETTING: 2 Dutch hospitals

Interventions

FORMAT: Interventions: educational meetings; dissemination of written information about study procedures, test characteristics discussed and results from previous studies; structural, rapid laboratory testing (PCR) for viral and atypical bacterial pathogens
Intervention Functions: education, environmental restructuring

DELIVERER: specialist physician (Medical Microbiology)

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, a total of 100 patients. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: % patients treated

CLINICAL: mortality, median duration of antibiotic treatment

FINANCIAL: cost of hospitalisation, all diagnostic and treatment costs

Notes

FINANCIAL SUPPORT: Funding: Association of Academic Hospitals and the Dutch Health Insurance Council (grant 01233). Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"Patients were randomly allocated ... by means of a computer generated table"

Allocation concealment (selection bias)

High risk

Allocation by investigators

Blinding (performance bias and detection bias)
All outcomes

High risk

Investigators were not blinded to patient randomisation.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Reported on all 107 patients

Selective reporting (reporting bias)

Low risk

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

Test data only reported for intervention patients.

Baseline characteristics similar?

High risk

"slightly more patients in the intervention group had received previous antibiotic treatment ": 42% vs 23%, which is not "slighly more"

Ostrowsky 2014

Methods

STUDY DESIGN: CITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospitals
PARTICIPANTS: all patients in the hospitals
CLINICAL PROBLEM: reduce use of antibiotics considered high risk for Clostridium difficile infection
SETTING: 10 hospitals in the USA, 6 intervention and 4 control

Interventions

FORMAT: Interventions: educational meetings (6 hospitals), dissemination of algorithms (3 hospitals), educational outreach by review and recommend change (2 hospitals), restrictive automatic stop order (1 hospital), unspecified "hospital wide restriction" (3 hospitals).

NB the authors describe the intervention in 2 hospitals as "audit and feedback", but there was no feedback of data over time about progress to goal, just review with feedback about individual patients.

Intervention Functions: education, enablement, persuasion, restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive. Each intervention hospital did a case control study to identify high‐risk antibiotics; these were piperacillin tazobactam (6 hospitals), fluoroquinolones (5 hospitals), or cefepime (2 hospitals).

Outcomes

PRESCRIBING: Choice: use of target antibiotics in DDD/1000 OBD and in days of therapy

MICROBIAL: C difficile infection (cases per 10,000 OBD)

Notes

FINANCIAL SUPPORT: Funding: Agency for Healthcare Research and Quality; US Department of Health and Human Services. Competing Interests: none declared

ADDITIONAL DATA: email response from authors with additional data about the intervention used by each of the 6 intervention hospitals

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Outcome data from pharmacy and microbiology computers

Free of other bias (ITS) ?

High risk

Intervention targets and intervention design were different in each of the 6 hospitals. Microbial ROB MEDIUM: case definition low, planned intervention low, other infection control UNCLEAR

Ozkaya 2009

Methods

STUDY DESIGN: NRT

Risk of Bias: HIGH

Participants

PROVIDERS: all staff in the ED
PARTICIPANTS: all children with influenza‐like illness
CLINICAL PROBLEM: reduction in antibiotic prescribing for influenza
SETTING: 1 university hospital in Turkey

Interventions

FORMAT: Intervention: structural, rapid laboratory test for influenza

Intervention Function: environmental restructuring
DELIVERER: specialist physicians, Department of Paediatrics
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: % children prescribed antibiotics

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: email response from authors but no additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

Does not say how groups were allocated

Allocation concealment (selection bias)

Unclear risk

Says there was blinding but unclear who was blinded.

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

Says there was blinding but unclear who was blinded.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

All included

Selective reporting (reporting bias)

Low risk

Yes, all outcomes reported.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No baseline outcome data

Free of contamination?

High risk

Within same ward

Baseline characteristics similar?

Low risk

Yes, Table 1

Palmay 2014

Methods

STUDY DESIGN: cluster RCT, stepped wedge, service level

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in 6 hospital services
PARTICIPANTS: all patients in 6 hospital services, 6 clusters (services)
CLINICAL PROBLEM: use of targeted antibiotics (carbapenems (ertapenem, meropenem), piperacillin‐tazobactam, 3rd‐generation cephalosporins (ceftazidime, ceftriaxone), fluoroquinolones (ciprofloxacin, levofloxacin, moxifloxacin), and intravenous vancomycin)
SETTING: 1 university hospital in Canada, 6 services: Neurosurgery, Orthopaedics, Nephrology, General Internal Medicine, Cardiology, General Surgery/Trauma

Interventions

FORMAT: Interventions: educational outreach by review and recommend change; reminders (circumstantial, physical, written recommendation on each patient reviewed)

NB the authors describe their intervention as "audit and feedback", but there was no feedback of data over time about progress to goal, just review with feedback about individual patients.
Intervention Functions: enablement, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Choice: use of target antibiotics in days of therapy/1000 OBD

MICROBIAL: Clostridium difficile infection and infection with antibiotic‐resistant organisms

FINANCIAL: time required to implement the intervention in critical‐care wards is described in Elligson 2012a.

Notes

FINANCIAL SUPPORT: Funding: Ontario Ministry of Health and Canadian Institutes of Health Research. Competing Interests: none declared

ADDITIONAL DATA: email response with additional details about the intervention from authors including Elligson 2012a describing the design and cost of implementing the intervention in critical‐care wards

Microbial Risk of Bias: MEDIUM: case definition low, unplanned intervention low, other infection control UNCLEAR

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

The order of implementation of the intervention on the 6 clinical services was determined by random number generation performed by a statistician uninvolved in daily stewardship activities.

Allocation concealment (selection bias)

Low risk

Following a 6‐month control period during which none of the services received antimicrobial stewardship (1 May 2010 to 31 October 2011), the intervention was introduced to each additional service at 1‐month intervals, beginning on 1 November 2010. By 1 April 2011, clinical rollout was complete.

Blinding (performance bias and detection bias)
All outcomes

High risk

Blinding was not possible.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Prescribing outcome data were from pharmacy computer.

Selective reporting (reporting bias)

Low risk

Prescribing outcome data were from pharmacy computer.

Other bias

Low risk

Unit of analysis was service, and clustering was included in the model. "Negative binomial regression, accounting for clustering at the level of service using random effects as well as for secular and seasonal trends, was used to compare overall targeted antimicrobial utilization in the control and intervention periods for the analysis involving patients qualifying for the stewardship intervention as well as the analysis of all admitted patients. The unit of analysis was each service’s mean monthly targeted days of therapy count. The covariates included in these multivariable models were study period, study month (as a continuous variable), and season"

Baseline Outcomes similar?

Low risk

Table 4

Free of contamination?

High risk

Contamination could have occurred during the rollout of intervention over 6 months.

Baseline characteristics similar?

Low risk

Parienti 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving antibiotics in the hospital
CLINICAL PROBLEM: use of fluoroquinolones; the aim of the study was to assess the effect of removing restriction
SETTING: 1 university hospital in France

Interventions

FORMAT: no reliable prescribing data. The intervention was removal of restriction, but only 1 prescribing outcome data point during restriction and 3 after restriction lifted.
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

MICROBIAL: monthly MRSA rate (%)

Notes

FINANCIAL SUPPORT:Funding: Centre Hospitalier Universitaire de Caen and the French Health Ministry (Programme Hospitalier de Recherche Clinique National). Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

MRSA data from microbiology computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

MRSA data from microbiology computer

Incomplete outcome data addressed (ITS) ?

Low risk

MRSA data from microbiology computer

Free of selected reporting (ITS) ?

Low risk

MRSA data from microbiology computer

Free of other bias (ITS) ?

Low risk

MICROBIAL RISK OF BIAS: case defiinition Low, planned intervention Low, other infection control Low, use of alchohol‐based hand rub (ABHR) unchanged during period of fluoroquinolone restriction (2001‐2) and for 3 years after restriction lifted (2003‐5). Data are also presented for a further 6 years of increased use of ABHR (2006‐11).

Parikh 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all paediatric physicians in the hospitals
PARTICIPANTS: children aged 28 days to 2 years
CLINICAL PROBLEM: antibiotic use in children with a primary diagnosis of acute bronchiolitis
SETTING: 41 hospitals in the USA

Interventions

FORMAT: Intervention: publication of American Academy of Pediatricians (AAP) bronchiolitis guidelines

Intervention Functions: education but no information about how the guidelines were disseminated
DELIVERER: departmental physicians (Pediatrics)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: % children treated with antibiotics

Notes

FINANCIAL SUPPORT: Funding: Academic Pediatric Association. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data. AAP 2006 Bronchiolitis Guidelines downloaded.

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from patient administration systems

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from patient administration systems

Incomplete outcome data addressed (ITS) ?

Low risk

Data from patient administration systems

Free of selected reporting (ITS) ?

Low risk

Data from patient administration systems

Free of other bias (ITS) ?

Low risk

Monthly data points for 20 months' pre‐ and 60 months' postintervention. "Guideline published in October 2006. Study phases: preguideline (November 2004 to March 2005), postguideline early (November 2007 to March 2008), and postguideline late (November 2011 to March 2012). These time periods were selected for the unadjusted analysis because they represent 3 bronchiolitis seasons, before and after guideline publication; the 2006 to 2007 season was not included because this is the year the guideline was published and was a period of distribution and assimilation. For the adjusted segmented regression analysis, publication of the guidelines, October 2006, was considered the event point."

Patel 1989

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients requiring antibiotic treatment
SETTING: single hospital in the UK

Interventions

FORMAT: Interventions: educational meetings with dissemination of guidelines; educational outreach by review and recommend change; reminders (physical and verbal, posters and intervention promoted at weekly ward meetings)
Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: pharmacist
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: expenditure on oral co‐amoxiclav

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Only 5 months' pre‐intervention data, so secular changes possible.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Paul 2006

Methods

STUDY DESIGN: cluster RCT, service level

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PATIENTS: all patients in the 3 hospitals (intervention 8 wards with 1245 patients, 297 with microbiologically documented infections; control 7 wards with 1081 patients, 273 with microbiologically documented infections), 15 clusters (wards)

CLINICAL PROBLEM: antibiotic prescribing

SETTING: 3 hospitals in 3 countries: Israel, Germany, and Italy

Interventions

FORMAT: Intervention: reminders (circumstantial, triggered by prescription of antibiotics); structural, computer decision support system

Intervention Functions: education, enablement, environmental restructuring, persuasion

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 1500 patients with microbiologically documented infections. Details in Appendix 3

Outcomes

PRESCRIBING: Choice: appropriate antibiotic treatments

COST: Costs, which included the estimated ecological cost of inappropriate antibiotic treatment

CLINICAL: Balancing: length of stay, 30‐day mortality

Notes

FINANCIAL SUPPORT: Funding: EU Fifth Framework, Information Society Technologies, IST‐9999‐11459. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"Wards were randomly allocated ... by drawing a random code from a closed opaque box"

Allocation concealment (selection bias)

High risk

Allocation could not be concealed.

Blinding (performance bias and detection bias)
All outcomes

Low risk

Primary outcome was measured by the CDSS.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all patients.

Selective reporting (reporting bias)

Low risk

The primary outcome was objective, based on whether or not the prescriber selected one of the CDSS top 3 recommendations.

Other bias

High risk

Trial was underpowered for the primary outcome measure.

Adjustment of drug costs for changes in prices not necessary because the intervention lasted only 6 months.

Baseline Outcomes similar?

Low risk

Table 1, cohort study before trial

Free of contamination?

Low risk

Only intervention wards had CDSS.

Baseline characteristics similar?

Low risk

Pear 1994

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients requiring antibiotic treatment
SETTING: single university hospital in the USA

Interventions

FORMAT: restrictive, no valid prescribing data

DELIVERER: specialist physician
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

MICROBIAL: cases of CDAD per month (ITS data). Prevalence of clindamycin‐resistant Clostridium difficile

Notes

FINANCIAL SUPPORT: none

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Enough data to account for seasonal variation, and infection control measures did not change over study period.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: run chart with no statistical analysis.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

High risk

Not done, the method of detection of C difficile toxin changed from cell culture assay in the first 4 years of the study to a latex test in the final year (5 months after the start of clindamycin restriction).

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

High risk

Not done, change in method of testing for C difficile during the study period (see case definition).

Free of other bias (ITS) ?

High risk

Microbial Outcome Risk of Bias Criteria: Case definition: NOT DONE Infection: diarrhoea with positive assay for C difficile cytotoxin and antibiotic therapy within the previous 60 days. However, the method of detection of toxin changed from cell culture assay in the first 4 years of the study to a latex test in the final year (5 months after the start of clindamycin restriction). Planned intervention: NOT DONE Response to an outbreak of CDAD starting 12 months before restriction. Other infection control, isolation, and IC practices: DONE Infection control measures were identical in the year before and after the start of clindamycin restriction. Hospital staff education and increased availability of gloves and improvement of environmental hygiene were implemented a year before restriction of clindamycin with no apparent impact on the frequency of new cases.

Perez 2003

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: physicians, surgeons, paediatricians, obstetricians‐gynaecologists, and intensivists
PARTICIPANTS: adults and children with normal renal function
CLINICAL PROBLEM: inappropriate prescribing of antibiotics (specifically in relation to intervals between doses of aminoglycosides and 1st‐ and 3rd‐generation cephalosporins for Intervention 1 and timing of surgical prophylaxis for Intervention 2)
SETTING: university hospital in Colombia

Interventions

FORMAT: Interventions:Intervention 1: reminders (posters, not circumstantial); educational meetings and dissemination of guidelines; restrictive by expert approval. Intervention 2: reminder (circumstantial, on blood pressure cuffs in operating theatre); educational meetings and dissemination of guidelines

Intervention Functions:Intervention 1: education, environmental restructuring, persuasion. Intervention 2: education, enablement, environmental restructuring, persuasion

DELIVERER: pharmacists
COMPARISON: usual care
DESIRED CHANGE: Intervention 1: increase effective; Intervention 2: decrease excessive

Outcomes

PRESCRIBING: Choice: reduction in incidence of incorrect antibiotic prescriptions (dosing intervals and timing of surgical prophylaxis).

Notes

FINANCIAL SUPPORT: Funding: International Clinical Epidemiology Network (INCLEN, grant #1004‐97‐6501) and by Pontificia Universidad Javeriana (grant #12‐24‐01‐ 31). Competing Interests: no information

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Analysed appropriately (ITS) ?

Low risk

Done in original paper: ARIMA analysis, selected in preference to segmented regression analysis because of nonlinear outcome data.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Peto 2008

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the surgical ICU
PARTICIPANTS: adult patients in surgical ICU (excluding general surgical and medical)

CLINICAL PROBLEM: excessive antibiotic use

SETTING: surgical ICU in a university hospital in Hungary

Interventions

FORMAT: Interventions: educational outreach by review and recommend change; restrictive by expert approval
Intervention Functions: enablement, persuasion, restriction

DELIVERER: specialist physician

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: total antibiotic consumption (DDD per 100 patient days)

Notes

FINANCIAL SUPPORT: no information

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Routine data from pharmacy

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Routine data from pharmacy

Incomplete outcome data addressed (ITS) ?

Low risk

Routine data from pharmacy

Free of selected reporting (ITS) ?

Low risk

Routine data from pharmacy

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Petrikkos 2007

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients requiring antibiotics
CLINICAL PROBLEM: decrease use of cephalosporins
SETTING: 1 university hospital in Greece

Interventions

FORMAT: Intervention: restrictive by expert approval

Intervention Function: restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of cephalosporins in DDD/100 OBD

MICROBIAL: % ESBL‐producing Klebsiella pneumoniae and Escherichia coli

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: HIGH case definition Low, planned intervention Low, other infection control Unclear, no data about other infection control measures

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of other bias (ITS) ?

Unclear risk

1 year (6 x 2‐monthly time points) pre‐ and postintervention

Pires 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all prescribers in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients receiving carbapenems
SETTING: 1 teaching hospital in Brazil

Interventions

FORMAT: Intervention: restriction by removal from availability in the hospital

Intervention Function: restriction

DELIVERER: Infection Control Committee

COMPARISON: pre‐intervention

DESIRED CHANGE: reduction in use of targeted carbapenems and in resistance

Outcomes

PRESCRIBING: Choice: use of target antibiotics

MICROBIAL: carbapenem resistance in Pseudomonas aeruginosa

Notes

FINANCIAL SUPPORT: Funding: Fundo de Incentivo a Pesquisa e Eventos, Hospital de Clinicas de Port Alegre. Competing Interests: none declared

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

No outbreak or other changes coincident with intervention

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of other bias (ITS) ?

Low risk

Data for 18 months' pre‐ and 3 years' postintervention

Po 2012

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital

CLINICAL PROBLEM: reduce linezolid use

SETTING: 1 hospital in the USA

Interventions

FORMAT: Interventions:Intervention 1: educational mettings or dissemination of educational materials. Intervention 2: reminders, structural, circumstantial ‐ computerised physician order entry system (CPOE) and educational meetings or dissemination of educational materials

Intervention Functions:Intervention 1: education. Intervention 2: education, enablement, environmental restructuring

DELIVERER: specialist physician

COMPARISON: usual care

DESIRED CHANGE: reduce inappropriate

Outcomes

PRESCRIBING: Choice: linezolid use (DDD per 1000 patient days)

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Yes, reports on all likely influencing interventions.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Yes, the point of analysis is the point of the intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Yes, pharmacy data used both pre‐ and postintervention.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome is objective.

Incomplete outcome data addressed (ITS) ?

Low risk

Yes, pharmacy data, so should be complete.

Free of selected reporting (ITS) ?

Low risk

Yes, all outcomes reported.

Free of other bias (ITS) ?

High risk

< 1 year data for phases 1 and 2

Poehling 2006

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: doctors in the ED
PARTICIPANTS: children with influenza‐like illness
CLINICAL PROBLEM: decrease antibiotic prescribing for influenza
SETTING: 1 university hospital in the USA

Interventions

FORMAT: Interventions: structural, rapid influenza testing
Intervention Functions: environmental restructuring

DELIVERER: specialist physicians, Department of Pediatrics

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: % children treated

Notes

FINANCIAL SUPPORT: Funding: New Vaccine Surveillance Network and Robert Wood Johnson Generalist Physicians Faculty Scholars Program. Competing Interests: none declared

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Random number generator

Allocation concealment (selection bias)

Unclear risk

Does not say, but possibly not due to nature of study

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

No information

Incomplete outcome data (attrition bias)
All outcomes

Low risk

From records, outcomes on all included children

Selective reporting (reporting bias)

Low risk

From records, outcomes on all included children

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No baseline outcomes taken.

Free of contamination?

Low risk

Influenza testing only on children in intervention group

Baseline characteristics similar?

Low risk

Table 1

Popovski 2015

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients with intra‐abdominal infections
CLINICAL PROBLEM: decrease use of ciprofloxacin for empirical treatment
SETTING: 1 university hospital in Canada

Interventions

FORMAT: Interventions: educational meetings with dissemination of guidelines; reminders (physical, posters, and on intranet)
Intervention Functions: education, environmental restructuring
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of ciprofloxacin in DDD/1000 OBD

CLINICAL: mortality, re‐admission (cohort data)

Notes

FINANCIAL SUPPORT: Funding: commercial Merck, Pfizer, Astellas, and the Medbuy Corporation. Hamilton Health Sciences Foundation (Jack Hirsh Fellowship). Competing Interests: 1 author received honoraria from Merck and Astellas for lectures. All other authors: none to declare

ADDITIONAL DATA: email response from authors with guideline and additional data about the intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Outcome data from pharmacy computer

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Price 2010

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: requiring antibiotic treatment or prophylaxis
SETTING: 1 university hospital in the UK

Interventions

FORMAT: Interventions: dissemination of guidelines; restrictive by removal and expert approval
Intervention Functions: education, restriction

Note that the published paper says: "The policy was widely disseminated in the hospital but no specific measures were put in place to enforce compliance". However, the antibiotic policy provided by the authors says: “Cephalosporins and fluoroquinolones. These agents will NOT be ward stock on any general medical or surgical wards – continuation of therapy beyond 24 hours (in Medicine) and single dose prophylaxis (in Surgery) requires consultant review, prescription by consultant and discussion with Micro ID”.

