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Cochrane Database of Systematic Reviews Protocol - Intervention

Mobile phone messaging for communicating results of medical investigations

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Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the effects of mobile phone messaging for communicating results of medical investigations to patients, on provider and patient acceptability, satisfaction, safety, costs and readiness to use the intervention.

Background

This review is part of suite of Cochrane reviews that examine the role of mobile phone messaging in health care (see Car 2008; de Jongh 2008; Vodopivec‐Jamsek 2008)

In our preliminary searches of the literature we have identified four distinct, although related areas of healthcare communication for which mobile phone messaging is being utilised. These reflect areas of communication for which previously other modes of distant communication have been used, such as telephone or mail. Our division of studies into the following four areas in reviews (mobile phone messaging for preventive health care and for provision of healthcare‐related information (Vodopivec‐Jamsek 2008); for communicating results of medical investigations; as reminders for attendance at scheduled healthcare appointments (Car 2008); and for facilitating self‐management of long‐term illnesses (de Jongh 2008) is thus largely on pragmatic grounds, although we believe this division is also theoretically defensible according to complexity and nature of communication. We were unable to identify any literature that would provide a stronger theoretical framework for the division of reviews.

Communicating the results of medical investigations can be defined as the transmission of the results of medical tests used for screening, diagnosis, prognosis and monitoring of disease. Some examples of medical investigations are: blood, urine and stool tests; medical imaging; and medical radiology. Although the most common route of communication is from the health provider to the patient, other routes are possible to enhance access, such as from a laboratory to a rural clinic health professional. Modes of communication include face‐to‐face visits, calls via telephone or mobile phone, and through web‐based health records, email, and text messaging.

Description of the intervention

Global mobile phone penetration is increasing rapidly, and at a faster rate in China, India and Africa, with 3.3 billion users (equivalent to half the global population) reached on 29 November 2007 (Reuters 2007). The penetration rates are 70% to 90% in high‐income countries, with a similar rate of increase across all socioeconomic groups (Atun 2006). Features such as ubiquity, mobility, direct and instantaneous access and direct communication offer the possibility of using mobile phones for health information transfer (Atun 2006). Most digital mobile phones offer Short Message Service (SMS) (also known as text messages), and Multimedia Message Service (MMS) for transmitting graphics, video clips and sound files. The terms text message, text, or txt are more commonly used in North America, the UK, Spain and the Philippines, while most other countries use the term SMS. Text messaging has developed rapidly into a new communication medium, particularly among young adults. These short messages, where up to 160 characters of text are sent from the internet or a mobile phone to one or several mobile phones, could provide an important, inexpensive delivery medium for communicating results of medical investigations.

How the intervention might work

Text messaging interventions can be used to enhance self‐efficacy (e.g. reminders, feedback on treatment success), to provide a form of social support (from peers and health professionals) and to establish social networks (support groups, peer‐to‐peer networks). These interventions, through increased self‐efficacy (Bandura 1977; Bandura 1982) and support mechanisms (Cohen 1985; Cobb 2002; Christakis 2004), may influence health behaviours and enhance self‐management of chronic illnesses.

For communicating results of medical investigations, six possible modes of communication are: face‐to‐face, postal, call to landline, call to mobile, via web‐based electronic health records and SMS/MMS. Basic characteristics and comparison of alternative modes of communication are outlined in Table 1 (Revised from Atun 2006). Effective communication involves accurate and timely transmission of the result to the correct recipient, taking privacy and confidentiality into account, and using strategies to minimise misunderstanding or misinterpretation of the result. The provider should also ensure that appropriate follow‐up actions are taken once the result is known, such as further investigation, change of treatment, or setting a new date set for review.

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Table 1. Characteristics of communication modes

Face‐to‐face

Postal Letter

Call to Landline

Call to Mobile

Web Based (EHR)

E‐mail

SMS / MMS

Immediacy

Slow: Requires a visit to provider.

Slow: 2 days

Immediate:
If person at home. Return call may be necessary.

