Scolaris Content Display Scolaris Content Display

Birth and death notification via mobile devices

Esta versión no es la más reciente

Contraer todo Desplegar todo

Abstract

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

Primary objectives

  • To assess the effects of birth notification via a mobile device, compared to standard practice.

  • To assess the effects of death notification via a mobile device, compared to standard practice.

Secondary objectives

  • To describe the range of strategies used to implement birth and death notification via mobile devices.

  • To identify factors influencing the implementation of birth and death notification via mobile devices.

Background

Globally, the birth of nearly 230 million children under the age of five, and two‐thirds of all deaths have not been officially registered (UNICEF 2016; WHO 2017a; World Bank 2014). Birth registration is a child’s right, and serves as the foundation for establishing legal identity, equitable access to basic services, such as healthcare and education, and protection from exploitation (UNHCR & UNICEF 2017; UNICEF 2013). Death registration, including identification of cause of death, enables public health systems to develop and implement programs to improve the health of populations, as well as rapidly deal with outbreaks (WHO 2013a; WHO 2017a; World Bank 2014). In the context of the post‐2015 development agenda, timely, accurate, and complete statistics on births and deaths, gained through the act of registration, are fundamental for tracking progress towards sustainable development goals and achievement of universal health coverage (WHO 2017b).

Description of the condition

Well‐functioning Civil Registration and Vital Statistics (CRVS) systems provide the most reliable and up‐to‐date data on births, deaths, and population size (UN‐DECA 2014). Civil registration is defined as the 'universal, continuous, permanent, and compulsory recording of vital events (livebirths, deaths, fetal deaths, marriages, and divorces) provided through decree or regulation in accordance with the legal requirements of each country' (UN‐DECA 2002; UNHCR & UNICEF 2017). Vital statistics are the compilation, processing, and dissemination of civil registration data in statistical form (Setel 2007; UN‐DECA 2014; UN‐DECA 2017). Statistics on births and deaths are used to generate population health indicators (e.g. fertility rate, birth rate, and life expectancy), data on mortality (e.g. maternal and infant mortality rates), and disease burden (e.g. using details of cause of death; (UN‐DECA 2014)). Hence, birth and death statistics are a valuable source of data for policymakers, to guide the development of global, national, and regional health policy, program planning, and appropriate resource‐allocation (Setel 2007; UN‐DECA 2014).

Over 100 developing countries lack functional or adequate civil registration systems for capturing vital events (World Bank 2014). Countries from South Asia and sub Saharan Africa house the majority of individuals missed by civil registration systems (AbouZahr 2015; Setel 2007; UNICEF 2016). Birth and deaths of individuals living in rural areas, or lower socio‐economic status households, are more likely to be unregistered, compared to their urban and wealthier counterparts (UNICEF 2013). There is also a link between birth registration and health outcomes (Phillips 2015). For example, children who are unregistered are more likely to miss out on essential health services, such as immunizations (Apland 2014; Fagernas 2013). Lack of accurate and timely death statistics, including cause of death, leads to weak disease surveillance, and threatens the ability of public health systems to prevent or rapidly deal with outbreaks (UN‐DECA 2017). From the health system perspective, the paucity of accurate statistics on births and deaths poses a key challenge in the estimation of program needs (e.g. number of children eligible for health services), appropriate resource allocation, and monitoring (e.g. for calculation of indicators of health system coverage or performance; (AbouZahr 2015; AbouZahr 2015a; Mahapatra 2007)).

Several challenges to civil registration have been identified in the literature, including geographic barriers (UNICEF 2013), low demand or lack of incentives for registration (Apland 2014; UNICEF 2013; WHO 2013b; World Bank 2014), use of paper‐based systems for reporting and recording births (Oomman 2013; World Bank 2014), and lack of, or incorrect cause of, death coding and documentation (Mikkelsen 2015; Rampatige 2013). Poor integration of CRVS systems with other government or citizen databases leads to missed opportunities, for instance, where data on births and deaths captured by the health system are not linked to civil registration systems (World Bank 2014). Even when integration between the health and civil registration system may exist, home births or deaths may not be reported where formal community‐level notification processes are deficient (World Bank 2014).