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of cephalosporins and quinolones (combined) in DDD/1000 OBD

MICROBIAL: Clostridium difficile infection

Notes

FINANCIAL SUPPORT: Funding: part commercial, Optimer Pharmaceuticals and US Department of Veterans Affairs. Competing Interests: 1 author declared multiple commercial sources of research funding and held patents relevant to C difficile infection licensed to ViroPharma

ADDITIONAL INFORMATION: authors provided the 2008 version of the hospital antibiotic policy, which included details about the restrictions on use of target drugs

Microbial Risk of Bias MEDIUM: case definition yes, planned intervention yes, infection control no (a cohorting ward was introduced at the same time as the antibiotic policy)

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

For prescrbiing outcome

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Pharmacy computer

Free of other bias (ITS) ?

High risk

1 year data pre‐ and postintervention
Microbial Risk of Bias: cohorting introduced at the same time as prescribing intervention.

Pulcini 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the Medical ICU
PARTICIPANTS: all patients in the ICU
CLINICAL PROBLEM: receiving antibiotics for 24 h to 96 h
SETTING: 1 university hospital in France

Interventions

FORMAT: Interventions: audit and feedback; educational outreach by academic detailing; reminders (physical, circumstantial, stickers placed in notes of patients receiving target antibiotics)
Intervention Functions: enablement, environmental restructuring, persuasion

DELIVERER: departmental physician (ICU consultant)

COMPARISON: usual care

DESIRED CHANGE: increase appropriate

Outcomes

PRESCRIBING: Choice: % appropriate treatment

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL INFORMATION: email from authors with additional information about intervention. The intervention design is described in more detail in Pulcini 2008.

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Unlikely to affect data collection (ITS) ?

Low risk

Primary outcome was appropriateness of treatment at 24 to 96 hours, which was the same in pre‐ and postintervention period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Dual data entry, the ICU consultant was blinded to study period, although the ID physician was not.

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data on all participants

Free of selected reporting (ITS) ?

Low risk

No evidence of selective reporting

Free of other bias (ITS) ?

High risk

< 1 year of data (25 weeks) in the pre‐ and postintervention phases

Qu 2012

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the ICU
PARTICIPANTS: 71 patients with with confirmed severe acute pancreatitis

CLINICAL PROBLEM: PCT for guiding duration of antibiotic therapy

SETTING: 1 hospital in China

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm with each PCT test); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring

DELIVERER: department physician (ICU)

COMPARISON: usual care

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: duration of all antibiotic treatment

CLINICAL: Balancing: mortality and length of stay

FINANCIAL: cost of hospitalisation, but no information about cost of intervention

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

Says it was randomised, but no further information

Allocation concealment (selection bias)

Unclear risk

No information

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

No mention of blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes on all 71 participants

Selective reporting (reporting bias)

Low risk

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No information

Free of contamination?

Low risk

PCT results only reported for intervention participants.

Baseline characteristics similar?

Low risk

Yes, Table 1

Rattanaumpawan 2010

Methods

STUDY DESIGN: NRT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 953 hospitalised adults (1028 prescriptions)

CLINICAL PROBLEM: receiving treatment with piperacillin/tazobactam, imipenem, and meropenem

SETTING: 1 hospital in Thailand

Interventions

FORMAT: Interventions: educational outreach by review and recommend change
Intervention Functions: education, enablement, persuasion, restriction

DELIVERER: AMT

COMPARISON: usual care

DESIRED CHANGE: reduce excessive

Outcomes

PRESCRIBING: Choice: use of target antibiotics

CLINICAL: Balancing: mortality, length of stay

FINANCIAL: cost of target antibiotics and all antibiotics. No information about cost of intervention

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: email from authors but no additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

By hospital number, even number in last digit received intervention

Allocation concealment (selection bias)

High risk

Not concealed

Blinding (performance bias and detection bias)
All outcomes

High risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Complete data reported.

Selective reporting (reporting bias)

High risk

Some outcomes (favourable clinical outcome, death from infection) subject to selective outcome reporting. No discussion of why there was a significant difference for death because of infection but no difference in the % of patients alive on discharge from hospital.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

Baseline frequency of inappropriate treatment was 50% in January 2007, but no information about risk of inappropriate treatment in the control group in August 2007.

Free of contamination?

High risk

Invervention and control participants were in the same hospital, and physicians were likely to have patients in both groups.

Baseline characteristics similar?

Low risk

Table 1

Rattanaumpawan 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: adult patients receiving antibiotics

CLINICAL PROBLEM: unnecessary double coverage for infection with anaerobic bacteria

SETTING: 1 hospital in Thailand

Interventions

FORMAT: Interventions: restrictive by prior approval, the intervention was removal of this restriction
Intervention Functions: restriction
DELIVERER: AMT
COMPARISON: unnecessary treatment before and after removal of the restriction
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: cumulative incidence of unnecessary treatment in DDD/admission

Notes

FINANCIAL SUPPORT: Funding: National Institutes of Health grant K24‐AI080942. Competing Interests: 1 author received research support from Merck, Ortho‐McNeil, Cubist, and AstraZeneca.

ADDITIONAL DATA: email response from authors but no additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

1 year of data pre‐ and postintervention

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

High risk

Primary outcome (unnecessary DACT) not objective.

Knowledge of the allocation adequately prevented(ITS)?

High risk

Primary outcome (unnecessary DACT) not objective.

Incomplete outcome data addressed (ITS) ?

High risk

Figure 1 includes 4 months with no unnecessary DACT, but it is not clear whether this was because there was no DACT or because all DACT was necessary. With the exception of July 2008, these months had relatively high use of ampicillin/sulbactam and metronidazole, so suggests they missed some DACT patients.

Free of selected reporting (ITS) ?

Unclear risk

Not clear if outcome was reported on all patients.

Free of other bias (ITS) ?

Low risk

Richards 2003

Methods

STUDY DESIGN:  ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients except ICU, ER, ID
CLINICAL PROBLEM: receiving treatment with target antibiotics
SETTING: 1 university hospital in Australia

Interventions

FORMAT: Interventions: audit and feedback; educational meetings with dissemination of guidelines; reminders (circumstantial and physical, on computer order form when prescribing antibiotics); restrictive by compulsory order form, expert approval, and removal
Intervention Functions: education, enablement, environmental restructuring, persuasion, restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: reduction in established management (reduction in use of target drugs)

Outcomes

PRESCRIBING: Choice: Primary: use of cefotaxime or ceftriaxone

Secondary: use of other antibiotics: gentamicin, benzyl penicillin, carbapenems, piperacillin, ticarcillin, and ciprofloxacin

FINANCIAL: cost of intervention

Notes

FINANCIAL SUPPORT: Funding: Royal Melbourne Hospital. Competing Interests: none declared.

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

8 months data pre‐intervention, 15 months postintervention, not enough to adjust for seasonal variation

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after) with Kruskal‐Wallis test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Richardson 2000

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital. Number, age, and time since qualification NOT CLEAR. 3 intensive care units, 3 general medical, and 1 general surgical
PARTICIPANTS: a total of 618 episodes of vancomycin use (220 pre‐ and 398 postintervention). Number of patients, age, gender, and ethnicity NOT CLEAR.
CLINICAL PROBLEM: patients requiring antibiotic treatment
SETTING: single tertiary‐care teaching hospital in the USA with 150 acute care and 90 long‐term care beds

Interventions

FORMAT: Interventions: educational outreach by review and recommend change
Intervention Functions: enablement, persuasion
COMPARISON: data for 3 months in the previous year (April, August, and January)
DESIRED CHANGE: decrease excessive (reduction in inappropriate use of vancomycin with the aim of reducing prevalence of VRE infections)

Outcomes

PRESCRIBING: Choice: % episodes of vancomycin use deemed inappropriate

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Data only collected for 3 months pre‐ and 6 months postintervention, so secular/seasonal changes possible.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Unclear risk

The reliability of the assessment of appropriate vancomycin use was not reported.

Knowledge of the allocation adequately prevented(ITS)?

High risk

Retrospective assessment of appropriateness without concealment of study phase.

Incomplete outcome data addressed (ITS) ?

High risk

Assessment of appropriateness from retrospective assessment of all patients treated in 1 month but only done every 4 to 6 months.

Free of selected reporting (ITS) ?

Unclear risk

Not clear, data were only collected intermittently.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Ross 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all paediatricians in the hospitals
PARTICIPANTS: children with community‐acquired pneumonia
CLINICAL PROBLEM: increase use of guideline‐recommended antibiotics
SETTING: 38 hospitals in the USA

Interventions

FORMAT: Intervention: dissemination of national guidelines

Intervention Function: education
DELIVERER: specialist physicians
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: % patients treated with guideline‐recommended antibiotics

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: 1 author has received research funding from Merck and Cubist and has served as a consultant for Merck, Pfizer, Astellas Pharma, and Cubist, and 3 authors have received research funding from Pfizer.

ADDITIONAL DATA: email from authors with no additional data. Paediatric infectious diseases guidelines available online (cid.oxfordjournals.org/content/early/2011/08/30/cid.cir531.full)

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from Pediatric Health Information System

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from Pediatric Health Information System

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from Pediatric Health Information System

Free of selected reporting (ITS) ?

Low risk

Outcome data from Pediatric Health Information System

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Saizy‐Callaert 2003

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients requiring antibiotic treatment
SETTING: single 600‐bed university hospital in France

Interventions

FORMAT: Interventions: educational meetings and dissemination of protocol; reminders (physical, pocket‐size guideline); restrictive by compulsory order form and expert approval
Intervention Functions: education, environmental restructuring, restriction

COMPARISON: data for 3 years after implementation of the programme
DESIRED CHANGE: reduce excessive

Outcomes

PRESCRIBING: Choice: anti‐infective expenditure per hospital patient

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

4 years' data pre‐ and 3 years' data postintervention, so enough data to account for seasonal change

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after) with Fisher's exact test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

High risk

There is no information about change in price of antibiotics over the study period.

Free of selected reporting (ITS) ?

Unclear risk

The intervention was targeted at specific antibiotics, but no information is provided about their use or cost.

Free of other bias (ITS) ?

Unclear risk

No adjustment of antibiotic costs for change in price, so change in price of antibiotics (rather than change in use) over the study period may have been responsible for reduction in cost per patient over the study period. No data about number of admissions pre‐intervention.

Salama 1996

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: requiring antibiotic therapy
SETTING: 1 university hospital in Canada

Interventions

FORMAT: Interventions: audit and feedback; educational meetings with dissemination of guidelines; educational outreach by academic detailing; reminders (circumstantial, physical, and verbal: newsletters, posters, pocket charts, educational rounds, and triggered by prescribing of target drugs); reminders (physical); restrictive by compulsory order form plus automatic 3‐day stop order for all antibiotics and review and make change (therapeutic substitution of selected drugs)
Intervention Functions: education, enablement, environmental restructuring, persuasion, restriction
DESIRED CHANGE: reduction in vancomycin and ceftazidime use

Outcomes

PRESCRIBING: Choice: vancomycin and ceftazidime use in units, antibiotic cost as a percentage of total drug cost

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

> 12 months' data pre‐ and postintervention, enough to account for seasonal change

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Schnoor 2010

Methods

STUDY DESIGN: cluster RCT, hospital level

Risk of Bias: HIGH

Participants

PROVIDERS: doctors managing patients with community‐acquired pneumonia
PARTICIPANTS: 623 patients with community‐acquired pneumonia (275 intervention, 348 control), 8 clusters (hospitals)
CLINICAL PROBLEM: community‐acquired pneumonia
SETTING: 8 hospitals in Germany

Interventions

FORMAT: Interventions: audit and feedback; educational meetings with dissemination of guideline; reminders (physical, posters, electronic and pocket versions of guideline)
Intervention Functions: education, enablement, environmental restructuring

DESIRED CHANGE: increase in compliance of initial treatment with guideline recommendation and decrease in duration of treatment

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Choice: % guideline compliant for initial treatment

CLINICAL: Balancing: mortality, length of stay

Notes

FINANCIAL SUPPORT: Funding: German Medical Assembly grant 06‐69 and German Federal Ministry of Education and Research grant 01K10103‐105. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Computer, by hospital

Allocation concealment (selection bias)

Low risk

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

Not clear who collected outcome data or whether they were blinded to allocation

Incomplete outcome data (attrition bias)
All outcomes

Unclear risk

All outcome data given as %, so unclear if some patients were missing.

Selective reporting (reporting bias)

Unclear risk

No details of data collection

Other bias

High risk

Intervention period (1 April 2007 to 29 February 2008) was different than control period (1 September 2006 to 28 February 2007).

Baseline Outcomes similar?

High risk

Duration of inpatient antibiotic at baseline was appropriate in only 47% intervention (versus 57% control).

Free of contamination?

Low risk

Randomised by site

Baseline characteristics similar?

High risk

75% inpatients in control group versus 50% for intervention, also fewer CURB 0 and more CURB 3

Schouten 2007

Methods

STUDY DESIGN: cluster RCT, hospital level

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians
PARTICIPANTS: 827 patients with lower respiratory tract infection (before intervention, 212 intervention, 166 control; after intervention, 276 intervention, 166 control). 6 clusters (hospitals)
CLINICAL PROBLEM: patients with lower respiratory tract infection
SETTING: 6 hospitals in the Netherlands

Interventions

FORMAT: Interventions: audit and feedback; educational meetings with dissemination of guideline; educational outreach by academic detailing; reminders (physical, desktop on computers, and pocket card)
Intervention Functions: education, enablement, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive (choice and streamlining) and increase effective (timeliness)

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Choice: % patients compliant with guideline for selected drug, timing (within 4 h of presentation), switching from IV to oral and streamlining

CLINICAL: Balancing: mortality, length of stay

Notes

FINANCIAL SUPPORT: Funding: The Netherlands Organisation for Health Research and Development (Zon/Mw; 2300.0024). Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Blinded researcher coin flip, hospital level

Allocation concealment (selection bias)

Low risk

Allocation at hospital level

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

No information

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcome data for all patients

Selective reporting (reporting bias)

Unclear risk

All relevant outcomes reported.

Other bias

Low risk

Baseline Outcomes similar?

Low risk

Table 3, also pair‐matched clusters for important variables

Free of contamination?

Low risk

Allocation at hospital level

Baseline characteristics similar?

Low risk

No clinically relevant differences

Schroeder 2009

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the ICU
PARTICIPANTS: all patients with sepsis in the ICU
CLINICAL PROBLEM: receiving antibiotics for suspected intra‐abdominal sepsis
SETTING: 1 university hospital in Germany

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm with each PCT test); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring
DELIVERER: departmental physicians
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Exposure: duration of antibiotic treatment (days)

CLINICAL: Balancing: length of hospital stay

Notes

FINANCIAL SUPPORT: Funding: none declared. Competing Interests: 1 author had speaking engagements for B.R.A.H.M.S AG.

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

No information

Allocation concealment (selection bias)

Unclear risk

No information

Blinding (performance bias and detection bias)
All outcomes

High risk

Not blinded

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all patients.

Selective reporting (reporting bias)

Low risk

Outcomes reported on all patients.

Other bias

High risk

Only 27 of 125 screened patients were randomised.

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

PCT only measured for intervention patients.

Baseline characteristics similar?

Low risk

Table 1

Schuetz 2009

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians
PARTICIPANTS: 1381 patients with lower respiratory tract infection randomised (687 intervention, 694 control), 6 clusters (hospitals)
CLINICAL PROBLEM: lower respiratory tract infection
SETTING: 6 hospitals in Switzerland

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm with each PCT test); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring
DELIVERER: departmental physician (respiratory)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 1002 participants total. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: % patients treated

Notes

FINANCIAL SUPPORT: Funding: grant SNF 3200BO‐116177/1 from the Swiss National Science Foundation and contributions from santésuisse and the Gottfried und Julia Bangerter‐Rhyner Foundation and participating hospitals. B.R.A.H.M.S Inc, the major manufacturer of the procalcitonin assay, provided all assay‐related material, Kryptor machines if not already available on site, and kits and maintenance required for 10,000 measurements related to the study.

Competing Interests: 3 authors received support from B.R.A.H.M.S Inc to attend meetings and fulfil speaking engagements, and 1 author served as a consultant and received research support from B.R.A.H.M.S Inc.

ADDITIONAL DATA: authors provided additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Prespecified, computer‐generated randomisation list

Allocation concealment (selection bias)

Low risk

Centralised, password‐protected website

Blinding (performance bias and detection bias)
All outcomes

Low risk

Password‐protected website with instructions for PCT and control groups

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Only 1 of 1381 patients lost to follow‐up; 16 (2%) patients in PCT group and 6 (1%) patients in control group withdrew.

Selective reporting (reporting bias)

Low risk

> 95% surviving patients completed 30‐day interview.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No baseline outcome data

Free of contamination?

High risk

The study was conducted in 6 hospitals, but patients in each hospital were in both intervention and control groups.

Baseline characteristics similar?

Low risk

Table 1

Schwann 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians
PARTICIPANTS: all patients undergoing elective surgery requiring antibiotic prophylaxis
CLINICAL PROBLEM: timing of first dose of antibiotic
SETTING: 1 hospital network in the USA

Interventions

FORMAT: Interventions: reminders (circumstantial and physical, point‐of care electronic prompt (triggered by operating room admission)); reminders (physical); restrictive; structural
Intervention Functions: enablement, environmental restructuring
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: % patients with first dose administered within 1 hour of incision

CLINICAL: Intended: surgical‐site infection

Notes

FINANCIAL SUPPORT: Funding: Lehigh Valley Hospital Network and Allentown Anesthesia Associates. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Statistical process control charts

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Electronic data for prescribing

Knowledge of the allocation adequately prevented(ITS)?

Unclear risk

Infection control personnel were blinded for assessment of wound infection, unsure about compliance data.

Incomplete outcome data addressed (ITS) ?

Low risk

Electronic data for prescribing

Free of selected reporting (ITS) ?

Low risk

Electronic data for prescribing

Free of other bias (ITS) ?

Low risk

1 year data pre‐ and postintervention

Schwartz 2007

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the long‐term care facility
PARTICIPANTS: all patients receiving antibiotics
CLINICAL PROBLEM: patients receiving antimicrobials
SETTING: 1 hospital

Interventions

FORMAT: Interventions: educational meetings with dissemination of guidelines and treatment algorithms; reminders (physical, pocket guidelines)

The guideline has 16 algorithms for management of clinical problems (fever, leukocytosis, confusion, diarrhoea) and common infections in older people.
Intervention Functions: education, environmental restructuring
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: antibiotic days/100 OBD

Notes

FINANCIAL SUPPORT: Funding: Chicago Antimicrobial Resistance Project, Centers for Disease Control and Prevention (U50/ CCU515853). Competing Interests: no information

ADDITIONAL DATA: email response with the guideline. The guidelines are supposed to be available online, but the link does not work.

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Days of antimicrobial use calculated automatically by pharmacy computer.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Days of antimicrobial use calculated automatically by pharmacy computer.

Incomplete outcome data addressed (ITS) ?

Unclear risk

1 and 2 January 2000 start data were censored, but this was reported and would have little impact on the other 48 data points.

Free of selected reporting (ITS) ?

Unclear risk

Days of antimicrobial use calculated automatically by pharmacy computer.

Free of other bias (ITS) ?

High risk

Only 10 months' pre‐intervention data, so secular trends could not be addressed.

Senn 2004

Methods

STUDY DESIGN: RCT

Risk of bias: MEDIUM

Participants

PROVIDERS: residents on medical and surgical wards
PATIENTS: 251 patients were recruited, 126 intervention and 125 control

CLINICAL PROBLEM: adult patients receiving IV antibiotics for 3 to 4 days with no modification since starting treatment

SETTING: single 800‐bed university hospital in Switzerland. Data collected over 5 months.