Immediate:
If person answers (more likely than landline).
Return call may be necessary.

Immediate:

Immediate
Or stored

Immediate
Or stored

Privacy and Confidentiality

High:
Personal communication.

High:
Personally addressed

Low: Confidentiality prevents message being left as others may answer or retrieve it.

High:
Personal device enables possibility of message being left.

Moderate:
Personal / public device?

Moderate:
Personal / public device?

High if
Personal device.

Likelihood of misinterpretation

Low

Moderate

Low:
Patient can request immediate clarification.

Low:
Patient can request immediate clarification.

Moderate

Moderate

Moderate

Delivery confirmation

N/A

Yes:
at significant expense.

Unnecessary if call answered. No if message left.

Unnecessary if call answered. No if message left.

N/A

Yes

Yes

Cost

High

Moderate

Low

Moderate

Low

Low

Low

Traditional approaches to communicating results of medical investigations and diagnoses to patients often involve the patients visiting the healthcare provider and collecting the results in person. Particularly in circumstances where visiting the clinician is inconvenient for the patient, where there are significant transportation costs and/or if the patient's health status is poor, SMS / MMS interventions are likely to result in reduced waiting times and costs to inform patients, increased convenience and satisfaction, and improved access to services (Lovitt 2005; Pal 1998). Sending results by SMS/MMS is faster than by face‐to‐face or postal communication, and adheres to privacy and confidentiality requirements if the phone is a personal device.

One study related to patient preferences regarding notification of test results identified privacy, responsiveness and interactive feedback, convenience, timeliness, and provision of details as patients' main concerns (Baldwin 2005). Results on preferences for particular modes of communication were mixed (Baldwin 2005; Lin 2005; Meza 2000; Schofield 1994). With regard to newer technologies, studies have reported positive responses to communicating test results using web messaging and electronic health records (Hassol 2004; Kleiner 2002; Liederman 2003; Lin 2005; Ralston 2007).

Some applications of SMS/MMS technology reported to date in high‐income countries include: communicating the results of in‐vitro diagnostic tests, such as blood or microbiology tests (Bradbeer 2003); and radiological imaging such as breast cancer screening (Lamont 2005). In low income countries, the applications are potentially more diverse, as there are greater barriers to accessing healthcare facilities. Some applications reported to date include sending results to clinics in rural areas more efficiently, and expediting the communication of occupational health examination results of foreign workers to their employers (Atun 2006).

Acceptability and risks of the intervention

Issues regarding mobile phone applications in health care include incomplete coverage of mobile networks across regions, lack of standards, and possible information overload (Adler 2007). There is also a mismatch between mobile phone penetration and morbidity patterns: mobile phone use decreases with age, whereas morbidity increases with age, with the gap being more evident in relatively advanced applications such as SMS/MMS. (Atun 2006b; DoCS 2006). Given this mismatch, mobile phone interventions are more likely to benefit younger age groups, and may add value to health provision if used as a complementary technology, or for specific interventions targeted at young people. Mobile phone applications usually provide privacy in health information transfer; however, privacy may not be ensured if the phone is shared, or generally used in a public space (e.g. a work or home environment); a situation more common in low income settings.

Possible disadvantages of using the SMS technology in particular include the risk of inaccurate data input and this inaccurate data being acted upon (Norwell 2003); misunderstanding or misinterpretation of the data; and difficulties in reading for those with poor vision. Mobile phone messaging technology is intended to support and complement the process of care delivery. A possible threat of the technology is that it may be misinterpreted by providers as an end point to their responsibilities within the care delivery process. Providers may believe that their work is done once the message is sent, which may result in inadequate follow‐up of patients after the intervention. SMS technology cannot capture the verbal and non‐verbal cues that may also influence the context and therefore the interpretation of the message. Data protection, confidentiality and disclosure are other key issues, as are the psychological and social impacts of using the mobile phone in this way.

Failures or delays in message delivery are rare but possible; however, harm is unlikely as senders are usually notified instantly in cases where there was a transmission problem. There may be additional monetary and time costs, as backup systems may be needed.