A global scale‐up plan for strengthening civil registration systems has been developed by the World Health Organization (WHO) and the World Bank, with the aim to "achieve universal civil registration of births, deaths, and other vital events, including reporting cause of death, and access to legal proof of registration for all individuals by 2030” (World Bank 2014). A cornerstone of this plan is the prioritisation and strengthening of the linkages between health and CRVS systems (Muzzi 2010; WHO 2013a; World Bank 2014). This includes a push to modernise data systems associated with civil registration, including through the use of digital information systems, and to improve coverage of registration services among underserved populations such as those residing in rural areas (World Bank 2014, Oomman 2013). In these respects, the global proliferation of mobile phones and cellular network connectivity is increasingly being leveraged, especially in resource‐limited settings, to drive development and use of digital civil registration systems (ITU 2016; Labrique 2012; Labrique 2013; Oomman 2013). Due to their access to mobile phones, community‐based individuals, such as vaccination programme workers, community health workers, and village elders can serve as 'notifiers', helping to increase the coverage of civil registration systems to underserved rural and remote regions (World Bank 2014). This approach may help to reduce delays in identification and reporting of births and deaths to health systems, local civil registration authorities, or both (World Bank 2014).

Description of the intervention

Civil registration involves four major activities: recording, notification, registration, and certification (see Figure 1 (WHO 2013a)). Recording entails capturing details related to a vital event at the point of event. For example, details of a birth may be recorded on a paper form at the health facility or at home. This is followed by notification, wherein details of the recorded event are communicated to the local civil registration office by lawful notifiers. Upon receiving a notification, the civil registrar registers the event, by verifying event details, and recording them in a civil register. Subsequently, a legally valid certificate of registration is issued. The certificate serves as proof that the birth or death has been registered in a civil register. Registered events are aggregated by the national authorities to produce vital statistics on key health and development indicators. Since notification is the key step that triggers registration, many strategies to improve the coverage and timeliness of birth or death registration are focused on reducing delays in notification, especially by using mobile devices to notify local officials. The scope of this review is limited to the notification of births and deaths conducted via mobile devices.


Linkage between CRVS and health system
 Adapted fromSetel 2007and World Bank and World Health Organization 2014 (World Bank 2014).

Linkage between CRVS and health system
Adapted fromSetel 2007and World Bank and World Health Organization 2014 (World Bank 2014).

  • By birth notification, we mean the transmission of information via a mobile device to a centralised system or focal individual(s) to report a birth event. In addition to the formal notification process, which leads to birth registration as it occurs within the context of CRVS systems, we include informal notification of births in this definition. By this, we mean that individuals, other than those defined under the law as official notifiers, may be involved in notifying with mobile devices. It may also mean that the notification is directed to focal individuals other than the civil registrar, or communicated directly to a digital system, and transmitted for purposes other than civil registration.

  • By death notification, we mean the transmission of information via a mobile device to a centralised system or focal individual(s) to report a death event. Death notification may include information on the cause of death. As in the case of birth notification, we also include informal notifications of death in this definition. By this, we mean that individuals, other than those defined under the law as official notifiers, may be involved in providing a notification. It may also mean that the notification is directed to focal individuals other than the civil registrar, or communicated directly to a digital system, and may be transmitted for purposes other than civil registration.

  • By mobile devices, we mean mobile phones of any kind (but not analogue landline telephones), as well as tablets, personal digital assistants, and smartphones. Laptops are not included in this list.

