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We will include published studies, conference abstracts, and unpublished data.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.

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

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.

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.

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.