POWER CALCULATION: yes, 135 patients in each group, but the trial was underpowered because the observed effect was lower than predicted. Details in Appendix 3

Interventions

FORMAT: Interventions: dissemination of questionnaire about guidelines; reminders (circumstantial and physical, questionnaire mailed to the resident in charge of patients who were receiving IV antibiotic treatment. The questionnaire asked 3 questions regarding possible adaptation of antibiotic therapy on day 3 or 4, and was collected 24 hours later. If the resident had not yet completed it at that time, he/she was reminded once to do so.)
Intervention Functions: education, enablement, environmental restructuring

DELIVERER: AMT

COMPARISON: control patients with no intervention

DESIRED CHANGE: reduction in established management (reduction in duration of IV therapy)

TIMING: intervention at the point of decision making (potential modification 3 to 4 days after start of antibiotics)

Outcomes

PRESCRIBING: Choice: % of patients discontinuing IV antibiotics and hazard ratio adjusted for patients' Karnofsky functional index

Notes

FINANCIAL SUPPORT: Funding: Quality Improvement Committee of the Lausanne University Hospital and grant 32–63128.00 of the Swiss National Science Foundation. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"Patients allocated ... by using a computer generated randomizations list"

Allocation concealment (selection bias)

Low risk

"Concealment of allocation was achieved as the physician in charge of the patient was involved after randomizations"

Blinding (performance bias and detection bias)
All outcomes

High risk

"This was a randomised, controlled, open trial"

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Primary outcome measure (duration of IV antibiotics) collected on all patients. Only 70% of questionnaires returned for the intervention group, which could account for the intervention effect being lower than expected. However, this did not affect outcome assessment.

Selective reporting (reporting bias)

Low risk

Complete primary outcome data

Other bias

High risk

The study was underpowered.

Baseline Outcomes similar?

Low risk

Pre‐study group, data collected for 2 months before intervention to estimate the magnitude of possible observation bias (Figure 2).

Free of contamination?

Low risk

The pre‐intervention group data were comparable to the control group, suggesting minimal observation bias.

Baseline characteristics similar?

Low risk

Presented in Table 1

Shehabi 2014

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the ICU
PARTICIPANTS: 400 patients; 6 withdrew consent, leaving 196 in the intervention and 198 in the control group
CLINICAL PROBLEM: patients with suspected sepsis and likely to receive antibiotics/remain in the ICU for at least 24 h
SETTING: 11 university hospitals in Australia

Interventions

Interventions: reminders (circumstantial, decision support algorithm with each PCT test); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring

DELIVERER: departmental physicians (ICU)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, 165 participants per group. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: duration of antibiotic treatment (days)

CLINICAL: mortality, re‐admission, and length of hospital stay

Notes

FINANCIAL SUPPORT: Funding: Intensive Care Foundation of Australia and New Zealand. Material support was provided by Roche Diagnostics, Thermo Fisher Scientific, and bioMérieux. Roche Diagnostics and Thermo Fisher Scientific provided additional unrestricted grant funding. Competing Interests: none declared

ADDITIONAL DATA: email from authors with additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Patients were variable block randomised 1:1 via a secured central study website into either a PCT‐guided (PCT) group or clinician‐guided (standard care) group. Randomisation was stratified according to the presence of septic shock (defined by the receipt of inotropes and/or any vasopressors within the previous 24 hours).

Allocation concealment (selection bias)

Low risk

See above

Blinding (performance bias and detection bias)
All outcomes

High risk

Single‐blind

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on 196/200 intervention and 198/200 control participants.

Selective reporting (reporting bias)

Low risk

Other bias

Low risk

1567 patients screened, but 1167 excluded; full details of how many patients met each of the exclusion criteria (Figure 1)

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

PCT only reported for intervention participants.

Baseline characteristics similar?

Low risk

Table 1

Shen 2011

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians on 2 respiratory wards
PARTICIPANTS: all patients on the wards
CLINICAL PROBLEM: receiving antibiotics for respiratory infection
SETTING: 1 hospital

Interventions

FORMAT: Interventions: educational outreach by review and recommend change
Intervention Functions: enablement, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Choice: score on 6 indicators of inappropriate antibiotic use: indication, choice, dosage, dosing schedule, duration, conversion

CLINICAL: Balancing: length of stay

FINANCIAL: cost (mean, SD) of antibiotics and total patient costs

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

Says it was randomised, no further information.

Allocation concealment (selection bias)

High risk

Patients from 2 wards were randomised, and there is no information about allocation concealment.

Blinding (performance bias and detection bias)
All outcomes

Low risk

"At the end of the study, a blinded coordinating investigator recorded the patients’ data"

Incomplete outcome data (attrition bias)
All outcomes

Low risk

All outcomes reported.

Selective reporting (reporting bias)

Low risk

All outcomes reported.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No information

Free of contamination?

High risk

Intervention and control patients were on both wards.

Baseline characteristics similar?

Low risk

Table 1

Shojania 1998

Methods

STUDY DESIGN: RCT with nested ITS analysis (Figures 3 and 4)

Risk of Bias: HIGH

Participants

PROVIDERS: unit of randomisation ‐ 396 physicians in 7 specialties. Non‐physicians (nurses or pharmacists) who were authorised to enter orders that required eventual signing off by physicians were also randomised.
PARTICIPANTS: There were 5536 episodes of care in 1798 patients.
CLINICAL PROBLEM: receiving vancomycin treatment
SETTING: 1 university hospital in the USA

Interventions

FORMAT: Interventions: dissemination of guideline; reminders (circumstantial, delivered through computer screen at the time of physician order entry and after 72 hours of therapy). The reminder required prescribers to produce a response: when someone would enter an order for intravenous vancomycin, a pop‐up screen would appear and display the appropriate indications for vancomycin use, which was a checkbox list of indications based on CDC guidelines. Users had to pick a reason or enter free text under 'other' in order to proceed.

Intervention Functions: education, enablement, environmental restructuring

DELIVERER: AMT
COMPARISON: no reminder. ITS analysis used 9 months' pre‐intervention data.
DESIRED CHANGE: reduction of established management (reduction in use of vancomycin)

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Choice: initiation and renewal of vancomycin therapy. Duration of vancomycin therapy on a per‐prescriber basis. Total use of vancomycin in the hospital.

FINANCIAL: estimated savings

Notes

FINANCIAL SUPPORT: Funding: grant R01‐HS08927 from the Agency for Healthcare Policy and Research. Competing Interests: no information

ADDITIONAL DATA: email from authors with additional details about the intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

"The study was a randomised controlled trial"; no details on how randomisation sequence was generated

Allocation concealment (selection bias)

High risk

States "possible that physicians in the control group could learn of the intervention from physicians in the study group"

Blinding (performance bias and detection bias)
All outcomes

High risk

Not done

Incomplete outcome data (attrition bias)
All outcomes

Unclear risk

Not clear for primary outcome

Selective reporting (reporting bias)

Low risk

Based on numbers of vancomycin orders

Other bias

Low risk

No issues noted.

Baseline Outcomes similar?

Unclear risk

No information about pre‐intervention vancomycin use

Free of contamination?

High risk

States "possible that physicians in the control group could learn of the intervention from physicians in the study group"

Baseline characteristics similar?

Low risk

Table 1

Singh 2000

Methods

STUDY DESIGN: RCT, allocation by patient

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians on 1 ICU
PARTICIPANTS: 81 episodes of care (39 intervention, 42 control)
CLINICAL PROBLEM: suspected ventilator‐associated pneumonia with low CPIS
SETTING: 1 hospital in the USA

Interventions

FORMAT: Intervention: restrictive by expert approval and review and make change

Intervention Function: restriction
DELIVERER: ID physician

COMPARISON: choice, number, and duration of antibiotics at the discretion of the care providers
DESIRED CHANGE: reduction of established management (reduction in duration of antibiotic treatment)

POWER CALCULATION: yes, 88 patients per group. The study was terminated early. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: total duration of all antibiotic treatment

CLINICAL: Balancing: mortality, length of ICU stay

MICROBIAL: number of patients with "antimicrobial resistance and/or superinfections" from randomisation until hospital discharge

FINANCIAL: total costs of care for patients with CPIS < 6 at 3 days and no extrapulmonary infections

Notes

FINANCIAL SUPPORT: Funding: Bayer Corporation. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

"Patients were randomized to either the control group or experimental group"; no information about how randomisation sequence was generated

Allocation concealment (selection bias)

Unclear risk

Not stated

Blinding (performance bias and detection bias)
All outcomes

High risk

Page 509: "Because the study was not blinded, physicians and care providers could see the results"

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Most outcomes are reported for 78 (96%) episodes of care; antimicrobial resistance and superinfection in 74 (91%) of episodes.

Selective reporting (reporting bias)

Low risk

No problems found.

Other bias

High risk

Microbial Risk of Bias HIGH. Case definition for microbial outcome NOT CLEAR: "Follow‐up respiratory cultures or cultures from clinical specimens performed 7 to 28 d after initiation of antibiotics were evaluated to assess the emergence of antimicrobial resistance or superinfections. Emergence of resistance was defined as the detection of new antimicrobial resistance pattern in the old or previously isolated organism. Superinfection was defined as the detection of the following organisms not present at study entry: Acinetobacter species, Serratia marcescens, Pseudomonas aeruginosa, Stenotrophomonas maltophilia, Enterobacter species, Citrobacter species, methicillin‐resistant Staphylococcus aureus (MRSA), Enterococcus species, and Candida species." It is therefore impossible to assess the impact of the intervention on colonisation or infection with bacteria resistant to specific antibiotics. Infection control NOT CLEAR. Planned intervention YES

Baseline Outcomes similar?

Unclear risk

Not stated, no information about pre‐intervention duration of antibiotic treatment

Free of contamination?

Unclear risk

Not stated

Baseline characteristics similar?

Low risk

See Table 1 in study.

Sirinavin 1998

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients requiring treatment with imipenem vancomycin or injectable ciprofloxacin
SETTING: 1 hospital in Thailand

Interventions

FORMAT: Interventions: educational meetings with dissemination of antimicrobial order form; educational outreach by review and recommend change of cases of inappropriate prescribing by ID consultant; restrictive by compulsory order form
Intervention Functions: education, enablement, persuasion, restriction

Figure 2 suggests that expenditure increased sharply in the final year of the study when ID consultant review ceased.

DELIVERER: specialist physician (ID)

COMPARISON: data for 4 years' pre‐restriction
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: restricted drugs cost in million THB/200,000 OBD

Notes

FINANCIAL SUPPORT: Funding: Ramathibodi Research Fund. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

4 years' data pre‐ and postintervention

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: run charts with no statistical analysis.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

High risk

NOT DONE, there is no information about change in price of antibiotics over the study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Unclear risk

NOT CLEAR, no adjustment of antibiotic costs for change in price, so change in price of antibiotics (rather than change in use) over the study period may have been responsible for some of the change in cost. Data were not adjusted for number of admissions or occupied bed days.

Skaer 1993

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: physicians (numbers not clear)
PATIENTS: all patients in the hospital

CLINICAL PROBLEM: adult patients receiving imipenem treatment

SETTING: 1 hospital in the USA

Interventions

FORMAT: Intervention: educational outreach by review and recommend change

Intervention Functions: enablement, persuasion

DELIVERER: pharmacist

COMPARISON: usual care in the pre‐intervention phase

DESIRED CHANGE: reduce excessive

Outcomes

PRESCRIBING: Choice: Monthly use (doses) of imipenem

CLINICAL: cohort data about length of stay and hospital charges for patients with a primary diagnosis of infection

Notes

FINANCIAL SUPPORT: Funding: Washington State University College of Pharmacy and Pullman Memorial Hospital. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Incomplete outcome data addressed (ITS) ?

Low risk

Free of selected reporting (ITS) ?

Low risk

Free of other bias (ITS) ?

Low risk

Yes for primary outcome but fatally flawed (UBA) for secondary outcomes.

Skrlin 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: use of ceftriaxone following removal of restriction
SETTING: 1 hospital in Croatia

Interventions

FORMAT: Intervention: restrictive, removal of restriction by expert approval

Intervention Function: restriction
DELIVERER: AMT
COMPARISON: removal of restriction versus restriction
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of ceftriaxone in DDD/1000 OBD

MICROBIAL: number of ESBL‐producing strains/1000 OBD

Notes

FINANCIAL SUPPORT: Funding none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: LOW case definition Low, planned intervention Low, other infection control Low

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of other bias (ITS) ?

Low risk

24 months' data pre‐ and postintervention

Solomon 2001

Methods

STUDY DESIGN: cluster RCT, service level

Risk of Bias: HIGH

Participants

PROVIDERS: 17 Internal Medicine services randomly assigned to intervention (9 services) or control (8 services)
PARTICIPANTS: a total of 4500 patients admitted during the baseline and study periods, of whom 260 patients received 278 unnecessary prescriptions for the target drugs; 17 clusters (services)
CLINICAL PROBLEM: patients receiving ceftazidime or levofloxacin.
SETTING: 1 hospital in the USA

POWER CALCULATION: no information. The methods say that the statistical model adjusted for clustering, but no results are given (see risk of bias).

Interventions

FORMAT: Interventions: educational meetings with dissemination of policy for necessary use; educational outreach by review and recommend change, either verbal (face to face or telephone) or by email
Intervention Functions: education, enablement, persuasion
COMPARISON: randomly assigned control services
DESIRED CHANGE: reduce excessive

POWER CALCULATION: no information. Note from Statistician: The study adjusted for some clustering, but possibly only in the repeated measures, not in the hospitals. Just using the results from Table 2, I do not get the P value that they state in the table using a unit of analysis error approach. This suggests to me that they are adjusting for "things". I therefore think on balance that it is probably OK to use the results.

Outcomes

PRESCRIBING: Choice: % patients with target antibiotics discontinued. Exposure: % patients with all antibiotics discontinued

CLINICAL: inpatient mortality, transfer to ICU, length of stay, and re‐admission within 30 days of discharge

FINANCIAL: estimated annual cost of the intervention

Notes

FINANCIAL SUPPORT: Funding: Brigham and Women’s Hospital and Arthritis Foundation Investigator Award. Competing Interests: no information

ADDITIONAL DATA: email from authors with information about the intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"We assigned services to intervention or control status using a blocked randomization design"

Allocation concealment (selection bias)

Unclear risk

Not concealed

Blinding (performance bias and detection bias)
All outcomes

High risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Unclear risk

Figure 2 and text give %, no denominator.

Selective reporting (reporting bias)

Unclear risk

Figure 2 and text give %, no denominator.

Other bias

Unclear risk

The methods say: "To estimate the relative reduction in unnecessary use of target antibiotics in the intervention group, we used a fixedeffects model (PROC GENMOD in SAS statistical software).20 This model used a log‐linear link function, assumed a Poisson distribution, and accounted for overdispersion. Experimental group assignment (intervention or control) was the independent variable of interest, the individual service was considered a class effect, and covariates included level of baseline prescribing and time, modeled as both a linear and categorical effect. The interaction between assignment and time was also assessed. We further considered a linear randomeffects model to account for variation between services (PROC MIXED in SAS statistical software)20; the results of this analysis were similar to those found in the fixed‐effects models with respect to the level of statistical significance, and only the fixedeffects model results are presented." However, no model outputs are given in the results (only point estimates), and the discussion says only: "This significant effect of the intervention remained after adjusting for baseline prescribing, clustering of repeated measures within a given service, and duration of the intervention."

Baseline Outcomes similar?

Low risk

Figures 1 and 2

Free of contamination?

High risk

The services were in the same hospital.

Baseline characteristics similar?

Low risk

Table 1

Standiford 2012

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: cost of animicrobials
SETTING: 1 hospital in the USA

Interventions

FORMAT: Interventions: educational outreach by review and recommend change
Intervention Functions: enablement, persuasion
DELIVERER: AMT
COMPARISON: usual care pre‐intervention and impact of removal of the intervention (2 years)
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: quarterly cost of all antimicrobials

CLINICAL: Balancing: cohort data for mortality, length of stay, and unplanned re‐admission. The DRG case mix index was monitored to ensure that changes in outcomes were not related to this index.

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

No information is given about changes in drug pricing over the 12 years of data collection, which is likely to have changed the outcome measure. In addition, there were changes in pharmacy data systems after the intervention, but the timing is clearly documented in Figure 1.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data were from the Pharmacy Administration and were independent from the AMT.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data were from the Pharmacy Administration and were independent from the AMT.

Incomplete outcome data addressed (ITS) ?

Low risk

Data were from the Pharmacy Administration and were independent from the AMT.

Free of selected reporting (ITS) ?

Low risk

Data were from the Pharmacy Administration and were independent from the AMT.

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Stevenson 1988

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: receiving antibiotics
SETTING: 1 hospital in the UK

Interventions

FORMAT: Interventions: dissemination of antibiotic policy

Intervention Function: education
DELIVERER: pharmacist

COMPARISON: 10 quarters (30 months) pre‐intervention
DESIRED CHANGE: reduce excessive

Outcomes

PRESCRIBING and FINANCIAL: Choice: average cost of antibiotics per patient. Prices were indexed to 1980.

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

2 years' data pre‐ and postintervention, enough to account for seasonal effects

Analysed appropriately (ITS) ?

Low risk

Done in original paper: regression analysis testing for structural break associated with intervention.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, drug costs were adjusted to 1980 prices.

Free of other bias (ITS) ?

Low risk

Drug costs were adjusted to 1980 prices and adjusted for number of discharges or deaths.

Stocker 2010

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the neonatal ICU
PARTICIPANTS: 121 neonates (60 intervention, 61 control)
CLINICAL PROBLEM: suspected sepsis
SETTING: 1 hospital in Switzerland

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm with each PCT test); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring
DELIVERER: departmental physician (Paediatrics)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: unclear. The trial was designed to obtain a power of 90% to detect a 30% difference between the 2 groups in the duration of antibiotic therapy, with an estimated standard deviation of 50%. Sample size: no information

Outcomes

PRESCRIBING: Exposure: duration, % treated > 72 h

Notes

FINANCIAL SUPPORT: Funding: commercial B.R.A.H.M.S Diagnostica (Berlin, Germany) provided the testing kits for PCT. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Randomised using assignment cards in envelopes

Allocation concealment (selection bias)

Low risk

Randomised using assignment cards in envelopes

Blinding (performance bias and detection bias)
All outcomes

High risk

Not blinded

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes on all patients

Selective reporting (reporting bias)

Low risk

Outcomes on all patients

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

PCT results only reported for intervention patients.

Baseline characteristics similar?

Low risk

Table 1

Stolz 2007

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in Internal Medicine
PARTICIPANTS: all patients hospitalised with exacerbations of chronic obstructive pulmonary disease; 288 screened, 226 randomised (113 intervention, 113 control)
CLINICAL PROBLEM: use of therapeutic antibiotics
SETTING: 1 hospital

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm with each PCT test); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring
DELIVERER: departmental physician (Respiratory)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION: yes, total 186 participants. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: % antibiotic use for the exacerbation and in the subsequent 6 months

CLINICAL: Balancing: length of stay, death, symptom scores

Notes

FINANCIAL SUPPORT: Funding: part commercial University Hospital Basel. B.R.A.H.M.S provided procalcitonin assays for this investigator‐driven study. Competing Interests: 1 author served as consultant and received payments from B.R.A.H.M.S to attend meetings and for travel expenses, speaking engagements, or research.

ADDITIONAL DATA: email response from authors with additional information about intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

No details: "Patients satisfying the entry criteria were randomly assigned to one of two groups at the time of admission to the emergency department "

Allocation concealment (selection bias)

Unclear risk

No details

Blinding (performance bias and detection bias)
All outcomes

High risk

SIngle‐blind

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcome data reported on all patients.

Selective reporting (reporting bias)

High risk

11 (10%) patients excluded from intervention and 7 (6%) from control group for "absence of COPD according to GOLD", but this should have occurred pre‐randomisation.

Other bias

Low risk

Baseline Outcomes similar?

High risk

No data

Free of contamination?