Why it is important to do this review

Mobile phone messaging is an important new means of human communication, even in low income countries. A recent literature review on the uses of mobile phones in health care has demonstrated the wide application and potential of mobile phones to increase access to health care; enhance efficiency of service delivery; improve diagnosis, treatment and rehabilitation of illnesses; and support public health programmes (Atun 2006). In particular, mobile phones have enabled certain population segments (such as teenage girls and young adult males) that are not typical users of health services to remotely access care providers for advice. SMS/MMS messaging has, for instance, been used to: provide appointment reminders (Bos 2005); improve patient compliance with their medications (Fairley 2003; Marquez 2004; Vilella 2004); monitor chronic conditions (Ferrer‐Roca 2004; Kwon 2004; Ostojic 2005); and provide psychological support (Bauer 2003; Franklin 2003). Mobile phones have also been used in managing communicable diseases (e.g. to facilitate contact tracing and partner notification for sexually transmitted illnesses (Newell 2001)), and in health promotion (e.g. in smoking cessation programmes (Obermayer 2004; Rodgers 2005)). Limited studies also point to potential economic benefits of mobile phone use in healthcare delivery.

Although there is some evidence on the use and effectiveness of mobile phones in healthcare delivery, answers to questions regarding the implementation of SMS technologies in routine care, such as their impact on patient‐related outcomes or on the processes of healthcare delivery, are unclear. Given the topical nature of mobile phone messaging, we want to undertake this review to identify answers to these questions and directions for future research. This review will also complement available studies on use of telephone consultations (Car 2003), email (Car 2004; Car 2004b) and personal digital assistants (PDAs) (Baumgart 2005) in health care, and forthcoming parallel Cochrane reviews by these authors on mobile phone messaging for other purposes than that which is the focus of this review (Car 2008; de Jongh 2008; Vodopivec‐Jamsek 2008).

Objectives

To assess the effects of mobile phone messaging for communicating results of medical investigations to patients, on provider and patient acceptability, satisfaction, safety, costs and readiness to use the intervention.

Methods

Criteria for considering studies for this review

Types of studies

Randomised controlled trials (RCTs), quasi‐randomised controlled trials (QRCTs), controlled before and after studies (CBAs), and interrupted time series (ITS) with at least three time points before and after the intervention.

We consider including QRCT, CBA and ITS designs, as preliminary literature searching indicates a scarcity of RCTs of text messaging interventions. However, if a sufficient number of well‐conducted RCTs is identified (upon which we can draw reliable conclusions), we will exclude other study designs during the review stage. If all study designs are included, we will perform a sensitivity analysis to assess whether the results change by including non‐RCT designs.

Types of participants

We will consider all study participants regardless of age, gender and ethnicity, as well as all types and stages of diseases. We will include studies in all settings, i.e. primary care settings (services of primary health care), outpatient settings (outpatient clinics), community settings (public health services) and hospital settings. We will not exclude studies according to the type of healthcare provider (e.g. nurse, doctor, allied staff).

Types of interventions

We will include interventions that use Short Messaging Service (SMS or 'text messaging) or Multimedia Message Service (MMS) messaging in communicating results of all medical tests, regardless of the purpose of the test (screening, diagnostic, guide to treatment, monitoring etc.). The SMS or MMS messaging needs to be between a healthcare provider (either in person or automated) or a 'treatment buddy' and patient, regardless of who sends the first SMS.

The review will not include interventions communicating results to people other than those for whom the medical investigation has been performed (e.g. partner notifications) or between two healthcare providers, such as from a laboratory to a rural health clinic. We will exclude studies in which SMS/MMS is a part of a multifaceted intervention, as it will not be possible to separate the effects of messaging alone.

We will make comparisons between outcomes of mobile phone messaging and no intervention, as well as other modes of communication such as face‐to‐face, postal letters, calls to landline or mobile telephones, e‐mail or via electronic health records; and if applicable, automated versus personal text messaging.