How the intervention might work

For birth notifications, information related to the birth may be transmitted via mobile phones as phone calls, inputs to an interactive voice response, or an unstructured supplementary service data (USSD) system, as short messaging service (SMS), from mobile device‐based applications (apps), or to publicly known short codes or access numbers. The content of the birth notification may vary by country or implementation, but may include the name of the child born, name and address of the parents, place and date of birth, and details of birth outcomes. An example of a formal birth notification sent via a mobile device, is when a community‐based notifier uses his or her mobile phone to relay notification about a home‐based birth to a digital civil registration system via USSD (NIRA 2017). The notification may be received and reviewed for accuracy and completeness by the local civil registration office before a birth certificate is issued. An example of an informal birth notification sent via a mobile device, is when a village elder sends information about a birth, via SMS, to a central digital server, for the purpose of enrolling the child in a longitudinal vaccination tracking system. The enrolment of the child in the tracking system may be used to initiate vaccination services for the child, and to track their subsequent vaccinations.

For death notifications, information related to the death may be transmitted via mobile phones as phone calls, inputs to an interactive voice response, or USSD system, as SMS, from apps, or to publicly known short codes or access numbers. The content of the death notification may vary by country or implementation, but may include name of the deceased, name and address of relatives (for example spouse), place and date of death, and details of the cause of death. An example of a formal death notification, sent via mobile device, is when a health provider uses a mobile phone app to transmit information about a death, including cause of death, to a digital civil registration system. The notification may be received and reviewed for accuracy and completeness by the local civil registration office before a death certificate is issued. An example of an informal death notification sent via a mobile devices, is when a community health worker sends a message about a death, via SMS, to a central digital server, for the purpose of disease surveillance.

Why it is important to do this review

Ministries of health, donors, and decision‐makers face expanding opportunities to harness the ubiquity and penetration of mobile technology to address longstanding challenges related to acquiring accurate and timely statistics on births and deaths. There is high demand from these stakeholders for evidence‐based guidance on the value of digital tools to strengthen linkages between civil registration and health systems, as a mechanism to improve the timeliness and accuracy of birth and death statistics. In response to this global need, the World Health Organization is developing guidelines to inform investments on digital health approaches that use mobile phones for birth and death notifications.

There is growing evidence on the use of mobile devices for birth and death notification. A previous systematic review on digital interventions for CRVS was published in 2013 (WHO 2013a). It examined literature from 23 countries, but found limited peer‐reviewed evidence for the use of mobile devices to notify of birth and death events. This review, focused entirely on low‐ and middle‐income countries, did not report quantitative outcomes, or examine factors that influenced the use of mobile phones to notify officials of birth and death events. Since this review was published, several new reports describing birth or death notification via mobile devices, have emerged. Hence, it is important to conduct a systematic review to assess these new trials. Findings from this systematic review will be used to directly inform WHO guidelines on the effectiveness of digital strategies to improve data on births and deaths.

Objectives

Primary objectives

  • To assess the effects of birth notification via a mobile device, compared to standard practice.

  • To assess the effects of death notification via a mobile device, compared to standard practice.

Secondary objectives

  • To describe the range of strategies used to implement birth and death notification via mobile devices.

  • To identify factors influencing the implementation of birth and death notification via mobile devices.

Methods

Criteria for considering studies for this review

Types of studies

For analysis of the primary objectives, we will include randomised trials and non‐randomised trials. We will include:

  • individual and cluster‐randomised trials;

  • cross‐over and stepped‐wedge study designs;

  • controlled before‐after studies, provided they have at least two intervention sites and two control sites; and

  • interrupted time series studies, if there is a clearly defined time point when the intervention occurred and at least three data points before and three after the intervention.

We will include published studies, conference abstracts, and unpublished data. We will include studies regardless of their publication status and language of publication.

For analysis of the secondary objectives, we will include any study design, either quantitative, qualitative, or descriptive, that:

  • aims to describe current strategies for birth and death notification via mobile devices; or

  • aims to explore factors that influence the implementation these strategies, including studies of acceptability or feasibility.