Low risk

PCT only reported for intervention patients.

Baseline characteristics similar?

Low risk

Table 1

Stolz 2009

Methods

STUDY DESIGN: RCT

Risk of Bias: MEDIUM

Participants

PROVIDERS: all staff in adult ICUs
PARTICIPANTS: 101 patients with VAP (51 intervention, 50 control)
CLINICAL PROBLEM: receiving antibiotics for VAP
SETTING: 3 university hospitals in Switzerland and the USA

Interventions

FORMAT: Interventions: reminders (circumstantial, decision support algorithm with each PCT test); structural, introduction of PCT testing
Intervention Functions: enablement, environmental restructuring
DELIVERER: respiratory physicians
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

POWER CALCULATION; yes, 84 participants total. Details in Appendix 3

Outcomes

PRESCRIBING: Exposure: duration of antibiotic treatment

CLINICAL: Balancing: mortality, hospital length of stay

Notes

FINANCIAL SUPPORT: Funding: Swiss National Foundation, Margarete und Walter Liechtenstein Foundation, Freiwillige Akademische Gesellschaft Basel, Will Rogers Foundation, and participating hospitals. B.R.A.H.M.S AG funded assay material and logistics. Competing Interests: not clear. The published paper says that a statement of interest for the study itself is available but the web address provided online and in print does not work.

ADDITIONAL DATA: email response from authors with additional information about intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Block size 20 envelopes

Allocation concealment (selection bias)

Low risk

Sealed, opaque envelopes

Blinding (performance bias and detection bias)
All outcomes

High risk

Primary outcome measure required collection of data from case noes by investigators.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Text shows that primary outcome was reported for all 101 randomised patients.

Selective reporting (reporting bias)

Low risk

Text shows that primary outcome was reported for all 101 randomised patients.

Other bias

Low risk

Multivariate analysis to adjust primary outcome for age, microbiology and centre effect

Baseline Outcomes similar?

Unclear risk

No data about baseline outcomes

Free of contamination?

Low risk

Procalcitonin only measured for intervention patients.

Baseline characteristics similar?

Low risk

Table 1

Strom 2010

Methods

STUDY DESIGN: cluster RCT, professional level

Risk of Bias: MEDIUM

Participants

PROVIDERS: A total of 1971 clinicians were assigned to either an intervention group receiving a nearly hard‐stop alert or a control group receiving the standard practice.
PARTICIPANTS: 342 patients receiving warfarin and trimethoprim‐sulfamethoxazole (194 intervention, 148 control), 1971 clusters (physicians)
CLINICAL PROBLEM: reduce risk of interaction between warfarin and trimethoprim‐sulfamethoxazole
SETTING: 2 hospitals in the USA

POWER CALCULATION: "It is generally accepted that randomization of at least 100 subjects will produce balance between the study groups and, of course, the present sample size is much larger than this."

Interventions

FORMAT: Interventions: reminder (circumstantial) and restrictive by compulsory electronic order form that would not allow concomitant orders of warfarin and trimethoprim‐sulfamethoxazole. The only exception allowed by the order form was the indication of Pneumocystis carinii pneumonia prophylaxis. Expert approval was allowed for other patients when discussed with pharmacy.

Intervention Functions: enablement, environmental restructuring, restriction
DELIVERER: pharmacist
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: the proportion of desired responses (i.e. not reordering the alert‐triggering drug within 10 minutes of firing)

CLINICAL: Balancing: 2 potential adverse outcomes of the computerised hard‐stop alert were monitored and reported to the Institutional Review Board. The first was a delay in obtaining trimethoprim‐sulfamethoxazole when the practitioner believed that an infection was best treated with trimethoprim‐sulfamethoxazole and when the potential warfarin interaction was judged less important than the need for the antibiotic. The second was unintentional warfarin cessation in a patient previously undergoing long‐term warfarin therapy. The study therefore also assessed the incidence of warfarin cessation on the day when an order of trimethoprim‐sulfamethoxazole was attempted in a patient already receiving warfarin.

Notes

FINANCIAL SUPPORT: Funding: University of Pennsylvania Health System and Agency for Healthcare Research and Quality. Competing Interests: none declared

ADDITIONAL DATA: email response from authors with additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Number randomisation

Allocation concealment (selection bias)

Low risk

"Each medical practitioner has a unique access code to use the electronic ordering system, and the order system menu can be varied by individual user. In addition, we wanted to keep each practitioner in the same study group for the duration of the study to minimize contamination between the 2 groups. However, there is the possibility"

Blinding (performance bias and detection bias)
All outcomes

High risk

Not blinded

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcome reported on all patients, determined electronically.

Selective reporting (reporting bias)

Low risk

Outcome reported on all patients, determined electronically.

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No information

Free of contamination?

Low risk

"We attempted to reduce contamination by trying to complete this study as rapidly as possible. It was initially planned to last 7 months but had to be terminated early."

Baseline characteristics similar?

Low risk

Table 1

Sun 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all cardiac surgeons and other professionals
PARTICIPANTS: all patients undergoing coronary artery bypass surgery
CLINICAL PROBLEM: improve reliability of administration of prophylaxis (first dose within 1 h of incision and duration not > 24 h)
SETTING: 1 hospital in Taiwan

Interventions

FORMAT: Interventions: audit and feedback; educational meetings with dissemination of guidelines and evidence base
Intervention Functions: education, enablement
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice and exposure: time to first antibiotic dose, % of prophylaxis ≤ 24 h

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

From Taiwan Quality Improvement Project database

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from Taiwan Quality Improvement Project database.

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome reported on all patients pre‐ and postintervention.

Free of selected reporting (ITS) ?

Low risk

Objective outcomes from Taiwan Quality Improvement Project database

Free of other bias (ITS) ?

High risk

< 1 year data pre‐ and postintervention

Suwangool 1991

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the Department of Medicine
PARTICIPANTS: all patients in the Department of Medicine
CLINICAL PROBLEM: inappropriate antibiotic prescribing
SETTING: single university hospital in Thailand

Interventions

FORMAT: Interventions: dissemination of guidelines; restrictive by expert approval
Intervention Functions: education, restriction

DELIVERER: AMT
COMPARISON: 6 months' data pre‐intervention
DESIRED CHANGE: reduce excessive (cost)

Outcomes

PRESRIBING: Choice: monthly cost of target antibiotics

CLINICAL: cohort data about mortality

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy computer

Free of other bias (ITS) ?

Unclear risk

< 1 year data pre‐ and postintervention. During the 18‐month study period, no adjustment was made to antibiotic costs for changes in prices, so changes in cost may have been due to changes in price as well as use.

Talpaert 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients receiving antibiotics for prophylaxis or treatment. The intervention targeted fluoroquinolones, cephalosporins, clindamycin, amoxicillin, and co‐amoxiclav, as they were considered to be "high risk" for Clostridium difficile infection
SETTING: 1 hospital

Interventions

FORMAT: Interventions: educational meetings with dissemination of guidelines; educational outreach by review and recommend change; reminders (verbal (on rounds) and physical (laminated pocket cards and posters)); restrictive by removal of target drugs from clinical areas
Intervention Functions: education, enablement, environmental restructuring, persuasion restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of target antibiotics in DDD/1000 OBD

MICROBIAL: monthly cases of C difficile infection

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: 1 author was paid lecture fees and provided sponsorship to attend conferences by pharmaceutical companies unrelated to this study.

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias LOW: case definition Low (new cases), planned intervention Low, other infection control Low, fully reported in ORION format

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

Change in site ‐ moved to another building

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

From electronic records, so unlikely

Knowledge of the allocation adequately prevented(ITS)?

Low risk

From electronic records, so unlikely

Incomplete outcome data addressed (ITS) ?

Low risk

From electronic records, so unlikely

Free of selected reporting (ITS) ?

Low risk

From electronic records, so unlikely

Free of other bias (ITS) ?

Low risk

1 year data pre‐ and postintervention

Tangdén 2011

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving therapeutic antibiotics
CLINICAL PROBLEM: aim (i) to reduce the consumption of 2nd‐ and 3rd‐generation cephalosporins; and (ii) to avoid increased prescription of fluoroquinolones and carbapenems.
SETTING: 1 hospital in Sweden

Interventions

FORMAT: Interventions: educational meetings with dissemination of guidelines; educational outreach by academic detailing
Intervention Functions: education, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of target drugs in DDD/1000 OBD

Notes

FINANCIAL SUPPORT: Funding: no external. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: HIGH, Case definition Low, Unplanned intervention High (outbreak), Other infection control High. "In August 2006, the hospital director organized a steering group (SG) with the assignment to implement the necessary measures to contain the outbreak, including reinforcement of hygienic measures, such as hand disinfection, use of disposable gloves and aprons, and isolation of patients colonized or infected with ESBL‐KP.14 In addition to hygienic measures, the SG decided to perform an antibiotic intervention."

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

DDD from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

DDD from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

DDD from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

DDD from pharmacy computer

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention

Toltzis 1998

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the mixed medical and surgical paediatric ICU
PARTICIPANTS: all patients in the paediatric ICU
CLINICAL PROBLEM: patients requiring antibiotic treatment
SETTING: a paediatric ICU in 1 hospital in the USA

Interventions

FORMAT: Intervention: restrictive, probably by expert approval ("Prohibition of ceftazidime use unless the patient's microbiological results indicated that the drug was necessary for cure.")

Intervention Function: restriction

DELIVERER: specialist (ID) physician
COMPARISON: 7 months' data before the start of the intervention
DESIRED CHANGE: reduce excessive

Outcomes

PRESCRIBING: Choice: ceftazidime use in doses

Notes

FINANCIAL SUPPORT: Funding: grant HD31323‐02 from the National Institutes of Health. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

NOT CLEAR, data for 7 months pre‐ and 12 months postintervention, not enough to adjust for seasonal variation

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after) with χ2 test.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

High risk

< 1 year data pre‐intervention

Toltzis 2002

Methods

STUDY DESIGN: NRT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians (paediatricians) on the ICU
PARTICIPANTS: all neonates in the ICU
CLINICAL PROBLEM: neonates with proven or suspected infections caused by gram‐negative bacteria
SETTING: 1 neonatal ICU in 1 hospital in the USA

Interventions

FORMAT: no valid prescribing data. Restrictive by removal, monthly rotation of the antibiotic regimen used for empirical prescribing of patients with proven or suspected gram‐negative infections

DELIVERER: specialist physician (ICU)
COMPARISON: standard practice
DESIRED CHANGE: reduce excessive (colonisation with multiresistant bacteria)

Outcomes

MICROBIAL: incidence of colonisation with multiantibiotic‐resistant aerobic gram‐negative bacilli

Notes

FINANCIAL SUPPORT: Funding: grant HD 31323‐05 from the National Institutes of Health Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: MEDIUM Case definition Low, Planned intervention Low, Other infection control Unclear

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

NRT with monthly rotation of regimens

Allocation concealment (selection bias)

High risk

Not possible with this study design

Blinding (performance bias and detection bias)
All outcomes

High risk

Not possible with this study design

Incomplete outcome data (attrition bias)
All outcomes

Unclear risk

Not stated whether screening samples obtained from all patients

Selective reporting (reporting bias)

Unclear risk

Not stated whether screening samples obtained from all patients

Other bias

Unclear risk

NOT CLEAR Microbial Outcome Risk of Bias Criteria Case definition: DONE Colonisation by screening. "For the purpose of this study, an 'antibiotic‐resistant Gram‐negative organism' was defined as any Gram‐negative bacillus resistant to gentamicin, piperacillin‐tazobactam, or ceftazidime. Pharyngeal and rectal swab specimens were obtained on all infants every Monday, Wednesday, and Friday". Planned intervention: DONE; Other infection control, Isolation: IC practices: NOT CLEAR Not described, but it is reasonable to assume that they were the same for the intervention and control groups due to the controlled clinical trial design.

Baseline Outcomes similar?

Unclear risk

Not stated

Free of contamination?

Unclear risk

Not stated, but doctors likely to have been managing patients in more than 1 study phase.

Baseline characteristics similar?

Low risk

Results, paragraph 1

Toltzis 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all paediatric surgeons and anaesthetists
PARTICIPANTS: all children undergoing surgery
CLINICAL PROBLEM: increase % of patients receiving antibiotic prophylaxis within 1 hour of incision as 1 of 3 components of a bundle of care
SETTING: 8 paediatric hospitals in the USA

Interventions

FORMAT: no valid prescribing data. Audit and feedback
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

CLINICAL: surgical‐site infection rate per 100 procedures

Notes

FINANCIAL SUPPORT: Funding: Ohio Business Roundtable, the Cardinal Health Foundation, and the Ohio Children’s Hospital Association. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Administration of antibiotics within 1 hour was 1 component of the bundle; the other 2 were avoiding shaving and encouraging use of clorhexidine for disinfection. In addition, 9 months after the intervention began an additional antibiotic element was added to encourage administration of an additional dose for operations lasting more than 3 hours.

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Patient administration systems and routine collection of surgical‐site infection data by each hospital's infection prevention teams

Knowledge of the allocation adequately prevented(ITS)?

High risk

Infection prevention teams were not prevented from knowing about allocation.

Incomplete outcome data addressed (ITS) ?

Low risk

Free of selected reporting (ITS) ?

Low risk

Data reported for all months when operations took place

Free of other bias (ITS) ?

High risk

Only 8 months' pre‐intervention data

Trenholme 1989

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 226 patients (110 intervention, 116 control)
CLINICAL PROBLEM: patients with bacteraemia
SETTING: 1 hospital in the USA

Interventions

FORMAT: Interventions: educational outreach by review and recommend change (intervention and control); structural, rapid processing and reporting of antimicrobial susceptibility tests (intervention only)
Intervention Functions: enablement, environmental restructuring, persuasion

DESIRED CHANGE: reduce excessive

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Choice: % changes in therapy in response to recommendation

FINANCIAL: savings in drug costs

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Unclear risk

Not stated; "the organism from the patient was randomly assigned"

Allocation concealment (selection bias)

Unclear risk

Not stated

Blinding (performance bias and detection bias)
All outcomes

Unclear risk

Not stated as blind

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Table 2 reports primary outcome for all 226 randomised patients.

Selective reporting (reporting bias)

Low risk

Table 2 reports primary outcome for all 226 randomised patients.

Other bias

Low risk

No other apparent biases found.

Baseline Outcomes similar?

Unclear risk

No information about recommendations for changes in therapy before the intervention

Free of contamination?

Unclear risk

Likely to be contamination as doctors managing control patients would receive advice on intervention patients.

Baseline characteristics similar?

Unclear risk

No information

Uçkay 2009

Methods

STUDY DESIGN: ITS

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in one orthopaedic unit
PARTICIPANTS: all patients in one orthopaedic unit
CLINICAL PROBLEM: suspected bone and joint infection
SETTING: 1 hospital in Switzerland

Interventions

FORMAT: Interventions: educational outreach by review and recommend change. The intervention is reported in 2 phases, the 1st delivered by "Dedicated ID specialist and one internist" and the 2nd delivered by "ID specialist with experience in Infection Control".
Intervention Functions: enablement, persuasion
DELIVERER: specialist (ID) physician
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of IV and oral antibiotics in DDD/1000 OBD

Notes

FINANCIAL SUPPORT: Funding: none.Competing Interests: none declared.

ADDITIONAL DATA: email response from authors with additional data about the intervention

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

Insufficient information to assess

Analysed appropriately (ITS) ?

Low risk

Time series analysis with ARIMA modelling

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Unclear risk

Outcome data were from routine pharmacy systems.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data were from routine pharmacy systems.

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data were from routine pharmacy systems.

Free of selected reporting (ITS) ?

High risk

The information in Table 1 does not include total antibiotic use or cost, so cannot be used to support the claims made in the paper.

Free of other bias (ITS) ?

High risk

< 1 year pre‐intervention data

Insufficient information to assess. In particular, it is not clear what difference the "ID specialist with experience in Infection Control" would make compared with "Dedicated ID specialist and one internist".

Valiquette 2007

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: receiving therapeutic or prophylactic antibiotics
SETTING: 1 hospital in Canada

Interventions

FORMAT: Interventions: educational meetings with dissemination of guideline and letter; educational outreach by review and recommend change; reminders (physical, pocket‐size guideline)
Intervention Functions: education, enablement, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice and exposure: use of individual targeted drugs in DDD/1000 OBD; use of all antibiotics in DDD/1000 OBD

MICROBIAL: Clostridium difficile infections/1000 OBD

Notes

FINANCIAL SUPPORT: Funding: National Foundation for Infectious Diseases. Competing Interests: 1 author has been on the speakers’ bureau for Wyeth; served on advisory boards for Wyeth and Cubist; and received grants from Wyeth, Genzyme, and Arpida. 1 author has been on the speakers’ bureau for Wyeth Canada; served on advisory boards for Bayer, Wyeth, ViroPharma, and Acambis; and received grants from Genzyme.

ADDITIONAL DATA: email from authors but no additional data

Microbial Risk of Bias: HIGH Case definition Low. Planned intervention High, response to epidemic of infection caused by high‐virulence strain. Other infection control High, the rate of CDI was already declining in response to infection control intervention when antimicrobial intervention began.

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Antimicrobial intervention followed an infection control intervention, so it is not possible to assess the independent impact on C difficile infection. Moreover, the infection control intervention could have been responsible for some or all of the reduction in total antibiotic use.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of other bias (ITS) ?

High risk

Microbial Risk of Bias HIGH

> 1 year of data pre‐intervention

van Hees 2008

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the Departments of Internal Medicine, Gastroenterology, Surgery, Urology, and Pulmonary Diseases
PARTICIPANTS: all patients in the same departments
CLINICAL PROBLEM: patients receiving ciprofloxacin
SETTING: 1 university hospital in the Netherlands

Interventions

FORMAT: Interventions: educational meetings; educational outreach by review and recommend change
Intervention Functions: education, enablement, persuasion
DELIVERER: specialist physicians (microbiologists)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive (reduce unnecessary ciprofloxacin)

Outcomes

PRESCRIBING: Choice: use of ciprofloxacin in prescriptions/1000 OBD

Notes

FINANCIAL SUPPORT:Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data for primary outcome measure were from pharmacy computer.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data for primary outcome measure were from pharmacy computer.

Incomplete outcome data addressed (ITS) ?

Low risk

Data for primary outcome measure were from pharmacy computer.

Free of selected reporting (ITS) ?

Low risk

Data for primary outcome measure were from pharmacy computer.

Free of other bias (ITS) ?

High risk

Only 3 months' pre‐ and 6 months' postintervention data, so cannot be adjusted for seasonal trends.

Van Kasteren 2005

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospitals

PATIENTS: all patients undergoing elective surgery

CLINICAL PROBLEM: surgical prophylaxis across 4 surgical disciplines

SETTING: 14 hospitals in the Netherlands

Interventions

FORMAT, Interventions: audit and feedback; educational meetings with dissemination of guidelines
Intervention Functions: education, enablement

DELIVERER: AMT

COMPARISON: pre‐intervention periods

DESIRED CHANGE: reduce excessive duration of surgical prophylaxis

Outcomes

PRESCRIBING: Exposure: total antibiotic use in DDD/100 procedures

CLINICAL: Balancing: cohort data on surgical‐site infections

Notes

FINANCIAL SUPPORT: Funding: Netherlands Organisation for Health Research and Development (ZonMw). Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Only 6 months' pre‐ and postintervention data, and the model was not adjusted for seasonal trends.

Analysed appropriately (ITS) ?

Low risk

Done in original paper: segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period. Change in price unlikely to be a problem because only 6 months' data pre‐ and postintervention.