Types of outcome measures

A number of processes and outcomes may be affected by interventions that aim to enhance and/or facilitate the communication between patients and healthcare providers using mobile phone messaging.

Primary outcomes of interest are whether the text message has been understood and acted upon correctly by the patient as meant by the healthcare provider and whether text messaging was an appropriate mode of communication.

To evaluate whether the text message was acted upon correctly, outcomes regarding patients' health status and well‐being (including physiological measures, e.g. blood pressure; biomarkers or clinical progression; clinical assessments, e.g. wound healing; patient self‐reports of symptom resolution or quality of life; patient self‐esteem; adoption of lifestyle behaviours) are relevant. Short term responses to the test result and intervention, including actions taken by the patients to improve their health status and well‐being (such as making a follow‐up appointment), are also included as primary outcome measures.

To evaluate whether text messaging was an appropriate mode of communication, the outcomes listed below are relevant:

  • Patient / healthcare consumer / carer's or healthcare providers' evaluation of the communication mode (including impact on self‐efficacy and support, satisfaction, availability, convenience, readiness to use and timeliness);

  • Patient and/or healthcare providers' use of resources following intervention (including time, health care or monetary resources);

  • Harm or adverse effects regarding the communication mode (e.g. breach of confidentiality, failure or delays in message delivery);

  • Costs and cost‐effectiveness.

We will also record data related to the medical setting and clinical context of patients to assess any changes in outcomes within that context.

Search methods for identification of studies

We will search the following electronic databases:

  • The Cochrane Central Register of Controlled Trials (CENTRAL) (Latest issue)

  • EMBASE (1993 to present)

  • PubMed (incorporating MEDLINE) (1993 to present)

  • Health Star (1993 to present)

  • PsycINFO (1993 to present)

  • CINAHL (1993 to present)

  • LILACS (1993 to present)

  • African Trials Register (1993 to present)

  • African Health Anthology (1993 to present)

We have included LILACS, African Trials Register and Health Anthology because preliminary literature searches indicate that text messaging applications are increasingly used in low‐ and middle‐income regions.

For grey literature we will search:

  • Proceedings from AMIA and MEDNET Congresses

  • TrialsCentralTM (www.trialscentral.org)

  • WHO Clinical Trial Search Portal (www.who.int/trialsearch)

  • Current Controlled Trials (www.controlled‐trials.com)

  • Dissertation Abstracts International

We will not handsearch key medical informatics or telemedicine journals as they are indexed in the databases specified above.

We will try to identify additional studies by searching the reference lists of included studies and by citation tracking of key articles. We will contact study authors, where possible, for further information on their studies as appropriate. We will ask the lead authors of included studies if they are aware of any other published or ongoing studies that would meet our inclusion criteria.

We will search for studies in all languages, published since 1993 (as the first commercial SMS message was sent in December 1992 (Wikipedia 2007)).

We will use a common search strategy for all four reviews, and will allocate relevant studies to their respective review for quality appraisal and data extraction. A study may be relevant to, and included in, more than one review.

The strategy for MEDLINE (Ovid) is given at Appendix 1 and will be tailored to the above databases.

Data collection and analysis

Selection of studies
All review authors will be involved in the selection process. Two review authors will independently assess the potential relevance of all titles and abstracts identified from the electronic searches. We will retrieve full text copies of all articles judged to be potentially relevant from the titles and abstracts. At least two review authors will then independently assess these articles for inclusion. A meeting of all review authors will check the final list of included and excluded studies, and any doubts or disagreements about particular studies will be resolved by discussion. Next, we will undertake a manual follow‐up of references from key publications. Where the description of the intervention is not sufficiently detailed to allow the review authors to judge whether it meets the review's inclusion criteria, the trial authors will be contacted and, where possible, more detailed descriptions and/or materials will then be assessed.

Data extraction and management
We will extract the following data from the included studies, using a data extraction form modified from the Cochrane Consumers and Communication Review Group's data extraction template:

  1. General information: title, authors, source, publication status, date published, language, review author information, date reviewed.