Types of participants

The following participants will be included in this review:

  • all cadres of healthcare providers, including professionals, paraprofessionals, and lay health workers (LHWs);

  • administrative, managerial, and supervisory staff at health facilities;

  • administrative, managerial, and supervisory staff, including registrars, associated with civil registration units;

  • focal individuals at the village‐ or community‐level (e.g. village leaders);

  • children whose births are being notified, as well as parents or other caregivers (e.g. grandparents) of such children; and

  • individuals whose deaths are being notified, as well as relatives or caregivers of such individuals.

Types of interventions

For analysis of the primary objectives, we will include studies that compare birth and death notification via mobile devices with standard practice. We define standard practice as non‐digital and non‐mobile, paper‐based processes, and workflows for notifying birth and death events.

The comparisons for this review will be:

  • birth notification via mobile devices compared with standard practice; and

  • death notification via mobile devices, compared with standard practice.

We will include:

  • studies in which birth or death notification is sent by parents, caregivers, other family members, administrative, managerial or supervisory staff, focal individuals in the community, or health workers, via mobile devices, to alert a central system, organization, or civil registration agency that a birth or death has taken place;

  • studies in which notified births are enrolled into a digital health record for tracking provision of newborn and child health services;

  • studies in which birth notification is part of a pregnancy digital health record, and where outcomes are reported for the postnatal period onward;

  • studies in which notified deaths, including cause of death, are reported to a disease surveillance system; and

  • studies in which birth and death notifications are delivered as part of a wider package, if we judge the birth or death notification to be the major component of the intervention.

For analysis of the secondary objectives, in addition to the above inclusion criteria, we will include:

  • studies in which birth and death notifications are delivered as part of a wider package:

    • even if birth and death notifications are judged not to be the major component of the intervention; and

    • as long as we can extract data on the birth and death notification components that are relevant to the primary or secondary objectives.

We will exclude:

  • studies in which birth and death notification is conducted on stationary computers or laptops alone;

  • studies that compare different specifications of technology systems (e.g. software, communication channels) for birth or death notification;

  • studies in which birth notification is part of a pregnancy digital health record, and where outcomes are only reported for the pregnancy and prenatal period. Such studies are excluded from this review because we cannot link the effect of the mobile birth notification to outcomes that occur during pregnancy. While such studies are excluded from this review, outcomes related to pregnancy and the prenatal period from such studies will be extracted and included in a separate review.

  • studies that only describe interventions to improve attribution of cause of death (e.g. digital verbal autopsy tools), without a notification component; and

  • feasibility or pilot studies (for analysis of primary objectives only).

Types of outcome measures

We will include studies that report outcomes related to birth and death notification via mobile devices in this review. When birth and death notifications are described in the same study, we will extract and report outcome data for birth and death notifications separately. Specific outcomes of interest are listed below.

For birth notification via mobile device

  • coverage (e.g. proportion) of births notified via mobile devices;

  • timeliness of birth notification via mobile device (e.g. time between birth and birth notification via mobile device);

  • proportion of legal birth registrations in response to birth notifications via mobile device, where legal birth registration is defined as the recording, within the civil registry, of the occurrence and characteristics of births in accordance with the legal requirements of a country. Legal birth registration is conducted by a civil registrar.

  • timeliness of legal birth registrations in response to birth notification via mobile device (e.g. time between birth notification and legal birth registration);

  • coverage of (e.g. proportion of children receiving) newborn or child health services (e.g. immunizations) in response to birth notification via mobile device;

  • timeliness of receipt of newborn or child health services (e.g. immunizations) in response to birth notification via mobile device (i.e. time between birth and receipt of services).