Volpe 2012

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the ED
PARTICIPANTS: all patients with fever and suspected neutropenia
CLINICAL PROBLEM: fever and suspected neutropenia
SETTING: 1 university paediatric hospital in the USA

Interventions

FORMAT: Interventions: audit and feedback with action planning; educational meetings with dissemination of care algorithm and forms to facilitate care; educational outreach by academic detailing; reminders (circumstantial, root‐cause analysis of individual cases not meeting goal); reminders (physical, posters, email, and verbal, during rounds)
Intervention Functions: education, enablement, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: increase effective, reduce time to first antibiotic dose

Outcomes

PRESCRIBING: Choice: time (minutes) to first antbiotic dose

BALANCING MEASURE OF UNINTENDED CONSEQUENCES: "For balancing measures during the improvement period, we chose to follow the timeliness of first b‐agonist treatment of patients with asthma and the left without being seen (LWBS) rate."

Notes

FINANCIAL SUPPORT:Funding: no external funding. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Statistical process control chart

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from patient administration system

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from patient administration system

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from patient administration system

Free of selected reporting (ITS) ?

Low risk

Outcome data from patient administration system

Free of other bias (ITS) ?

Low risk

> 12 months' data pre‐ and postintervention

Walker 1998

Methods

STUDY DESIGN: RCT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 50 patients (25 intervention, 25 control)
CLINICAL PROBLEM: duration of IV antibiotics for patients with community‐acquired pneumonia
SETTING: 1 hospital in the USA

Interventions

FORMAT: Interventions: educational outreach by review and recommend change
Intervention Functions: enablement, persuasion
A written recommendation to change from IV ceftriaxone to an oral regimen was placed in each patient's prescription chart by the pharmacist. Direct contact with prescribers was not possible "because the medical staff in community hospitals have a large variation in the hours in which they make rounds" and "the physician is frequently busy, phone calls usually involve multiple pharmacists".
DELIVERER: pharmacist
COMPARISON: standard practice (no intervention)
DESIRED CHANGE: reduce excessive

POWER CALCULATION: no information

Outcomes

PRESCRIBING: Choice: number of patients changed to oral antibiotic therapy
CLINICAL: Balancing: re‐admissions (total and for pneumonia)

Notes

FINANCIAL SUPPORT: Funding: commercial, Pharmacia and Upjohn. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"A list of random numbers was generated from Sigmastat version 1.0 statistical software"

Allocation concealment (selection bias)

Unclear risk

Not stated, but open label, so unlikely to be concealed

Blinding (performance bias and detection bias)
All outcomes

High risk

"Open label"

Incomplete outcome data (attrition bias)
All outcomes

Low risk

No problems found.

Selective reporting (reporting bias)

Low risk

No problems found.

Other bias

Low risk

No other apparent biases found.

Baseline Outcomes similar?

Unclear risk

Not stated

Free of contamination?

Unclear risk

Not stated

Baseline characteristics similar?

Low risk

See Table 1 in paper

Wang 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in 16 adult ICUs
PARTICIPANTS: all patients in the ICUs
CLINICAL PROBLEM: use of target antibiotics in patients with positive blood cultures
SETTING: 1 University hospital in Taiwan

Interventions

FORMAT: Intervention: educational outreach by review and recommned change; restrictive by expert approval

Intervention Functions: education, enablement, persuasion, restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive, reduce cost of antimicrobials by reducing unnecessary use

Outcomes

PRESCRIBING: Choice: primary outcome is cost of all antimicrobials (Figure 4G). Also reports impact on use of 7 target antibacterials and use of antifungals in DDD/1000 OBD.

CLINICAL: Balancing: mortality, ICU re‐admission (segmented regression analysis)

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Outcome data from pharmacy computer

Free of other bias (ITS) ?

High risk

> 12 months' data pre‐ and postintervention. However, no adjustment of primary outcome for changes in drug pricing over the 5 years of the study.

Wax 2007

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all anaesthetists in the hospital
PARTICIPANTS: all patients undergoing elective surgery
CLINICAL PROBLEM: time to first dose for antibiotic prophylaxis
SETTING: 1 hospital in the USA

Interventions

FORMAT: Interventions: reminders (physical, electronic on screen during all surgical procedures, not just those requiring prophylaxis)
Intervention Functions: education, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

PRESCRIBING: Choice: % patients with first dose within 1 hour of incision

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcome data from electronic patient record, Anaesthesia Information Management System (AIMS)

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcome data from electronic patient record (AIMS)

Incomplete outcome data addressed (ITS) ?

Low risk

Outcome data from electronic patient record (AIMS)

Free of selected reporting (ITS) ?

Low risk

Outcome data from electronic patient record (AIMS)

Free of other bias (ITS) ?

High risk

Only 6 months' data pre‐intervention

Weinberg 2001

Methods

STUDY DESIGN: controlled ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: operating theatre teams at participating hospitals

PARTICIPANGS: low‐income women needing C‐section

CLINICAL PROBLEM: infection after C‐section

SETTING: 2 hospitals in Colombia

Interventions

FORMAT: Interventions: audit and feedback in the form of run charts for the 2 key process measures (secondary outcomes) with data collected and displayed by the clinical teams; dissemination of flow charts with revised system for administration of prophylactic antibiotics
Intervention Functions: education, enablement
DELIVERER: obstetric teams, doctors and nurses

COMPARISON: physician choice about antibiotic and timing

DESIRED CHANGE: reduce infection after C‐section

TIMING: before clinical decision making; the intervention was continued for 2 years

Outcomes

PRESCRIBING: Choice: percentage of women who received prophylaxis; percentage who received prophylaxis within 1 hour

CLINICAL: Intended: SSI rate per 100 C‐sections

Notes

INSTRUCTIONS: action plan provided, specific target but no specified time for target to be achieved

FINANCIAL SUPPORT: Funding: International Society for Infectious Diseases, Paul Schliesman Memorial Traveling Fellowship, and the Von L. Meyer Award. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Data collection method was the same pre‐ and postintervention.

Analysed appropriately (ITS) ?

Low risk

Done in original paper: segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Data collection method was the same pre‐ and postintervention.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Prescribing outcome data were from electronic systems.

Incomplete outcome data addressed (ITS) ?

Low risk

For prescribing outcome. Not stated whether SSI was evaluated in all patients

Free of selected reporting (ITS) ?

Low risk

For prescribing outcome. Not stated whether SSI was evaluated in all patients

Free of other bias (ITS) ?

High risk

< 1 year of data in each of the 3 study phases

Weiner 2009

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all attending emergency physicans, physician assistants, and emergency nurses
PARTICIPANTS: all patients with community‐acquired pneumonia
CLINICAL PROBLEM: time to first antibiotic dose
SETTING: 1 university hospital in the USA

Interventions

FORMAT: Interventions: audit and feedback; reminders (physical, electronic ‐ weekly emails)

Intervention Functions: enablement, environmental restructuring, persuasion
DELIVERER: departmental nurse administrator
COMPARISON: usual care
DESIRED CHANGE: increase effective

Outcomes

PRESCRIBING: Choice: mean time to first antibiotic dose (minutes)

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed; our analysis questions the authors' conclusion that the intervention was effective.

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

TFAD from patient administration system

Knowledge of the allocation adequately prevented(ITS)?

Low risk

TFAD from patient administration system

Incomplete outcome data addressed (ITS) ?

Low risk

TFAD from patient administration system, outcome reported on all included patients.

Free of selected reporting (ITS) ?

Low risk

"Patients were excluded if the time of antibiotic administration was not documented in the electronic medical record, if the patient was documented as having received antibiotics within 48 hours prior to arrival, or if the patient was referred from another facility or clinic with a known diagnosis of pneumonia." Exclusion rate in pre‐intervention period (37/281, 13%) similar to intervention period (40/342, 12%).

Free of other bias (ITS) ?

High risk

Only 11 months' data pre‐ and postintervention

Weiss 2013

Methods

STUDY DESIGN: cluster NRT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the ICU
PARTICIPANTS: all patients in the ICU
CLINICAL PROBLEM: receiving antibiotic treatment
SETTING: 1 University hospital in the USA

Interventions

FORMAT: Intervention: reminder, verbal (on rounds) based on a scripted electronic checklist of issues to discuss about antibiotics

Intervention Functions: environmental restructuring, persuasion
DELIVERER: departmental physicians
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: duration of empiric antibiotic treatment before narrowing choice, % patient days on which empiric antibiotics were used. Exposure: duration of all antibiotic treatment

CLINICAL: Balancing: mortality (total, standardised mortality ratio, and adjusted odds of death), length of hospital stay, length of ICU stay

Notes

FINANCIAL SUPPORT: National Heart, Lung, and Blood Institute (T32HL076139‐07) and Parker B. Francis Fellowship to CHW. Dr Weiss has received funding from the National Institutes of Health. Drs Sung and Rho received a travel award to present a research abstract at American Thoracic Society conference in May 2012 from Northwestern University. Dr Wunderink is a board member for Pfizer and has consulted for Crucell (now Johnson & Johnson), Trius, AstraZeneca, and GlaxoSmithKline. He has received grant support from bioMérieux and payment for lectures from the American Thoracic Society. The remaining authors have not disclosed any potential conflicts of interest.

ADDITIONAL DATA: online supplementary data for this article and further details of intervention in Weiss 2011. No response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Coin toss to allocate 1 medical team to intervention and 1 to control

Allocation concealment (selection bias)

High risk

No concealment

Blinding (performance bias and detection bias)
All outcomes

High risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcomes reported on all patients.

Selective reporting (reporting bias)

High risk

No information about inter‐rater reliability of primary outcome measure, which was not objective: "empirical antibiotics were defined as any antimicrobial agent administered without culture‐documented infection".

Other bias

High risk

Unit of analysis error, no adjustment for clustering

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

High risk

Intervention and control teams worked on the same ICU.

Baseline characteristics similar?

Low risk

Table 1

Welker 2008

Methods

STUDY DESIGN: unintended consequences, cohort study

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the ED
PARTICIPANTS: 548 patients with an admission diagnosis of community‐acquired pneumonia
CLINICAL PROBLEM: hospital admission diagnosis of community‐acquired pneumonia
SETTING: 1 hospital in the USA

Interventions

FORMAT: Interventions: audit and feedback; financial, institution incentive
Intervention Functions: enablement, incentive
DELIVERER: departmental physicians (ED)
COMPARISON: usual care (before introduction of core quality measure of 4 hours' time to first antibiotic dose)
DESIRED CHANGE: increase effective

Outcomes

UNINTENDED CONSEQUENCES: accuracy of admission diagnosis, antibiotic‐associated adverse drug events

Notes

ROBINS‐I RISK OF BIAS CRITERIA:

1. Confounding: Low, confounding of the effect of intervention unlikely in this study

2. Selection of participants into the study: Low, selection into the study unrelated to intervention or outcome

3. Measurement of interventions: Low, intervention status well defined, recorded at the time of intervention and unaffected by knowledge of the outcome or risk of the outcome

4. Departures from intended interventions: Low, no switches to other interventions or evidence of intervention failure

5. Missing data: Low, outcome data and intervention status complete in all 548 patients

6. Measurement of outcome: High, outcome measures not objective, and investigators were not blinded to intervention status

7. Selection of the reported result: Low, single analysis of prespecified outcomes

FINANCIAL SUPPORT: Funding: commercial: Pfizer, US Pharmaceutical Corporation. Competing Interests: none declared.

ADDITIONAL DATA: no response from authors to request for additional data

Wenisch 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients receiving moxifloxacin
SETTING: 1 university hospital in Austria

Interventions

FORMAT: Intervention: educational meetings; restrictive by compulsory order form

Intervention Functions: education, restriction
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of moxifloxacin in DDD

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: Low for case definition, planned intervention, and other infection control

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Re‐analysed

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of other bias (ITS) ?

High risk

< 12 months' data in the pre‐intervention (5 months) and postintervention (7 months) phases

Microbial Risk of Bias LOW: case definition Low, planned intervention Low, other infection control Low

Willemsen 2010

Methods

STUDY DESIGN: ITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving therapeutic antibiotics
CLINICAL PROBLEM: decrease use of ciprofloxacin
SETTING: 1 hospital in the Netherlands

Interventions

FORMAT: Interventions: educational meetings with dissemination of guidelines; educational outreach by review and recommend change; reminders (physical, newsletter and on all microbiology reports saying that ciprofloxacin should be prescribed on strict indications only)
Intervention Functions: education, enablement, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: prescribed daily doses of ciprofloxacin (IV and oral)

MICROBIAL: % quionolone‐resistant gram‐negative clinical isolates

Notes

FINANCIAL SUPPORT: Funding: Amphia Hospital, Breda/Oosterhout, Netherlands. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: LOW Case definition infection with quionolone‐resistant gram‐negative bacteria, Planned intervention Low, Other infection control Low, no changes (information in Discussion)

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Outcomes from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Outcomes from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Outcomes from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Outcomes from pharmacy and microbiology computers

Free of other bias (ITS) ?

Low risk

1 year data pre‐ and postintervention

Wilson 1991

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients receiving amoxicillin or pivampicillin
SETTING: 3 hospitals in the UK

Interventions

FORMAT: Intervention: dissemination of newsletter to all prescribers

Intervention Function: education

DELIVERER: pharmacists
COMPARISON: 5 months before introduction of the newsletter
DESIRED CHANGE: reduce excessive

Outcomes

PRESCRIBING: Choice: use of amoxicillin and pivampicillin

Notes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

Only 5 months' pre‐intervention data. Even with 26 months' postintervention data, could still be secular changes.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: run chart with no statistical analysis.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Winters 2010

Methods

STUDY DESIGN: unintended consequences, cohort study

Risk of Bias: LOW

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 3251 patients receiving antibiotics
CLINICAL PROBLEM: time to first antibiotic dose
SETTING: 1 hospital in the USA

Interventions

FORMAT: Interventions: restrictive by prior approval
Intervention Functions: restriction
DELIVERER: AMT
COMPARISON: usual care, 10 restricted vs 15 unrestricted antibiotics; daytime (8 am to 10 pm) when prior approval is required vs nighttime (10 pm to 8 am) when the first dose of all antimicrobials was exempted
DESIRED CHANGE: decrease excessive

Outcomes

UNINTENDED CONSEQUENCES: delays of > 1 hour or > 2 hours in TFAD

Notes

ROBINS‐I RISK OF BIAS CRITERIA:

1. Confounding: Low, confounding of the effect of intervention unlikely in this study

2. Selection of participants into the study: Low, selection into the study unrelated to intervention or outcome

3. Measurement of interventions: Low, intervention status well defined, recorded at the time of intervention and unaffected by knowledge of the outcome or risk of the outcome

4. Departures from intended interventions: Low, no switches to other interventions or evidence of intervention failure

5. Missing data: Low, outcome data and intervention status complete in all 3251 patients

6. Measurement of outcome: Low, outcome measures objective and ascertained from patient administration system

7. Selection of the reported result: Low, single analysis of prespecified outcomes

FINANCIAL SUPPORT: no information

ADDITIONAL DATA: no response from authors to request for additional data

Wishaupt 2011

Methods

STUDY DESIGN: NRT

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: 614 children < 12 years old (309 intervention, 305 control)
CLINICAL PROBLEM: acute respiratory infections (NB only 2/3 of randomised patients admitted to hospital)
SETTING: 1 hospital in the Netherlands

Interventions

FORMAT: Intervention: structural, rapid reporting of microbiology results

Intervention Function: environmental restructuring
DELIVERER: specialist physician (Microbiology)
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Exposure: % treated with antibiotics and duration if treated

CLINICAL: Intended: length of stay

Notes

FINANCIAL SUPPORT:Funding: Research Activity Committee of the Reinier de Graaf Hospital (project 620604). Competing Interests: no information

ADDITIONAL DATA: email response and additional files (protocol) from authors

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

By lab number

Allocation concealment (selection bias)

High risk

Not concealed

Blinding (performance bias and detection bias)
All outcomes

High risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

States missing information was retrieved from records

Selective reporting (reporting bias)

Low risk

Outcomes on all patients

Other bias

Low risk

Baseline Outcomes similar?

Unclear risk

No information

Free of contamination?

Low risk

Rapid reporting for intervention only

Baseline characteristics similar?

Low risk

Table 1

Woodward 1987

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: inpatient prescribing of all antibiotics
SETTING: 1 hospital in the USA

Interventions

FORMAT: Interventions: educational meetings; restrictive by expert approval, automatic stop order after 72 hours' treatment, and by removal from formulary
Intervention Functions: education, restriction
DELIVERER: specialist physician (ID)
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING and FINANCIAL: total antibiotic costs and average antibiotic cost per day

Notes

FINANCIAL SUPPORT: Funding: administration of Barnes Hospital. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

25 months' pre‐ and 17 months' postintervention data

Analysed appropriately (ITS) ?

Low risk

Done in original paper: ordinary least squares regression analysis adjusting for pre‐existing time trends, re‐analysis with segmented regression performed for the purposes of comparison of effect size with other studies in the review.

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Unclear risk

The abstract states: "Even after some cost increases (not significant) in new and other antibiotics, the program saved $1.33 per antibiotic day", but it is not clear whether the analysis was adjusted for changes in the price of antibiotics during the 3½‐year study period.

Wyatt 1998

Methods

STUDY DESIGN: cluster RCT, hospital level

Risk of Bias: MEDIUM

Participants

PROVIDERS: a total of 25 hospitals, 13 control and 12 intervention, targeting 2 providers (lead obstetrician and senior midwife manager) in each hospital
PARTICIPANTS: 1318 episodes of care in 1318 patients, 25 clusters (hospitals)
CLINICAL PROBLEM: administration of prophylactic antibiotics to women undergoing Caesarean section. The intervention also targeted 3 other care processes.
SETTING: 25 district general (non‐teaching) hospitals

POWER CALCULATION: As only 25 obstetric units were available for randomisation, and accurate baseline figures for the rates and variability of the 4 marker clinical practices were not available, sample size calculation was not carried out.

Interventions

FORMAT: educational meeting with dissemination of guideline and slides

COMPARISON: 13 control hospitals with no intervention

DESIRED CHANGE: increase effective

Outcomes

PRESCRIBING: Exposure: % women that received antibiotic prophylaxis

Notes

FINANCIAL SUPPORT: Funding: regional research implementation initiatives of the North Thames and South Thames regional health authorities; the Imperial Cancer Research Fund; and North Staffordshire Hospital Trust. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

Obstetric units were allocated to intervention or control group by the toss of a coin.

Allocation concealment (selection bias)

Low risk

To eliminate bias during data collection at follow‐up by a second research midwife, and to allow blinded assessment of guideline quality, the allocation was concealed from everyone except JCW, DGA, RJ, and the first research midwife.

Blinding (performance bias and detection bias)
All outcomes

Low risk

To eliminate bias during data collection at follow‐up by a second research midwife, and to allow blinded assessment of guideline quality, the allocation was concealed from everyone except JCW, DGA, RJ, and the first research midwife.

Incomplete outcome data (attrition bias)
All outcomes

Low risk

"No unit was excluded after randomisation, all intervention units participated in the visits, and data on clinical practices were available for all units, although smaller numbers of case notes were obtainable than planned for steroid usage"

Selective reporting (reporting bias)

Low risk

See above

Other bias

Low risk

"To reduce the impact of ceiling effects, the proportion of cases in which clinicians failed to carry out each clinical practice was recorded for each obstetric unit at baseline and follow up, and then baseline to follow up ratios were computed to yield the risk ratio for failure to implement each practice in each unit."

Baseline Outcomes similar?

Unclear risk

"Accurate baseline figures for the rates and variability of the four marker clinical practices were not available"

Free of contamination?

Low risk

Randomisation by units that were located in different hospitals

Baseline characteristics similar?