  2. Study methods: aims of intervention, aim of study, study design, methods of participant recruitment, inclusion/exclusion criteria, informed consent and ethical approval, funding.

  3. Risk of bias: data to be extracted depends on the study design (see 'Assessment of risk of bias in included studies').

  4. Patients: description, geographic location, setting, number, age, gender, ethnicity, socioeconomic status distribution. If relevant: principal health problem or diagnosis, stage of illness, treatment received.

  5. Providers: description, geographic location, setting, age, gender

  6. Interventions: description including technical specifications on SMS and handset provider, duration of intervention, purpose of intervention, initiator of intervention, message content, details of control/usual or routine care, co‐interventions.

  7. Outcomes: principal and secondary outcomes as specified above, methods of assessing outcomes, follow up for non‐respondents, timing of outcome assessment, adverse events.

  8. Results: for outcomes and times of assessment, control and intervention groups if applicable.

Two review authors independently will extract full descriptions of the interventions onto a standard form. The standard forms will then be sent to other review authors who will check these descriptive data. Any discrepancies between the two review authors' data extraction sheets will be discussed by the data extractors and resolved in a joint meeting with other review authors. If data are missing, we will attempt to contact the authors of the studies to obtain the information.

Assessment of risk of bias in included studies

We will assess and report on the risk of bias of included studies in accordance with the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2008) which recommends the explicit reporting of sequence generation, allocation concealment, blinding of participants, providers and outcome assessors, incomplete outcome data, selective outcome reporting and other sources of bias for RCTs. We will assess the risk of bias of cluster RCTs, quasi‐randomised controlled trials, CBA and ITS studies using a modified version of the risk of bias tool, and in accordance with the guidelines of the Cochrane Consumers and Communication Review Group (Ryan 2007).

In all cases, two review authors will independently assess the risk of bias of included studies, with any disagreements resolved by discussion and consensus of the team. We will use a template to guide the assessment of risk of bias, and will judge each domain as 'yes' (indicating a low risk of bias), 'no' (indicating a high risk of bias) or 'unclear' (indicating an uncertain risk of bias). We will present all included studies by study type and risk of bias level.

We will contact study authors for additional information about the included studies, or for clarification of the study methods as required. We will present the results of the risk of bias assessment in tables, and incorporate the results of this assessment into the review through systematic narrative description and commentary about each of the domains, leading to an overall assessment the risk of bias of included studies and a judgement about the internal validity of the review's results.

Measurement of effect of the intervention

We will use risk ratios (RR) as effect measures for dichotomous outcomes and standardised mean differences (SMD) for continuous outcomes (Deeks 2001). We will report confidence intervals with all measures of effect.

Unit of analysis issues

We will take into account unit of analysis issues resulting from cluster‐randomised trials, repeated measurements and studies with more than two treatment groups. If applicable, the data will be analysed using the recommendations in Cochrane Collaboration Open Learning Module on issues related to the unit of analysis (Alderson 2002a).

Dealing with missing data

We will obtain relevant missing data from study authors, if feasible. We will carefully evaluate important numerical data such as screened, eligible and randomised patients as well as intention‐to‐treat and per‐protocol population. With incomplete outcome data (such as drop‐outs, misses to follow‐up and withdrawn study participants), we will assess and report the risk of bias as 'low' or 'high' as guided by the Cochrane Handbook (Higgins 2008) and identify the numbers as well as the reasons for incomplete data (requesting for additional information from the study authors if necessary). Issues of last‐observation‐carried‐forward (LOCF) will be critically appraised and compared to specifications of primary outcome parameters and power calculation.

Assessment of reporting biases

We will assess reporting biases statistically and using funnel plots in RevMan 5. We will assess selection bias, performance bias, attrition bias and detection bias in the included studies using the checklist provided in Ryan 2007.