For death notifications via mobile device

  • coverage (e.g. proportion) of deaths notified via mobile devices;

  • timeliness of death notification via mobile device (i.e. time between death and death notification via mobile device);

  • proportion of legal death registrations in response to death notifications via mobile device, where legal death registration is defined as the recording, within the civil registry, of the occurrence and characteristics of death in accordance with the legal requirements of a country. Legal death registration is conducted by a civil registrar.

  • timeliness of legal death registrations in response to death notification via mobile device (i.e. time between death notification and legal death registration);

  • proportion of deaths where causes of death were ascertained, reported, or both, to a disease surveillance system in response to death notifications via mobile device;

  • timeliness of causes of death ascertainment, reporting to a disease surveillance system, or both, in response to death notifications via mobile device (i.e. time between death and cause of death ascertainment).

For both birth and death notifications via mobile device

  • quantitative measures of notifiers’ acceptability or satisfaction (or both) with birth and death notifications via mobile device;

  • resource use (e.g. human resources and time, including additional time spent by notifiers when managing and transitioning from paper to digital reporting systems, training, supplies, and equipment);

  • unintended consequences (e.g. transmission of inaccurate data, for instance, by incorrect data entry, privacy and disclosure issues, failure or delay in message delivery, interrupted workflow due to infrastructure constraints for recharging batteries and network coverage, and impact on equity).

Study findings for secondary objectives

For analysis of the secondary objectives, we will extract data about strategies for the notification of births and deaths via mobile device, and data about factors that influence the implementation of these strategies.

Search methods for identification of studies

An independent information specialist (JE) will develop the search strategies in consultation with the review authors. We will use the cutoff search date of 2000. This is based on the increased availability and penetration of mobile devices in low‐ and middle‐income countries starting in 2000 (ITU 2016). Search strategies are comprised of titles, abstracts, and keywords, including controlled vocabulary terms. We will not apply any limits on language. We will use a study design search filter used by Cochrane Effective Practice and Organisation of Care (EPOC) to retrieve both randomised and non‐randomised studies. We will use the EPOC filter to find study designs outlined under 'secondary outcomes' among the retrieved records. See Appendix 1 for the MEDLINE search strategy, which we will adapt for other databases.

Electronic searches

We will search these databases for primary studies:

  • Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library;

  • MEDLINE Ovid;

  • Embase Ovid;

  • Global Health Library WHO;

  • POPLINE K4Heath.

Searching other resources

Trial registries

  • World Health Organization International Clinical Trials Registry Platform (WHO ICTRP; www.who.int/ictrp);

  • US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov (www.clinicaltrials.gov).

Systematic review registry

We will search Epistemonikos (www.epistemonikos.org) for related systematic reviews and potentially eligible primary studies.

Grey literature

We will conduct a grey literature search to identify studies not indexed in the databases listed above, and to capture the broader range of study designs to be included for the secondary objectives. Because this review is focused on birth and death notifications using mobile devices, we will review mhealthevidence.org for contributed content that is not referenced in MEDLINE Ovid. In addition, the WHO will issue a call for papers through popular digital health communities of practice, such as the Global Digital Health Network and Implementing Best Practices, to identify additional primary studies and grey literature.

Other resources

  • We will review reference lists of all included studies and relevant systematic reviews for potentially eligible studies.

  • We will contact authors of included studies and reviews to clarify reported published information, and to seek unpublished results and data.

  • We will conduct citation searches of included studies in Scopus, Web of Science, and Google Scholar.

Data collection and analysis

Selection of studies

We will download all titles and abstracts retrieved by electronic searching to a reference management database, and remove duplicates. Two review authors (NH, NM) will independently screen titles and abstracts for inclusion. We will retrieve the full‐text study reports and publications, and two review authors (NH, NM) will independently screen the full‐text, identify studies for inclusion, and identify and record reasons for excluding ineligible studies. We will resolve any disagreement through discussion, or if required, we will consult a third review author. LV will serve as the third reviewer for studies published in English. For all other languages, we will consult with a reviewer with appropriate fluency from the Cochrane Response Team.