Low risk

"Despite randomisation there were baseline differences in two of the four clinical practices" (use of ventouse and use of polyglycolic acid sutures). "There were no other baseline differences." (includes antibiotic prophylaxis)

Yealy 2005

Methods

STUDY DESIGN: cluster RCT, hospital level

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the ED
PARTICIPANTS: 2075 patients admitted from ED (849 intervention, 1227 control), 32 clusters (EDs)
CLINICAL PROBLEM: community‐acquired pneumonia
SETTING: 32 EDs in the USA

Interventions

FORMAT: low‐intensity (control, 8 hospitals); moderate‐intensity (12 hospitals); and high‐intensity (12 hospitals) interventions

Low‐intensity intervention: audit and feedback of baseline data; dissemination of guidelines

Low‐intensity invervention functions: education, enablement

Moderate‐intensity intervention: same as low intensity, but with additional on‐site educational meeting before patient enrolment

Moderate‐intensity intervention additional function: education

High‐intensity intervention: same as moderate with additional audit and feedback of data about management of individual patients within a week of enrolment plus 2 monthly feedback of group performance data; educational outreach through academic detailing with Plan Do Study Act cycles to discuss actions to be taken in response to group performance data

High‐intensity intervention additional functions: education, enablement, persuasion

DELIVERER: departmental physicians

COMPARISON: usual care

DESIRED CHANGE: increase effective: 4 process measures including time to first antibiotic dose

POWER CALCULATION: Primary outcome was site of treatment rather than the antibiotic process measures. "We estimated that we would need 96 eligible patients per hospital (3072 in total) to achieve 80% power to detect a 12% difference across the intervention groups for the site‐of‐treatment decision among low‐risk patients."

"For the site‐of‐treatment decision, this study achieved greater than 80% power to detect differences of 10% between high‐intensity and moderate‐intensity groups and differences of 12% between high‐intensity and low‐intensity groups according to separate 1‐tailed tests in which the level was 0.025."

Outcomes

PRESCRIBING: Choice: time to first antibiotic dose and choice compliant with guideline

CLINICAL: Intended: mortality and medical complications

Notes

INSTRUCTIONS: action plan provided, no explicit target

FINANCIAL SUPPORT: Funding: Agency for Healthcare Research and Quality (grant number R01 HS10049). National Institute of Allergy and Infectious Diseases (grant number K24 AI001769). Competing Interests: 1 author received consultancies, honoraria or grants from Genesoft Pharmaceuticals, Zynx Health Corporation, Healthcare Communications Inc., Stephen Lynn Klein, Kellogg Grants, and Pfizer Inc.

ADDITIONAL DATA: email response from authors to request for additional data with care pathway, slide sets, order sheets, and protocol (Yealy 2004)

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

Low risk

"After stratifying emergency departments by state, teaching status, and annual volume, our statistician randomly assigned these departments to low‐intensity, moderate‐intensity, and high‐intensity guideline implementation strategies in the ratio of 2:3:3, respectively"

Allocation concealment (selection bias)

Low risk

Blinding (performance bias and detection bias)
All outcomes

High risk

Not blinded

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Incomplete chart review on only 19 (0.6%) of 3219 patients

Selective reporting (reporting bias)

Low risk

Other bias

Low risk

"The target sample size included an adjustment of 30% to account for the clustering of patients within providers."

Baseline Outcomes similar?

Unclear risk

No data

Free of contamination?

Low risk

Cluster RCT

Baseline characteristics similar?

Low risk

Demographic characteristics differed between eligible patients who were and were not enrolled. Moreover, authors observed some imbalances in levels of illness severity across the intervention groups; however, their analyses of the site of treatment were performed separately for low‐risk and higher‐risk patients, and their multivariable analyses were not sensitive to the few imbalances that were observed at baseline.

Yeo 2012

Methods

STUDY DESIGN: CITS

Risk of Bias: LOW

Participants

PROVIDERS: all physicians
PARTICIPANTS: all patients receiving therapeutic antibiotics
CLINICAL PROBLEM: use of all carbapenems (ertapenem, imipenem, and meropenem), 3rd‐ and 4th‐generation cephalosporins (ceftriaxone, ceftazidime, and cefepime), piperacillin/tazobactam, and vancomycin
SETTING: 1 cancer hospital in Singapore

Interventions

FORMAT: Interventions: audit and feedback; educational outreach by review and recommend change
Intervention Functions: enablement, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of target antibiotics in DDD/1000 OBD

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: 1 author received research funding and speaker’s honoraria from Pfizer, AstraZeneca, Janssen‐Cilag, and Merck Sharp & Dohme.

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Low risk

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Prescribing outcome in DDD from pharmacy computer

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Prescribing outcome in DDD from pharmacy computer

Incomplete outcome data addressed (ITS) ?

Low risk

Prescribing outcome in DDD from pharmacy computer

Free of selected reporting (ITS) ?

Low risk

Prescribing outcome in DDD from pharmacy computer

Free of other bias (ITS) ?

Low risk

Same 11 months of data (Aug‐Jun) in consecutive years pre‐ and postintervention

Yong 2010

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients receiving therapeutic antibiotics
CLINICAL PROBLEM: use of broad‐spectrum antibiotics (3rd‐ and 4th‐generation cephalosporins, aminoglycosides, antipseudomonal penicillins, carbapenems, fluoroquinolones)
SETTING: 1 hospital in Australia

Interventions

FORMAT: Interventions: structural, computerised decision support system
Intervention Functions: enablement, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of broad‐spectrum antibiotics in DDD/1000 OBD

Notes

FINANCIAL SUPPORT: Funding: Victorian Department of Human Services Quality Branch and Australian Commonwealth Biotechnology Information Fund, which funded the development of Guidance DS. Competing Interests: none declared

ADDITIONAL DATA: email from authors with additional data about intervention (Richards 2003; Thursky 2006)

Microbial Risk of Bias: MEDIUM (Other infection control High)

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Acinetobacter outbreak during intervention period resulting in hand hygiene and staff education interventions. Also see Table 4.

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of other bias (ITS) ?

Low risk

> 1 year data pre‐ and postintervention, so low risk for prescribing outcome

Microbial Risk of Bias: MEDIUM Case definition Low, % susceptibility of Pseudomonas isolates, Planned intervention Low for outcome (outbreak was of Acinetobacter), Other infection control High, enhanced during prescribing intervention

Yoon 2014

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: requiring therapeutic antibiotics and receiving carbapenems
SETTING: 1 university hospital in Korea, same hospital as Kim 2008

Interventions

FORMAT: Intervention 1: restrictive by expert approval (same intervention format as Kim 2008)

Intervention 1 functions: restriction

Intervention 2: addition of reminders (circumstantial, electronic triggered by computerised antibiotic order, the system is described in more detail in Kim 2008)
Intervention 2 functions: enablement, environmental restructuring, persuasion
DELIVERER: AMT
COMPARISON: usual care
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of carbapenems in DDD/1000 OBD

MICROBIAL: infections with CRAB (carbapenem‐resistant Acinetobacter baumanii)/1000 OBD

CLINICAL: Balancing measures of adverse effects, all‐cause mortality

Notes

FINANCIAL SUPPORT: Funding: commercial, Merck Sharp & Dohme. Competing Interests: supported by Merck Sharp & Dohme Corp.

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: HIGH case definition Low, planned intervention Low, other infection control High, ICU cleaning intervention during Phase 3

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

High risk

Intensive environmental cleaning implemented in 2012 in ICU, which was intended to reduce infections with CRAB (microbial outcome).

Analysed appropriately (ITS) ?

Low risk

Segmented regression analysis

Shape of effect pre‐specified (ITS) ?

Low risk

Point of intervention was point of analysis.

Unlikely to affect data collection (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Data from pharmacy and microbiology computers

Incomplete outcome data addressed (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of selected reporting (ITS) ?

Low risk

Data from pharmacy and microbiology computers

Free of other bias (ITS) ?

Low risk

> 1 year data in each study phase

Young 1985

Methods

STUDY DESIGN: ITS

Risk of Bias: MEDIUM

Participants

PROVIDERS: all physicians in the hospital
PARTICIPANTS: all patients in the hospital
CLINICAL PROBLEM: patients requiring aminoglycoside antibiotic treatment
SETTING: 1 hospital in the USA

Interventions

FORMAT: Interventions: restrictive by review and make change (substitution of amikacin for gentamicin) and expert approval from the Infectious Diseases Division
Intervention Function: restriction
DELIVERER: pharmacist

DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: gentamicin usage as a percentage of total aminoglycoside usage

Notes

FINANCIAL SUPPORT: Funding: Veterans Adminstration and Bristol‐Myers Squibb. Competing Interests: none declared, but Bristol‐Myers Squibb was the manufacturer of amikacin

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Intervention independent (ITS) ?

Unclear risk

3 months' data before, 15 months' during, and 22 months' after the restriction. Not enough data to adjust for seasonal variation.

Analysed appropriately (ITS) ?

Low risk

Re‐analysed. Not done in original paper: comparison of means (uncontrolled before‐after).

Shape of effect pre‐specified (ITS) ?

Low risk

Done, intended effect was decrease in primary outcome, and point of analysis was point of intervention.

Unlikely to affect data collection (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Knowledge of the allocation adequately prevented(ITS)?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Incomplete outcome data addressed (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of selected reporting (ITS) ?

Low risk

Done, data were from routine systems and unlikely to change over study period.

Free of other bias (ITS) ?

Low risk

No other apparent biases found.

Yu 2014

Methods

STUDY DESIGN: CBA

Risk of Bias: HIGH

Participants

PROVIDERS: all physicians
PARTICIPANTS: all patients
CLINICAL PROBLEM: patients receiving therapeutic antibiotics
SETTING: 5 hospitals in an integrated healthcare system in the USA

Interventions

FORMAT: Intervention: educational outreach through review and recommend change in 2 hospitals

Intervention Functions: enablement, persuasion
DELIVERER: AMT
COMPARISON: usual care in 3 hospitals
DESIRED CHANGE: decrease excessive

Outcomes

PRESCRIBING: Choice: use of target antibiotics in DDD/1000 OBD

CLINICAL: hospital standardised mortality ratio

MICROBIAL: Clostridium difficile infection rates

FINANCIAL: total and direct acquisitional cost of targeted antimicrobials

Notes

FINANCIAL SUPPORT: Funding: none. Competing Interests: none declared

ADDITIONAL DATA: no response from authors to request for additional data

Microbial Risk of Bias: HIGH case definition Not Clear, planned intervention Low, other infection control measures Not Clear

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

Study sites selected from baseline antimicrobial use.

Allocation concealment (selection bias)

High risk

No concealment

Blinding (performance bias and detection bias)
All outcomes

High risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Data from pharmacy computer

Selective reporting (reporting bias)

Low risk

Data from pharmacy computer

Other bias

Low risk

Baseline Outcomes similar?

High risk

Table 2

Free of contamination?

Low risk

Intervention and control sites different hospitals

Baseline characteristics similar?

High risk

Several potentially important differences between intervention and control sites

Zanetti 2003

Methods

STUDY DESIGN: NRT

Risk of Bias: HIGH

Participants

PROVIDERS: all surgeons in the hospital
PARTICIPANTS: 331 patients undergoing cardiac surgery
CLINICAL PROBLEM: additional dose of antibiotic prophylaxis for operations that lasted more than 4 hours
SETTING: 1 hospital in the USA

Interventions

FORMAT: Intervention: dissemination of guideline; reminder (circumstantial, electronic, automated intra‐operative alert)

Intervention Functions: education, enablement, environmental restructuring, persuasion
COMPARISON: control group plus 480 patients from the 6 months before the study period
DESIRED CHANGE: increase effective

Outcomes

PRESCRIBING: Exposure: % patients who received additional intra‐operative antibiotics

CLINICAL: Intended: wound infection rate

Notes

FINANCIAL SUPPORT: Funding: Centers for Disease Control and Prevention cooperative agreement, UR8/CCU115079, University Hospital of Lausanne, and the Leenaards Foundation. Competing Interests: no information

ADDITIONAL DATA: no response from authors to request for additional data

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

Based on a case number assigned to every surgical procedure performed in the hospital, independent of the study itself

Allocation concealment (selection bias)

High risk

No concealment

Blinding (performance bias and detection bias)
All outcomes

High risk

No blinding

Incomplete outcome data (attrition bias)
All outcomes

Low risk

Outcome on all 273 patients

Selective reporting (reporting bias)

Low risk

Outcome on all 273 patients

Other bias

Low risk

Outcome on all 273 patients

Baseline Outcomes similar?

Low risk

Cohort data before start of trial

Free of contamination?

High risk

Control patients were operated on by the same surgeons, and the reminder for intervention patients is likely to have increased awareness of the need for additional doses.

Baseline characteristics similar?

Low risk

Table 1

AB: antibiotic
AKI: acute kidney injury
AMT: multidisciplinary antibiotic management team
APACHE: Acute Physiology and Chronic Health Evaluation
ARGNB: antibiotic‐resistant gram‐negative bacilli
ARGPB: antibiotic‐resistant gram‐positive bacilli
ARIMA: autoregressive integrated moving average
ASP: Antimicrobial Stewardship Program
BCT: behaviour change technique
CAP: community‐acquired pneumonia
CBA: controlled before‐after study
CBC: complete blood count
CDAD: Clostridium difficile‐associated diarrhoea
CDC: Centers for Disease Control and Prevention
CDI: Clostridium difficile infection
CDSS: clinical decision support system
CI: confidence interval
CITS: comparative interrupted time series
CPIS: clinical pulmonary infection score
CRP: C‐reactive protein
C‐section: Caesarean section
DACT: double anaerobic coverage therapy
DDD: defined daily dose
DRG: diagnosis‐related group
ED: emergency department
EPOC: Effective Practice and Organisation of Care
ER: emergency room
ESBL‐EB: extended‐spectrum beta‐lactamase‐producing Enterobacteriaceae
FTE: full‐time equivalent
GRE: glycopeptide‐resistant enterococci
IC: infectious control
ICD: International Classification of Diseases
ICU: intensive care unit
ID: infectious diseases
IDP: infectious diseases physician
IHC: Intermountain Healthcare
IL‐8: interleukin‐8
ITS: interrupted time series
IQR: interquartile range
IV: intravenous
LOS: length of stay
MRSA: methicillin‐resistant Staphylococcus aureus
MSSA: methicillin‐sensitive Staphylococcus aureus
LRTI: lower respiratory tract infection
MICU: medical intensive care unit
NHAP: nursing home‐acquired pneumonia
NIH: National Institutes of Health
NRT: non‐randomised (controlled) trial
NRSI: non‐randomised studies of interventions
OBD: occupied bed day
OR: odds ratio
PA: parenteral antibiotics
PCR: polymerase chain reaction
PCT: procalcitonin
RCT: randomised controlled trial
RCOG: Royal College of Obstetricians and Gynaecologists
RDD: recommended daily doses
ROB: risk of bias
ROBINS‐I: risk of bias in non‐randomised studies of interventions
RR: risk ratio
SCIP: Surgical Care Improvement Project
SD: standard deviation
SE: standard error
SHEA: Society for Healthcare Epidemiology of America
SICU: surgical intensive care unit
SNF: skilled nursing facilities
SSI: surgical‐site infection
TFAD: time to first antibiotic dose
TREAT: computerised decision support system for antibiotic treatment
UBA: uncontrolled before‐after study
VAP: ventilator‐associated pneumonia
VRE: vancomycin‐resistant enterococci

Characteristics of excluded studies [ordered by study ID]

Study

Reason for exclusion

Ahronheim 2000

RCT with no relevant data. Antibiotics were only part of a complex care plan for 6% of participants in the intervention group, and the outcome data do not include information about the effect of the intervention on antibiotic prescribing.

Bruno‐Murtha 2005

ITS of antibiotic cycling with no interpretable data because there are no pre‐cycling data. Only provides data for 4 phases of cycling.

Burke 1997

ITS with no interpretable data. 2 different interventions (education, then restriction via order form) with 3 points before the education intervention and 3 after, but the restriction intervention started after the 4th point.

Cook 2006

ITS with no interpretable data because no clearly defined point in time at which the intervention started.

Crist 1987

NRT with no interpretable data. Unacceptable allocation bias ("the allocation of a patient to a particular group was determined by the attending physician").

Cunningham 2008

ITS with no relevant data. The only valid outcome data are about compliance with a guideline about generic documentation of prescription rather than any specific antibiotic prescribing outcome. The data about time to first antibiotic dose are UBA.

Dellinger 2005

ITS with no interpretable data because no clearly defined point in time at which the intervention started. Only 4 data points for antibiotic use, and the intervention included multiple components in addition to antibiotic use, so even if an intervention effect could be calculated reliably it could not be attributed to change in antibiotic prescribing.

Destache 1990

RCT with no interpretable data because of incomplete and selective reporting of outcome data. The primary outcome measure was length of stay, but 32% of participants in the intervention group were excluded because they had prolonged length of stay.

Ehrenkranz 1992

RCT with no interpretable data. Only report data for participants whose physicians followed recommendations.

Ehrenkranz 1993

RCT with no interpretable data. Only report data for participants whose physicians followed recommendations.

Evans 1994

NRT with no interpretable data. The first part compared the drugs that the Antibiotic Consultant programme recommended, with the drugs actually prescribed by physicians. Data from the second part are presented in an uninterpretable format, with the denominator as cultures, not participants or physicians.

Foy 2004

Cluster RCT with no relevant data. Intervention targeted 5 care processes for women having an abortion. Only 1 included antibiotic prescribing within a composite (antibiotic prophylaxis or screening for lower genital tract organisms). Effect of intervention on prescribing cannot be estimated.

Garcia‐San Miguel 2014

Cluster RCT with no interpretable data. The study included 9 hospitals with 32 hospitalisation units (wards). Patients were included if they had drugs dispensed from an electronic system.

Baseline: Jan‐June 2003 baseline, no intervention

1. Jan‐June 2004, intervention in half of the wards that were randomised in each hospital

2. Jan‐June 2005, cross‐over, intervention in wards that were randomised to control in Period 2

There is no description of the randomisation process. The primary outcome measure was adherence to recommendations; text on page 658 says they do not present data about mortality or re‐admission, but that appears to be what is in Figure 4. Figure 4: legend (and text) says it is about DDD and cost of drugs, but labelling says it is mortality and re‐admission. We asked authors to clarify and provide valid outcome data but received no reply.

Gerding 1991

ITS with no interpretable data. Describes 10 years of experience with aminoglycoside cycling, but the intervention periods cannot be mapped onto the outcome data about prescribing or resistance.

Kolar 1999

ITS with no interpretable data due to inadequate control for the effect of other interventions (infection control measures; see detailed critique by Monnet 2000).

Lan 2003

ITS with unacceptable missing data and inappropriate statistical analysis. There are 3 monthly data points pre‐intervention, then a gap in colonisation data for 3 months at the start of the intervention period followed by 3 monthly data points from months 4 to 6 of the intervention phase.

Lee 2004

ITS with no interpretable data. There were no isolates of ESBL‐Klebsiella pneumoniae in the last 3 months of the intervention phase, but no data are provided about the number of specimens screened. Appropriate statistical analysis in original paper not done (averages pre‐ and postintervention with χ2 and Fisher's exact test). Re‐analysis not possible because there are only 2 reliable data points in the postintervention phase.

MacCosbe 1985

RCT with no interpretable data. Only 29% of randomised doctors were followed up, and recommendations were only made in 6% of the intervention group.

Marrie 2000

Cluster RCT with no relevant data. Antibiotic prescribing was only 1 component of a care pathway, results for impact on antibiotic prescribing and its contribution to outcome not reported separately.

Martin 2005

ITS with no interpretable data. No antibiotic data pre‐intervention, only data about MRSA; this information is uninterpretable without information about pre‐intervention antibiotic prescribing.

McGregor 2006

RCT with no interpretable data. Statistical analysis of primary outcome measure (antibiotic costs) not done, and re‐analysis not possible from the data presented.

Nagao 2010

ITS with no interpretable data. Figure 1 reports the number of participants with inappropriate antibiotic use, consultations, significant laboratory test results, and total number of blood cultures obtained. However, the number of participants in each category is not clear in the figure. We asked the authors for raw data but they were unable to provide this information.

Naughton 2001

Cluster RCT in 10 skilled nursing facilities. The intention was to increase use of IV antibiotics for severe pneumonia. The comparison was between the same intervention delivered by a multidisciplinary team (intervention) versus a physician (control). There was no difference in the intervention effect, but the study provides no reliable evidence of intervention effect (UBA data in all 10 skilled nursing facilities).

Pastel 1992

NRT in 1 hospital, no interpretable data because no protection against contamination and unreliable primary outcome measure.