Data synthesis

We will present a narrative overview of the findings, including tabular summaries of extracted data. We aim to structure the narrative primarily according to the intended purpose of the message. We will consider whether it is appropriate to combine the studies quantitatively once we have completed the search. The decision is likely to rest on the diversity of interventions and outcome measures used in the studies. Studies will be classified on the following issues:

If quantitative analysis is undertaken, the meta‐analysis will depend on the outcomes reported. For continuous data, where outcomes have been measured in a standard way across studies, we will report the SMD and confidence intervals (Alderson 2002b). For dichotomous data, when outcomes have been measured in a standard way, we will report the RR. In such cases, a cautious approach will be taken to combining results, and the rationale will be detailed. We will conduct statistical analysis according to the guidelines in the Cochrane Handbook (Higgins 2008).

Assessment of heterogeneity

In the event of substantial clinical, methodological or statistical heterogeneity, we will not combine study results in meta‐analysis. We will identify heterogeneity by visual inspection of the forest plots, by using a standard Chi2 test and a significance level of alpha = 0.1, in view of the low power of such tests. We will also examine heterogeneity with I2, where I2 values of 50% or more indicate a substantial level of heterogeneity (Higgins 2003). When heterogeneity is found, we will attempt to determine potential reasons for it by examining individual study characteristics and those of subgroups of the main body of evidence.

Subgroup analysis

If there are sufficient trial data, and if appropriate, we will analyse subgroups according to age, as mobile phone messaging usage and general healthcare utilisation patterns are different across age groups. We will distribute patients into three subgroups; 0 to 18, 18 to 55, over 55. The distribution was made on the basis of a survey by MORI in 2005 (MORI 2005). The use of text messaging by different age groups varied, but was significant and consistently high except in the over 55 age group where around only 40% of users had communicated by text messaging.

Sensitivity analysis

We will perform sensitivity analyses where appropriate in order to explore the influence of the following factors on effect size:

  • excluding unpublished studies;

  • taking account of risk of bias of included studies, as specified above;

  • excluding any large studies to establish how they impact on the results;

  • excluding studies using the following filters: criteria used for clinical diagnosis and eligibility for intervention, language of publication, source of funding (industry versus other), country;

  • the length of the interval between delivery of the intervention and measurement of the effect.

We may also test the robustness of the results by repeating the analysis using different measures of effects size (risk difference, odds ratio etc.) and different statistical models (fixed effect and random effects models).

Consumer participation

The draft review will be circulated for peer review by consumers in the Cochrane Collaboration. We will examine whether consumers were involved in the design and implementation of each included study. We also aim to receive consumer feedback from organisations that may represent consumers/patients who would be affected by the interventions identified in our review.

Dissemination plans

We will aim to promote and disseminate the findings of our review through publication of the review in peer‐reviewed journal(s), by presenting the findings at conferences and scientific meetings and by giving talks on the topic of the review for broad audiences varying from public and policy‐makers to healthcare providers. We will also promote and disseminate the findings of the review through organisations representing consumers ‐ as described above.

Table 1. Characteristics of communication modes

Face‐to‐face

Postal Letter

Call to Landline

Call to Mobile

Web Based (EHR)

E‐mail

SMS / MMS

Immediacy

Slow: Requires a visit to provider.

Slow: 2 days

Immediate:
If person at home. Return call may be necessary.

Immediate:
If person answers (more likely than landline).
Return call may be necessary.

Immediate:

Immediate
Or stored

Immediate
Or stored

Privacy and Confidentiality

High:
Personal communication.

High:
Personally addressed

Low: Confidentiality prevents message being left as others may answer or retrieve it.

High:
Personal device enables possibility of message being left.

Moderate:
Personal / public device?

Moderate:
Personal / public device?

High if
Personal device.

Likelihood of misinterpretation

Low

Moderate

Low:
Patient can request immediate clarification.

Low:
Patient can request immediate clarification.

Moderate

Moderate

Moderate

Delivery confirmation

N/A

Yes:
at significant expense.

Unnecessary if call answered. No if message left.

Unnecessary if call answered. No if message left.

N/A

Yes

Yes

Cost

High

Moderate

Low

Moderate

Low

Low

Low

Figures and Tables -
Table 1. Characteristics of communication modes