We will list studies that initially appeared to meet the inclusion criteria in abstract form, but that we excluded after reviewing the full‐text report, in the 'Characteristics of excluded studies' table. We will collate multiple reports of the same study so that each study, rather than each report, is the unit of interest in the review. We will also provide any information we can obtain about ongoing studies. We will record the selection process in sufficient detail to complete a PRISMA flow diagram (Liberati 2009).

Data extraction and management

We will use the EPOC standard data collection form and adapt it for study characteristics and outcome data (EPOC 2017a); we will pilot the form on at least one study in the review.

For the analysis of primary objectives, two review authors (NH, NM) will independently extract the study characteristics from the included studies, such as:

  1. General information: title, reference details, author contact details, publication type, funding source, conflicts of interest of study authors;

  2. Methods: study design, number of study sites and location, study setting, withdrawals, date of study, follow‐up;

  3. Participants: number, mean age, age range, gender, severity of condition, inclusion criteria, exclusion criteria, other relevant characteristics;

  4. Interventions: intervention components, comparison, intervention purpose, mode, timing, frequency, and duration of intervention delivery, content of the intervention, type of mobile device used (smartphone, tablet, feature phone, basic phone, laptops), interoperability, compliance with national guidelines, data security, fidelity assessment;

  5. Outcomes: main and other outcomes specified and collected, time points reported;

  6. Notes: funding for trial, notable conflicts of interest of trial authors, ethical approval, interoperability, data security, compliance with national guidelines, limitations for delivery at scale.

Two review authors (NH, NM) will independently extract outcome data from included studies. We will note in the 'Characteristics of included studies' table if outcome data were reported in an unusable way. We will resolve disagreements by consensus or by involving a third review author (LV).

For the analysis of secondary objectives, we will extract descriptive data where applicable and available, including the details of the intervention used, groups or stakeholders involved in implementing the intervention, pathway of action (how they thought it would work), context of implementation, factors affecting implementation, type of evaluation (study design), and outcome measures assessed.

To assess the factors affecting the implementation of birth and death notifications via mobile device, we will use the SURE (Supporting the Use of Research Evidence) framework, which provides a comprehensive list of possible factors that may influence the implementation of health system interventions (Glenton 2017; SURE 2011). We will extract data on:

  1. individual characteristics (e.g. knowledge and skills, attitudes regarding program acceptability, appropriateness and credibility, motivation to change or adopt new behaviour);

  2. health system constraints (e.g. accessibility of care, financial resources, human resources, educational and training system, including recruitment and selection, clinical supervision, support structures and guidelines, internal communication, external communication, allocation of authority, accountability, community participation, management or leadership (or both), information systems, facilities, client processes, distribution systems, incentives, bureaucracy, relationship with norms and standards); and

  3. social and political constraints (e.g. ideology, governance, short‐term thinking, contracts, legislation or regulation, donor policies, influential people, corruption, political stability and commitment).

In addition, we will include any emergent codes describing implementation challenges, which are not captured within the SURE framework.

Assessment of risk of bias in included studies

Two review authors (NH, NM) will independently assess risk of bias for each study, using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions Section 8.5 (Higgins 2011), and the guidance from the EPOC group (EPOC 2017b). Any disagreement will be resolved by discussion, or by involving a third review author (LV). We will assess the risk of bias according to the following domains:

  1. random sequence generation;

  2. allocation concealment;

  3. blinding of participants and personnel;

  4. blinding of outcome assessment;

  5. incomplete outcome data;

  6. selective outcome reporting;

  7. baseline outcomes measurement;

  8. baseline characteristics;

  9. other bias;

  10. appropriate analysis (interrupted time series studies only);

  11. prespecified shape of effect (interrupted time series studies only);

  12. unlikely to affect data collection (interrupted time series studies only).