Ronning 1998

RCT with no relevant data. Not primarily an intervention on antibiotic therapy, compared stroke unit versus general medical ward.

Sanazaro 1978

NRT with no relevant data. Antibiotic prescribing was only 1 of 3 components of a care pathway, results for impact on antibiotic prescribing and its contribution to outcome not reported separately.

Takahashi 2010

ITS with no interpretable data. The only time series data (Figures 2 and 3) are MRSA and Pseudomonas aeruginosa infections. The paper claims that a prophylaxis intervention in early 2007 was responsible for reduction in P aeruginosa and MRSA infections, whereas the figures clearly show the reduction happened between July and December 2006. The paper does not include valid data about prescribing outcomes, and the authors were unable to provide these data.

Thomas 2002

CBA in 64 hospitals, no interpretable data because no clear point in time for the intervention.

Tiley 2003

ITS with no interpretable data. Multiple interventions are described without clear definition of intervention points.

Tsiata 2001

RCT with no interpretable data. These are provider interventions, but allocation was by patient randomisation. The unequal numbers of patients in each group (134 Group A, 141 Group B, and 105 Group C) and the differences in baseline characteristics indicate unacceptable allocation bias.

Van Loon 2005

ITS with no interpretable data about the impact of antibiotic cycling on resistance because there are no pre‐cycling data.

Wahlstrom 2003

RCT with no relevant data. Antibiotics included in the indicators for treatment of hospitalised cases of pneumonia (compliance with policy, dose and duration) and diarrhoea (no use of antibiotics without bacterial identification), but no separate data are presented for these outcomes. The only data provided are mean scores on a single composite indicator for each condition.

CBA: controlled before‐after study
DDD: defined daily dose
ESBL: extended‐spectrum beta‐lactamase
ITS: interrupted time series
MRSA: methicillin‐resistant Staphylococcus aureus
NRT: non‐randomised trial
RCT: randomised controlled trial
UBA: uncontrolled before‐after study

Data and analyses

Open in table viewer
Comparison 1. Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Dichotomous outcomes, increase in desired practice Show forest plot

29

23394

Risk Difference (M‐H, Fixed, 95% CI)

0.15 [0.14, 0.16]

Analysis 1.1

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 1 Dichotomous outcomes, increase in desired practice.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 1 Dichotomous outcomes, increase in desired practice.

2 Dichotomous outcomes, all RCTs with results of cluster RCTs adjusted by inflation factor Show forest plot

29

5802

Risk Difference (M‐H, Fixed, 95% CI)

0.17 [0.15, 0.19]

Analysis 1.2

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 2 Dichotomous outcomes, all RCTs with results of cluster RCTs adjusted by inflation factor.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 2 Dichotomous outcomes, all RCTs with results of cluster RCTs adjusted by inflation factor.

3 Dichotomous outcomes, low or medium 'Risk of bias' studies only Show forest plot

15

13086

Risk Difference (M‐H, Fixed, 95% CI)

0.11 [0.10, 0.12]

Analysis 1.3

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 3 Dichotomous outcomes, low or medium 'Risk of bias' studies only.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 3 Dichotomous outcomes, low or medium 'Risk of bias' studies only.

4 Continuous outcomes, duration of all antibiotic treatment (days) Show forest plot

14

3318

Mean Difference (IV, Fixed, 95% CI)

‐1.95 [‐2.22, ‐1.67]

Analysis 1.4

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 4 Continuous outcomes, duration of all antibiotic treatment (days).

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 4 Continuous outcomes, duration of all antibiotic treatment (days).

5 Continuous outcomes, duration of all antibiotic treatment with results of cluster RCTs adjusted by inflation factor Show forest plot

14

3318

Mean Difference (IV, Fixed, 95% CI)

‐1.95 [‐2.23, ‐1.67]

Analysis 1.5

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 5 Continuous outcomes, duration of all antibiotic treatment with results of cluster RCTs adjusted by inflation factor.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 5 Continuous outcomes, duration of all antibiotic treatment with results of cluster RCTs adjusted by inflation factor.

6 Continuous outcomes, low or medium 'Risk of bias' studies only Show forest plot

3

755

Mean Difference (IV, Fixed, 95% CI)

‐3.06 [‐3.76, ‐2.37]

Analysis 1.6

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 6 Continuous outcomes, low or medium 'Risk of bias' studies only.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 6 Continuous outcomes, low or medium 'Risk of bias' studies only.

7 Continuous outcome, consumption of targeted antibiotic only, standardised mean reduction (original outcome cost, days or DDD) Show forest plot

4

1053

Std. Mean Difference (IV, Fixed, 95% CI)

‐0.25 [‐0.37, ‐0.13]

Analysis 1.7

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 7 Continuous outcome, consumption of targeted antibiotic only, standardised mean reduction (original outcome cost, days or DDD).

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 7 Continuous outcome, consumption of targeted antibiotic only, standardised mean reduction (original outcome cost, days or DDD).

Open in table viewer
Comparison 2. Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Mortality, all RCTs Show forest plot

28

15827

Risk Difference (M‐H, Fixed, 95% CI)

‐0.00 [‐0.01, 0.00]

Analysis 2.1

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 1 Mortality, all RCTs.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 1 Mortality, all RCTs.

2 Mortality, all RCTs with results of cluster RCTs adjusted by inflation factor Show forest plot

28

8332

Risk Difference (M‐H, Fixed, 95% CI)

‐0.01 [‐0.02, 0.01]

Analysis 2.2

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 2 Mortality, all RCTs with results of cluster RCTs adjusted by inflation factor.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 2 Mortality, all RCTs with results of cluster RCTs adjusted by inflation factor.

3 Mortality, low or medium 'Risk of bias' RCTs Show forest plot

8

6249

Risk Difference (M‐H, Fixed, 95% CI)

‐0.00 [‐0.02, 0.01]

Analysis 2.3

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 3 Mortality, low or medium 'Risk of bias' RCTs.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 3 Mortality, low or medium 'Risk of bias' RCTs.

4 Length of stay, all RCTs Show forest plot

15

3834

Mean Difference (IV, Fixed, 95% CI)

‐1.12 [‐1.54, ‐0.70]

Analysis 2.4

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 4 Length of stay, all RCTs.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 4 Length of stay, all RCTs.

5 Length of stay, all RCTs with results of cluster RCTs adjusted by inflation factor Show forest plot

15

3834

Mean Difference (IV, Fixed, 95% CI)

‐1.22 [‐1.68, ‐0.76]

Analysis 2.5

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 5 Length of stay, all RCTs with results of cluster RCTs adjusted by inflation factor.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 5 Length of stay, all RCTs with results of cluster RCTs adjusted by inflation factor.

6 Length of stay, low or medium 'Risk of bias' RCTs only Show forest plot

6

1731

Mean Difference (IV, Fixed, 95% CI)

‐0.85 [‐1.38, ‐0.32]

Analysis 2.6

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 6 Length of stay, low or medium 'Risk of bias' RCTs only.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 6 Length of stay, low or medium 'Risk of bias' RCTs only.

Open in table viewer
Comparison 3. Adverse effects: Clinical outcomes of interventions targeting antibiotic choice

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Mortality for trial patients Show forest plot

11

7658

Risk Difference (M‐H, Fixed, 95% CI)

‐0.00 [‐0.02, 0.01]

Analysis 3.1

Comparison 3 Adverse effects: Clinical outcomes of interventions targeting antibiotic choice, Outcome 1 Mortality for trial patients.

Comparison 3 Adverse effects: Clinical outcomes of interventions targeting antibiotic choice, Outcome 1 Mortality for trial patients.

2 Length of stay for trial patients Show forest plot

7

2276

Mean Difference (IV, Fixed, 95% CI)

‐1.50 [‐2.16, ‐0.83]

Analysis 3.2

Comparison 3 Adverse effects: Clinical outcomes of interventions targeting antibiotic choice, Outcome 2 Length of stay for trial patients.

Comparison 3 Adverse effects: Clinical outcomes of interventions targeting antibiotic choice, Outcome 2 Length of stay for trial patients.

Open in table viewer
Comparison 4. Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Mortality for trial patients Show forest plot

18

9173

Risk Difference (M‐H, Fixed, 95% CI)

‐0.00 [‐0.01, 0.01]

Analysis 4.1

Comparison 4 Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure, Outcome 1 Mortality for trial patients.

Comparison 4 Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure, Outcome 1 Mortality for trial patients.

2 Length of stay for trial patients Show forest plot

8

1558

Mean Difference (IV, Fixed, 95% CI)

‐0.87 [‐1.42, ‐0.33]

Analysis 4.2

Comparison 4 Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure, Outcome 2 Length of stay for trial patients.

Comparison 4 Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure, Outcome 2 Length of stay for trial patients.

Open in table viewer
Comparison 5. Modifiers of intended effect: Comparison of enabling interventions with and without feedback

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Enablement with feedback Show forest plot

4

3747

Risk Difference (M‐H, Fixed, 95% CI)

0.19 [0.16, 0.22]

Analysis 5.1

Comparison 5 Modifiers of intended effect: Comparison of enabling interventions with and without feedback, Outcome 1 Enablement with feedback.

Comparison 5 Modifiers of intended effect: Comparison of enabling interventions with and without feedback, Outcome 1 Enablement with feedback.

2 Enablement without feedback Show forest plot

7

1827

Risk Difference (M‐H, Fixed, 95% CI)

0.13 [0.09, 0.17]

Analysis 5.2

Comparison 5 Modifiers of intended effect: Comparison of enabling interventions with and without feedback, Outcome 2 Enablement without feedback.

Comparison 5 Modifiers of intended effect: Comparison of enabling interventions with and without feedback, Outcome 2 Enablement without feedback.

Figure 1 Study flow diagram.
Figuras y tablas -
Figure 1

Figure 1 Study flow diagram.

Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.Blank sections in this graph are due to use of different ROB criteria for CBA, NRT and RCT versus ITS studies
Figuras y tablas -
Figure 2

Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.

Blank sections in this graph are due to use of different ROB criteria for CBA, NRT and RCT versus ITS studies

Forest plot of comparison: 1 Prescribing: RCTs of all interventions to reduce unnecessary prescribing, outcome: 1.1 Dichotomous outcomes, increase in desired practice.
Figuras y tablas -
Figure 3

Forest plot of comparison: 1 Prescribing: RCTs of all interventions to reduce unnecessary prescribing, outcome: 1.1 Dichotomous outcomes, increase in desired practice.

Forest plot of comparison: 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, outcome: 1.4 Continuous outcomes, duration of all antibiotic treatment (days).
Figuras y tablas -
Figure 4

Forest plot of comparison: 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, outcome: 1.4 Continuous outcomes, duration of all antibiotic treatment (days).

Forest plot of comparison: 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, outcome: 2.1 Mortality, all RCTs.
Figuras y tablas -
Figure 5

Forest plot of comparison: 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, outcome: 2.1 Mortality, all RCTs.

Forest plot of comparison: 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, outcome: 2.4 Length of stay, all RCTs.
Figuras y tablas -
Figure 6

Forest plot of comparison: 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, outcome: 2.4 Length of stay, all RCTs.

Meta‐regression by effect modifier for 29 RCTs. A positive value for Beta indicates enhanced intervention effect. One RCT had both enabling and restrictive components in the intervention (Strom 2010).
Figuras y tablas -
Figure 7

Meta‐regression by effect modifier for 29 RCTs. A positive value for Beta indicates enhanced intervention effect. One RCT had both enabling and restrictive components in the intervention (Strom 2010).

Forest plot of comparison 5: RCTs of enablement with and without feedback, outcome: 5.1 Enablement plus feedback.
Figuras y tablas -
Figure 8

Forest plot of comparison 5: RCTs of enablement with and without feedback, outcome: 5.1 Enablement plus feedback.

Forest plot of comparison 5: RCTs of enablement with and without feedback, outcome: 5.2 Enablement without feedback.
Figuras y tablas -
Figure 9

Forest plot of comparison 5: RCTs of enablement with and without feedback, outcome: 5.2 Enablement without feedback.

Meta‐regression by effect modifiers of intervention for 91 ITS studies. Outcome is effect on prescribing six months' postintervention. There are 16 studies with both enabling and restricting intervention components ().
Figuras y tablas -
Figure 10

Meta‐regression by effect modifiers of intervention for 91 ITS studies. Outcome is effect on prescribing six months' postintervention. There are 16 studies with both enabling and restricting intervention components (Figure 11).

Meta‐regression of prescribing outcome by effect modifiers for 29 ITS studies of interventions that included restriction.
Figuras y tablas -
Figure 11

Meta‐regression of prescribing outcome by effect modifiers for 29 ITS studies of interventions that included restriction.

Meta‐regression by effect modifier for 43 ITS studies of interventions that included enablement but not restriction. Outcome is effect on prescribing six months' postintervention. Note that four studies with feedback were not included in this analysis because they also included restriction.
Figuras y tablas -
Figure 12

Meta‐regression by effect modifier for 43 ITS studies of interventions that included enablement but not restriction. Outcome is effect on prescribing six months' postintervention. Note that four studies with feedback were not included in this analysis because they also included restriction.

Meta‐regression by effect modifiers for 34 microbial outcomes 12 months' postintervention from 26 ITS studies. The bars show the results for unadjusted versus adjusted analyses, the comparison for unplanned interventions is with planned interventions in both the unadjusted and adjusted analysis.CDI: Clostridium difficile infection
 GPC: infection with antibiotic‐resistant gram‐positive cocci
 GNB: infection with antibiotic‐resistant gram‐negative bacteriaOther infection control: 'Yes' means there were changes to infection control processes during the study period.
Figuras y tablas -
Figure 13

Meta‐regression by effect modifiers for 34 microbial outcomes 12 months' postintervention from 26 ITS studies. The bars show the results for unadjusted versus adjusted analyses, the comparison for unplanned interventions is with planned interventions in both the unadjusted and adjusted analysis.

CDI: Clostridium difficile infection
GPC: infection with antibiotic‐resistant gram‐positive cocci
GNB: infection with antibiotic‐resistant gram‐negative bacteria

Other infection control: 'Yes' means there were changes to infection control processes during the study period.

Meta‐regression by effect modifiers for 20 microbial outcomes 12 months' postintervention from 14 ITS studies of planned interventions that provided details about other infection control changes or interventions.CDI: Clostridium difficile infection
 GPC: infection with antibiotic‐resistant gram‐positive cocci
 GNB: infection with antibiotic‐resistant gram‐negative bacteriaOther infection control: 'Yes' means there were changes to infection control processes during the study period.
Figuras y tablas -
Figure 14

Meta‐regression by effect modifiers for 20 microbial outcomes 12 months' postintervention from 14 ITS studies of planned interventions that provided details about other infection control changes or interventions.

CDI: Clostridium difficile infection
GPC: infection with antibiotic‐resistant gram‐positive cocci
GNB: infection with antibiotic‐resistant gram‐negative bacteria

Other infection control: 'Yes' means there were changes to infection control processes during the study period.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 1 Dichotomous outcomes, increase in desired practice.
Figuras y tablas -
Analysis 1.1

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 1 Dichotomous outcomes, increase in desired practice.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 2 Dichotomous outcomes, all RCTs with results of cluster RCTs adjusted by inflation factor.
Figuras y tablas -
Analysis 1.2

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 2 Dichotomous outcomes, all RCTs with results of cluster RCTs adjusted by inflation factor.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 3 Dichotomous outcomes, low or medium 'Risk of bias' studies only.
Figuras y tablas -
Analysis 1.3

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 3 Dichotomous outcomes, low or medium 'Risk of bias' studies only.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 4 Continuous outcomes, duration of all antibiotic treatment (days).
Figuras y tablas -
Analysis 1.4

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 4 Continuous outcomes, duration of all antibiotic treatment (days).

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 5 Continuous outcomes, duration of all antibiotic treatment with results of cluster RCTs adjusted by inflation factor.
Figuras y tablas -
Analysis 1.5

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 5 Continuous outcomes, duration of all antibiotic treatment with results of cluster RCTs adjusted by inflation factor.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 6 Continuous outcomes, low or medium 'Risk of bias' studies only.
Figuras y tablas -
Analysis 1.6

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 6 Continuous outcomes, low or medium 'Risk of bias' studies only.

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 7 Continuous outcome, consumption of targeted antibiotic only, standardised mean reduction (original outcome cost, days or DDD).
Figuras y tablas -
Analysis 1.7

Comparison 1 Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 7 Continuous outcome, consumption of targeted antibiotic only, standardised mean reduction (original outcome cost, days or DDD).

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 1 Mortality, all RCTs.
Figuras y tablas -
Analysis 2.1

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 1 Mortality, all RCTs.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 2 Mortality, all RCTs with results of cluster RCTs adjusted by inflation factor.
Figuras y tablas -
Analysis 2.2

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 2 Mortality, all RCTs with results of cluster RCTs adjusted by inflation factor.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 3 Mortality, low or medium 'Risk of bias' RCTs.
Figuras y tablas -
Analysis 2.3

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 3 Mortality, low or medium 'Risk of bias' RCTs.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 4 Length of stay, all RCTs.
Figuras y tablas -
Analysis 2.4

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 4 Length of stay, all RCTs.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 5 Length of stay, all RCTs with results of cluster RCTs adjusted by inflation factor.
Figuras y tablas -
Analysis 2.5

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 5 Length of stay, all RCTs with results of cluster RCTs adjusted by inflation factor.

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 6 Length of stay, low or medium 'Risk of bias' RCTs only.
Figuras y tablas -
Analysis 2.6

Comparison 2 Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use, Outcome 6 Length of stay, low or medium 'Risk of bias' RCTs only.

Comparison 3 Adverse effects: Clinical outcomes of interventions targeting antibiotic choice, Outcome 1 Mortality for trial patients.
Figuras y tablas -
Analysis 3.1

Comparison 3 Adverse effects: Clinical outcomes of interventions targeting antibiotic choice, Outcome 1 Mortality for trial patients.

Comparison 3 Adverse effects: Clinical outcomes of interventions targeting antibiotic choice, Outcome 2 Length of stay for trial patients.
Figuras y tablas -
Analysis 3.2

Comparison 3 Adverse effects: Clinical outcomes of interventions targeting antibiotic choice, Outcome 2 Length of stay for trial patients.

Comparison 4 Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure, Outcome 1 Mortality for trial patients.
Figuras y tablas -
Analysis 4.1

Comparison 4 Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure, Outcome 1 Mortality for trial patients.

Comparison 4 Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure, Outcome 2 Length of stay for trial patients.
Figuras y tablas -
Analysis 4.2

Comparison 4 Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure, Outcome 2 Length of stay for trial patients.

Comparison 5 Modifiers of intended effect: Comparison of enabling interventions with and without feedback, Outcome 1 Enablement with feedback.
Figuras y tablas -
Analysis 5.1

Comparison 5 Modifiers of intended effect: Comparison of enabling interventions with and without feedback, Outcome 1 Enablement with feedback.

Comparison 5 Modifiers of intended effect: Comparison of enabling interventions with and without feedback, Outcome 2 Enablement without feedback.
Figuras y tablas -
Analysis 5.2

Comparison 5 Modifiers of intended effect: Comparison of enabling interventions with and without feedback, Outcome 2 Enablement without feedback.

Summary of findings for the main comparison. Effects of interventions to improve use of antibiotics on prescribing, clinical outcomes, adverse events, and effect modifiers (heterogeneity)

Patient or population: adults or children undergoing inpatient antibiotic prophylaxis or treatment

Settings: mainly high‐income countries (North America or Western Europe)

Intervention: any intervention targeting healthcare professionals that aimed to improve antibiotic prescribing to hospital inpatients

Comparison: usual care (varied across studies)

Effectiveness: prescribing outcomes from RCTs

Outcomes

Absolute effect*

No of participants

(No of studies)

Certainty of the evidence (GRADE)

Comments

Without intervention

With intervention

Proportion of participants who were treated according to antibiotic prescribing guidelines

Follow‐up to end of study

43 per 100

58 per 100

23,394 participants

(29 RCTs)

⊕⊕⊕⊕
High

We have graded the certainty of evidence as high because heterogeneity was explained by prespecified effect modifiers (see below). The intervention effect varied between the studies, but the direction of effect was consistent. Restricting the analysis to studies at low risk of bias gave a similar result (RD 11%, 95% CI 10% to 12%).