We will judge each potential source of bias as high, low, or unclear, and provide a quote from the study report together with a justification for our judgment in the 'Risk of bias' table. We will summarise the 'Risk of bias' judgements across different studies for each of the domains listed. We will consider blinding separately for different key outcomes where necessary (e.g. for unblinded outcome assessment, risk of bias for all‐cause mortality may be very different than for a patient‐reported pain scale). Where information on risk of bias relates to unpublished data or correspondence with a trialist, we will note this in the 'Risk of bias' table. We will not exclude studies on the grounds of their risk of bias, but will clearly report the risk of bias when presenting the results of the studies.

When considering treatment effects, we will take into account the risk of bias of the studies that contribute to that outcome.

We will conduct the review according to this published protocol and report any deviations form it in the 'Differences between protocol and review' section of the systematic review.

Measures of treatment effect

For the analyses of the primary objectives, we will report means and proportions where appropriate. When applicable, we will estimate the effect of the intervention using risk ratio or risk difference for dichotomous data, together with the appropriate associated 95% confidence interval, and mean difference or standardised mean difference for continuous data, together with the 95% appropriate associated confidence interval. We will ensure that an increase in scores for continuous outcomes can be interpreted in the same way for each outcome, explain the direction to the reader, and report where the directions were reversed, if this was necessary.

Unit of analysis issues

We will perform data analysis at the same level as the allocation, to avoid unit‐of‐analyses errors. For clustered designs (such as cluster‐randomised trials), the reported results in included studies will often be on a level other than the level of allocation. If this is the case, we will perform an analysis adjusting for clustering, in order to avoid unit‐of‐analyses errors. When extracted results are not based on analyses adjusted for clustering, we will reanalyse the results (EPOC 2017c). If there is a unit of analysis error in the reported analysis for a study and there is insufficient information to reanalyse the results, a review author (LV) will contact the authors to request necessary data. We will not report confidence intervals or P values for which there is a unit‐of‐analysis error, if these data are not available.

Dealing with missing data

We will contact investigators in order to verify key study characteristics and request missing outcome data where possible (e.g. when a study is identified as abstract only).

Assessment of heterogeneity

If we find a sufficient number of studies, we will conduct a meta‐analysis. We will use the I² statistic to measure heterogeneity among the trials in each analysis. If we identify substantial heterogeneity, we will explore it by prespecified subgroup analysis.

Assessment of reporting biases

We will attempt to contact study authors, asking them to provide missing outcome data. Where this is not possible, and the missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results. If we are able to pool more than 10 trials, we will create and examine a funnel plot to explore possible publication biases, interpreting the results with caution (Sterne 2011).

Data synthesis

For the analyses of primary objectives, we will undertake meta‐analyses only where this is meaningful, i.e. if the treatments, participants, and the underlying clinical question are similar enough for pooling to make sense. A common way that trialists indicate when they have skewed data is by reporting medians and interquartile ranges. When we encounter this, we will note that the data are skewed and consider the implication of this. Where multiple trial arms are reported in a single trial, we will include only the relevant arms. If two comparisons (e.g. intervention A versus usual care and intervention B versus usual care) must be entered into the same meta‐analysis, we will halve the control group to avoid double‐counting.

For the analyses of secondary objectives, one review author (LV) will go through the included studies to assess whether any include robust outcome data (e.g. studies that report results based on objective measures, from high quality, routine information systems).

For studies that contain robust outcome data:

  • we will extract relevant outcome data, if applicable;

  • we will report the outcome data appropriately in the review.

For all studies included in the analyses of secondary objectives, the extracted information will form the basis of a table in the review, describing interventions that have been proposed or evaluated. We will also summarize the extracted data in narrative form. Specifically for the secondary objective on factors affecting the implementation of birth and death notifications via mobile devices, one review author (LV) will read each of the included documents, and extract any data that described factors tied to the implementation. Two review authors (LV, CG) will then identify and discuss key emerging themes, their definitions, and how these themes relate to the SURE framework. The two review authors will categorize similar themes that go together, within the relevant SURE framework category.

'Summary of findings' table and GRADE

We will create 'Summary of findings' tables (EPOC 2017d) for the main intervention comparisons, and include the most important outcomes in order to draw conclusions about the certainty of the evidence within the text of the review:

  1. coverage (e.g. proportion) of births notified via mobile device;

  2. timeliness of birth notification via mobile device (e.g. time between birth and birth notification via mobile device);

  3. timeliness of receipt of newborn or child health services (e.g. immunizations) in response to birth notification via mobile device (i.e. time between birth and receipt of services);

  4. coverage (e.g. proportion) of deaths notified via mobile device;

  5. timeliness of death notification via mobile device (i.e. time between death and death notification via mobile device);

  6. timeliness of causes of death ascertainment, reporting to a disease surveillance system, or both, in response to death notifications via mobile device (i.e. time between death and cause of death ascertainment).

If we become aware of an important outcome that we failed to list in our planned 'Summary of findings' tables during the review process, we will include the relevant outcome and explain the reasons for this in the section 'Differences between protocol and review'.

Two review authors (LV, MF) will independently assess the certainty of the evidence (high, moderate, low, and very low), using the five GRADE considerations (risk of bias, consistency of effect, imprecision, indirectness, and publication bias; (Guyatt 2008)). We will use methods and recommendations described in Section 8.5 and Chapter 12 of the Cochrane Handbook for Systematic Reviews of interventions (Higgins 2011), and the EPOC worksheets (EPOC 2017d), and GRADEpro software (GRADEpro GDT). We will resolve disagreements on certainty ratings by discussion and provide justification for decisions to down‐ or upgrade the ratings, using footnotes in the table and make comments to aid readers' understanding of the review, where necessary. We will use plain language statements to report these findings in the review (EPOC 2017e).

We will consider whether there is any additional outcome information that we were unable to incorporate into meta‐analyses, note this in the comments, and state if it supports or contradicts the information from the meta‐analyses. If it is not possible to meta‐analyse the data, we will summarise the results in the text.

Subgroup analysis and investigation of heterogeneity

If meaningful, we plan to carry out the following subgroup analyses:

  1. by study setting (e.g. high‐income versus low‐ and middle‐income countries; urban versus rural);

  2. by whether there is an existing CRVS (paper‐based) system in place versus no CRVS system in place at all;

  3. by whether the notification is formal (i.e. for civil registration) versus informal (for purposes other than civil registration).

We will use the following outcomes in subgroup analysis.

For birth notifications via mobile device

  • coverage (e.g. proportion) of births notified via mobile device;

  • timeliness of birth notifications via mobile device (e.g. time between birth and birth notification via mobile device);

  • timeliness of receipt of newborn or child health services (e.g. immunizations) in response to birth notifications via mobile device (i.e. time between birth and receipt of services).

For death notifications via mobile device

  • coverage (e.g. proportion) of deaths notified via mobile device;

  • timeliness of death notifications via mobile device (i.e. time between death and death notification via mobile device);

  • timeliness of cause of death ascertainment, reporting to a disease surveillance system, or both, in response to death notifications via mobile device (i.e. time between death and cause of death ascertainment).

Sensitivity analysis

We will perform three sensitivity analyses to assess the robustness of our conclusions, and explore the impact on effect sizes. We will restrict the analysis (i) to published studies, and (ii) to studies with a low risk of bias. For outcomes where acceptability or satisfaction is assessed quantitatively, we will (iii) exclude studies using unvalidated scales.

Linkage between CRVS and health system
 Adapted fromSetel 2007and World Bank and World Health Organization 2014 (World Bank 2014).
Figuras y tablas -
Figure 1

Linkage between CRVS and health system
Adapted fromSetel 2007and World Bank and World Health Organization 2014 (World Bank 2014).