Difference: 15 more participants per 100 (95% CI 15 to 23) received appropriate treatment following intervention.

Duration of all antibiotic treatment

11.0 days

9.1 days

3318 participants

(14 RCTs)

⊕⊕⊕⊕
High

Difference: 1.95 fewer days per participant (95% CI 2.22 to 1.67)

Mortality

Follow‐up to end of study

11 per 100

11 per 100

15,827 participants

28 (RCTs)

⊕⊕⊕⊝1
Moderate

Mortality and length of stay were measured to determine the impact of reduced antibiotic use on clinical outcomes. The results were similar for studies that targeted antibiotic choice or exposure.

Only 1 of the interventions in the RCTs with mortality or length‐of‐stay outcomes had a restrictive component (Singh 2000). This evidence is therefore at high risk of indirectness because 7 studies in the next section of the table (see below) raise concerns about the safety of restrictive interventions. Moreover, the ITS studies showed that restrictive components were included in 42 (34%) of 123 hospital interventions.

Difference: 0 more deaths per 100 participants (95% CI 1 to 0 fewer)

Mean length of hospital stay per participant

12.9 days

11.8 days

3834 participants

15 (RCTs)

⊕⊕⊕⊝1
Moderate

Difference: 1.1 fewer days per participant (95% CI 1.5 to 0.7 fewer)

Delay in treatment

Restrictive interventions increased the risk of delay in all 3 studies. The risk to patients resulted in termination of the RCT by the Trial Monitoring Committee.

1 RCT, 2 cohort

⊕⊕⊝⊝2
Low

The evidence from these 7 studies of unintended consequences raises concerns about the directness of the evidence of safety from the 29 RCTs in the previous section of the table (see above).

Negative professional culture

Loss of trust in infection specialists because of failure to record approvals for restricted drugs or provide warning about stopping treatment

Misleading or inaccurate information from prescribers in order to meet criteria for restricted drugs. In 1 hospital, misdiagnosis of hospital‐acquired infection was large enough to trigger an outbreak investigation.

1 case control, 2 cohort, 1 qualitative

⊕⊕⊖⊖3
Low

Effect modifiers (heterogeneity) for immediate effect of intervention on prescribing outcomes:
impact of behaviour change functions (enablementor restriction) and additional impact of feedback, RCTs and ITS studies. A positive value for Beta means the modifier is associated with increased effect

Effect modifier

Adjusted effect in meta‐regression
Beta
(95% CI)

Number of studies

Certainty of the evidence (GRADE)

Comments

Enablement

15.12

(8.45 to 21.8)

29 RCTs

⊕⊕⊕⊕
High

The effect of enablement and restriction is similar in the RCTs and ITS studies. Of the 29 RCTs, only 8 (31%) of interventions were hospital‐wide, the majority being in single units. In contrast, 64 (70%) of the interventions in ITS studies were hospital‐wide.

12.86

(4.11 to 21.6)

91 ITS

Restriction

34.91

(13.52 to 56.29)

29 RCTs

⊕⊕⊕⊕
High

24.69

(13.74 to 35.64)

91 ITS

Addition of feedback to enablement

10.88

(7.16 to 19.32)

23 RCTs

⊕⊕⊕⊝2
Moderate

Feedback was included in 4 (17%) of 23 RCTs and 20 (47%) of 43 ITS studies with interventions that included enablement. There were not enough interventions with goal setting and action planning to analyse as effect modifiers.

15.63

(0.56 to 30.70)

43 ITS

Addition of enablement to restriction

38.36

(18.94 to 57.78)

29 ITS

⊕⊕⊖⊖3
Low

Enablement was included in 13 (45%) of 29 ITS studies with restrictive interventions.

*The risk WITHOUT the intervention is based on the median control group risk across studies. The corresponding risk WITH the intervention (and the 95% confidence interval for the difference) is based on the overall relative effect (and its 95% confidence interval).
CI: confidence interval; ITS: interrupted time series; RCT: randomised controlled trial; RD: risk difference

GRADE Working Group grades of evidence
High certainty: Further research is very unlikely to change our confidence in the estimate of effect.
Moderate certainty: Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate.
Low certainty: Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate.
Very low certainty: We are very uncertain about the estimate.

Details of five GRADE criteria for all outcomes from RCTs are in Appendix 2.

1We downgraded the evidence to moderate because of indirectness.
2We downgraded the evidence because most studies are non‐randomised studies.
3We graded the evidence as low because it is all from non‐randomised studies.
4We graded the evidence as very low because it is all from non‐randomised studies and there was too much heterogeneity for reliable evidence synthesis.

Figuras y tablas -
Summary of findings for the main comparison. Effects of interventions to improve use of antibiotics on prescribing, clinical outcomes, adverse events, and effect modifiers (heterogeneity)
Table 1. Definition of behaviour change techniques and intervention functions

Intervention Function

Definition

Intervention components

Education

Increasing knowledge or understanding

Educational meetings;

Dissemination of educational materials;

Educational outreach

Persuasion

Using communication to induce positive or negative feelings or to stimulate action

Educational outreach by academic detailing or review and recommend change

Restriction

Using rules to reduce the opportunity to engage in the target behaviour (or increase the target behaviour by reducing the opportunity to engage in competing behaviours)

Restrictive

Environmental restructuring

Changing the physical context

Reminders (physical) such as posters, pocket‐size or credit card‐size summaries or on laboratory test reports;

Structural (e.g. new laboratory tests or rapid reporting of results)

Enablement

Increasing means/reducing barriers to increase capability or opportunity

Audit and feedback;

Decision support through computerised systems or through circumstantial reminders that were triggered by actions or events related to the targeted behaviour;

Educational outreach by review and recommend change

Figuras y tablas -
Table 1. Definition of behaviour change techniques and intervention functions
Table 2. Unintended consequences of ITS studies: mortality*

Study

Prescribing target

Restriction

Design of analysis

Effect estimate

95% CI

Lee 2014

Choice of drug

No

Cohort

Incidence rate ratio 1.1

0.9 to 1.5

Popovski 2015

Choice of drug

No

Cohort

Increase by 1.4%

‐1.2% to 4.1%

Wang 2014

Choice of drug

Yes

ITS, segmented regression

Change in slope ‐0.0172

No data

Yoon 2014

Choice of drug

Yes

Cohort

+0.43 per 1000 OBD

No data

*Mortality was measured in all patients in the hospital rather than just those patients who were the targets of the interventions.

CI: confidence interval
ITS: interrupted time series
OBD: occupied bed day

Figuras y tablas -
Table 2. Unintended consequences of ITS studies: mortality*
Table 3. Unintended consequences of ITS studies: length of stay*

Study

Prescribing target

Restrictive

Design of analysis

Effect estimate

95% CI

Mittal 2014

Exposure, % treated

No

Cohort

‐0.5 days

No data

Skaer 1993

Choice of drug

No

Cohort

‐0.1 days

‐0.49 to +0.29

*Length of stay was measured in all patients in the hospital rather than just those patients who were the targets of the interventions.

CI: confidence interval
ITS: interrupted time series

Figuras y tablas -
Table 3. Unintended consequences of ITS studies: length of stay*
Table 4. Unintended consequences of ITS studies: other

Study

Prescribing target

Design of analysis

Effect measure

Effect estimate

95% CI

Bell 2014

Antibiotic choice

ITS, segmented regression

Risk of postoperative acute kidney injury

Increase 98%

93.8% to 94.2%

Van Kasteren 2005

Exposure, duration

Cohort

Surgical‐site infection

Decrease 0.8%

‐2.2% to 0.6%

Volpe 2012

Time to first antibiotic dose

Cohort

Left without being seen rate

Decrease 0.4%

No data

CI: confidence interval
ITS: interrupted time series

Figuras y tablas -
Table 4. Unintended consequences of ITS studies: other
Table 5. Unintended consequences studies (case control, cohort, or qualitative)

Study

Design

Patients

Intended target

Unintended consequence

Effect estimate

95% CI

Interventions with a restrictive component

Baysari 2013

Qualitative

36 physicians

Reduce unnecessary use of restricted antibiotics

Inaccurate feedback

Not quantified; qualitative study

Calfee 2003

Case control

Not clear

Increase in physician‐based diagnosis of nosocomial infection

No denominator data

Connor 2007

Cohort

120

Failure to warn prescribers about discontinuation

Duvoisin 2014

Cohort

222

Reduce unnecessary laboratory tests

Delay in TFAD (HR > 1 shows delay less likely in intervention period)

Multivariate HR 1.56

1.17 to 2.07

LaRosa 2007

Cross‐sectional

15,440

Reduce unnecessary use of restricted antibiotics

Orders for restricted antibiotics (% all orders) from 10 to 11 pm vs all other hours

Cohort

360

% appropriate orders 10 to 11 pm vs 9 to 10 pm

‐23.7%

‐31.8% to ‐15.5%

Linkin 2007

Cohort

200

Risk of inaccurate information in orders judged inappropriate vs appropriate

OR 2.2

1.0 to 4.4

Winters 2010

Cohort

3251

Risk of 1‐hour delay in TFAD

OR 1.5

1.2 to 1.8

Risk of 2‐hour delay in TFAD

OR 1.8

1.4 to 2.2

Interventions with no restrictive component

Friedberg 2009

Cohort

13,042

Reduce time to first antibiotic dose for patients with community‐acquired pneumonia

% CAP diagnoses

1% increase

No denominator data

Kanwar 2007

Cohort

518

% correct CAP diagnoses

‐7.9% decrease

‐15.4% to ‐0.4%

Welker 2008

Cohort

548

% correct CAP diagnoses

‐16.0% decrease

‐7.6% to ‐24.4%

CAP: community‐acquired pneumonia
CI: confidence interval
HR: hazard ratio
OR: odds ratio
TFAD: time to the first antibiotic dose

Figuras y tablas -
Table 5. Unintended consequences studies (case control, cohort, or qualitative)
Table 6. Summary of intervention components for 29 RCTs (Analysis 1.1; Figures 3 and 7) and 91 ITS studies (Figure 10)

Intervention function and components

RCT

ITS

Enablement

24

studies

59

studies

Number of enabling or restrictive intervention components

27

76

Studies with > 1 Enabling intervention component

2

8%*

19

32%*

Audit and feedback

4

17%

24

41%

Computerised decision support

1

4%

3

5%

Circumstantial reminders

16

67%

18

31%

Review and recommend change

6

25%

31

53%

Restriction

2

studies

29

studies

Number of Restrictive intervention components

3

41

Studies with > 1 Restrictive intervention component

1

50%

10

34%

Expert approval

1

50%

18

62%

Compulsory order form

1

50%

7

24%

Removal

0

10

34%

Review and make change

1

50%

6

21%

No Enablement or Restriction

4

studies

18

studies

Number of intervention components

6

25

Studies with > 1 intervention component

2

50%

6

33%

Educational materials or meetings

3

75%

16

89%

Educational outreach (academic detailing)

1

25%

6

33%

Physical reminders

1

25%

2

11%

Structural intervention

1

25%

1

6%

*The denominator for all percentages is the number of studies for each intervention function. One RCT, Strom 2010, and 16 ITS studies (Figure 11) included both enabling and restrictive intervention components.

ITS: interrupted time series
RCT: randomised controlled trial

Figuras y tablas -
Table 6. Summary of intervention components for 29 RCTs (Analysis 1.1; Figures 3 and 7) and 91 ITS studies (Figure 10)
Table 7. Data from 5 studies about the effect of removal of interventions. The intended effect of all interventions was reduction in unnecessary antibiotic use

Study

Intervention function

Intervention effect (95% CI)

Time intervention was in place

Effect of removal (95% CI)

Kallen 2009

Restriction

‐87.5%

‐115.4 to ‐59.7

6 months

398.9%

238.2 to 559.5

Kim 2008

Restriction

‐23.1%

‐53.7 to +7.4

9 months

6.0%

‐23.4 to 35.4

Standiford 2012

Enablement

‐28.6%

‐46.5 to ‐10.6

7 years

31.0%

6.8 to 55.3

Himmelberg 1991

Restriction

No data

“long‐standing”

301.2%

230.9 to 371.5

Skrlin 2011

Restriction

2 years

255.8%

194.7 to 316.9

CI: confidence interval

Figuras y tablas -
Table 7. Data from 5 studies about the effect of removal of interventions. The intended effect of all interventions was reduction in unnecessary antibiotic use
Table 8. Randomised controlled trials with microbial outcomes

Study

Design

Microbial outcome

Reason not in meta‐analysis

Annane 2013

RCT

Colonisation with MRSA (nasal swab) and GNRB (rectal swabs)

Not comparable with any other RCT

Bouza 2007

RCT

Number of cases of Clostridium difficile

Not in prescribing meta‐analysis

Lesprit 2013

RCT

Secondary infection and/or colonisation with multidrug‐resistant bacteria in the 6 months following randomisation

Not in prescribing meta‐analysis. It is impossible to assess the impact of the intervention on colonisation or infection with bacteria resistant to specific antibiotics.

Palmay 2014

RCT

CDI and infection with antibiotic resistant organisms cases/1000 OBD

Not in prescribing meta‐analysis

Singh 2000

RCT

Number of participants with "antimicrobial resistance and/or superinfections" from randomisation until discharge from hospital

It is impossible to assess the impact of the intervention on colonisation or infection with bacteria resistant to specific antibiotics.

CDI: Clostridium difficile infection
GNRB: gram‐negative resistant bacteria
MRSA: methicillin‐resistant Staphylococcus aureus
OBD: occupied bed day
RCT: randomised controlled trial

Figuras y tablas -
Table 8. Randomised controlled trials with microbial outcomes
Table 9. Microbial outcomes from 26 ITS studies from the prescribing meta‐analysis that include reliable data about prescribing outcomes at 6 months and microbial outcomes at 12 months postintervention

Prescribing target

Microbial outcome

N

Study ID

Cephalosporins

GNRB

8

Grohs 2014; Kim 2008; Knudsen 2014; Lee 2007; McNulty 1997; Meyer 2009; Petrikkos 2007; Tangdén 2011

MRSA

1

May 2000

Carbapenems

GNRB

1

Goldstein 2009

Fluoroquinolones

GNRB

3

Cook 2011b; Lafaurie 2012; Willemsen 2010

MRSA

1

Lafaurie 2012

High‐risk antibiotics

CDI

6

Aldeyab 2012; Chan 2011; Dancer 2013; Fowler 2007; Talpaert 2011; Valiquette 2007

GNRB

4

Buising 2008a; Chan 2011; Dancer 2013; Liebowitz 2008

MRSA

6

Aldeyab 2014; Ananda‐Rajah 2010; Chan 2011; Dancer 2013; Fowler 2007; Liebowitz 2008

Total antibiotic use

CDI

2

Cook 2011a; Jump 2012

MRSA

1

Cook 2011a

Vancomycin

VRE

1

Lautenbach 2003

Total microbial

34*

*Some studies had more than one microbial outcome, so the total is 34 microbial outcomes from 26 studies.

CDI: Clostridium difficile infection
GNRB: gram‐negative resistant bacteria
ITS: interrupted time series
MRSA: methicillin‐resistant Staphylococcus aureus
VRE: vancomycin‐resistant enterococci

Figuras y tablas -
Table 9. Microbial outcomes from 26 ITS studies from the prescribing meta‐analysis that include reliable data about prescribing outcomes at 6 months and microbial outcomes at 12 months postintervention
Comparison 1. Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Dichotomous outcomes, increase in desired practice Show forest plot

29

23394

Risk Difference (M‐H, Fixed, 95% CI)

0.15 [0.14, 0.16]

2 Dichotomous outcomes, all RCTs with results of cluster RCTs adjusted by inflation factor Show forest plot

29

5802

Risk Difference (M‐H, Fixed, 95% CI)

0.17 [0.15, 0.19]

3 Dichotomous outcomes, low or medium 'Risk of bias' studies only Show forest plot

15

13086

Risk Difference (M‐H, Fixed, 95% CI)

0.11 [0.10, 0.12]

4 Continuous outcomes, duration of all antibiotic treatment (days) Show forest plot

14

3318

Mean Difference (IV, Fixed, 95% CI)

‐1.95 [‐2.22, ‐1.67]

5 Continuous outcomes, duration of all antibiotic treatment with results of cluster RCTs adjusted by inflation factor Show forest plot

14

3318

Mean Difference (IV, Fixed, 95% CI)

‐1.95 [‐2.23, ‐1.67]

6 Continuous outcomes, low or medium 'Risk of bias' studies only Show forest plot

3

755

Mean Difference (IV, Fixed, 95% CI)

‐3.06 [‐3.76, ‐2.37]

7 Continuous outcome, consumption of targeted antibiotic only, standardised mean reduction (original outcome cost, days or DDD) Show forest plot

4

1053

Std. Mean Difference (IV, Fixed, 95% CI)

‐0.25 [‐0.37, ‐0.13]

Figuras y tablas -
Comparison 1. Effectiveness: Prescribing outcomes from RCTs of interventions to reduce unnecessary antibiotic use
Comparison 2. Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Mortality, all RCTs Show forest plot

28

15827

Risk Difference (M‐H, Fixed, 95% CI)

‐0.00 [‐0.01, 0.00]

2 Mortality, all RCTs with results of cluster RCTs adjusted by inflation factor Show forest plot

28

8332

Risk Difference (M‐H, Fixed, 95% CI)

‐0.01 [‐0.02, 0.01]

3 Mortality, low or medium 'Risk of bias' RCTs Show forest plot

8

6249

Risk Difference (M‐H, Fixed, 95% CI)

‐0.00 [‐0.02, 0.01]

4 Length of stay, all RCTs Show forest plot

15

3834

Mean Difference (IV, Fixed, 95% CI)

‐1.12 [‐1.54, ‐0.70]

5 Length of stay, all RCTs with results of cluster RCTs adjusted by inflation factor Show forest plot

15

3834

Mean Difference (IV, Fixed, 95% CI)

‐1.22 [‐1.68, ‐0.76]

6 Length of stay, low or medium 'Risk of bias' RCTs only Show forest plot

6

1731

Mean Difference (IV, Fixed, 95% CI)

‐0.85 [‐1.38, ‐0.32]

Figuras y tablas -
Comparison 2. Adverse effects: Clinical outcomes from RCTs of interventions to reduce unnecessary antibiotic use
Comparison 3. Adverse effects: Clinical outcomes of interventions targeting antibiotic choice

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Mortality for trial patients Show forest plot

11

7658

Risk Difference (M‐H, Fixed, 95% CI)

‐0.00 [‐0.02, 0.01]

2 Length of stay for trial patients Show forest plot

7

2276

Mean Difference (IV, Fixed, 95% CI)

‐1.50 [‐2.16, ‐0.83]

Figuras y tablas -
Comparison 3. Adverse effects: Clinical outcomes of interventions targeting antibiotic choice
Comparison 4. Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Mortality for trial patients Show forest plot

18

9173

Risk Difference (M‐H, Fixed, 95% CI)

‐0.00 [‐0.01, 0.01]

2 Length of stay for trial patients Show forest plot

8

1558

Mean Difference (IV, Fixed, 95% CI)

‐0.87 [‐1.42, ‐0.33]

Figuras y tablas -
Comparison 4. Adverse effects: Clinical outcomes of interventions targeting antibiotic exposure
Comparison 5. Modifiers of intended effect: Comparison of enabling interventions with and without feedback

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Enablement with feedback Show forest plot

4

3747

Risk Difference (M‐H, Fixed, 95% CI)

0.19 [0.16, 0.22]

2 Enablement without feedback Show forest plot

7

1827

Risk Difference (M‐H, Fixed, 95% CI)

0.13 [0.09, 0.17]

Figuras y tablas -
Comparison 5. Modifiers of intended effect: Comparison of enabling interventions with and without feedback