ArticleBMJ open2026
Economic evaluations of digital health interventions on maternal, newborn and child health in low-income and middle-income countries: a systematic review protocol.
Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionDigital health interventions have emerged as promising solutions to strengthen maternal, newborn and child health (MNCH) systems in low-income and middle-income countries (LMICs). Although evidence on their effectiveness is growing, corresponding economic evaluations remain limited, heterogeneous and fragmented. Understanding the value for money of digital health interventions is essential for supporting scale-up decisions and efficient resource allocation. This protocol outlines the methods for a systematic review synthesising economic evaluations of digital health interventions across the MNCH continuum in LMICs. METHODS AND ANALYSIS: We will systematically search PubMed, Embase, Scopus, the Cochrane Library, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO and Turning Research Into Practice (TRIP) Pro for peer-reviewed studies published from 1 January 2000 to 31 December 2025. Backward citation searching (reference lists of included articles) and forward citation tracking will be performed to ensure comprehensive study identification, and study authors will be contacted when necessary to obtain missing or unclear data. Artificial intelligence (AI)-based Deep Research tools will be used as a supplementary approach to identify additional keywords and assess the completeness of the search strategy. Eligible studies will include full and partial economic evaluations embedded within randomised controlled trials, quasi-experiments, controlled before-and-after studies, time-series analyses, cohort or case-control designs, implementation studies and economic modelling studies. Three reviewers will independently conduct study selection and data extraction using a predefined form adapted from the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 guidelines. Methodological quality will be assessed using the Drummond checklist. Due to heterogeneity in study designs and economic methods, a narrative synthesis will be conducted. Costs will be standardised to the US dollar (USD) in 2024. ETHICS AND DISSEMINATION: This review will synthesise evidence from already published studies and does not involve the collection of primary data; therefore, ethical approval is not required. All data extracted will be derived from publicly available peer-reviewed literature, and no identifiable personal information will be used. The findings of this systematic review will be disseminated through publication in a peer-reviewed journal and presentations at academic conferences focused on global health, digital health and MNCH. In addition, the results will be shared with relevant stakeholders, including policymakers, programme implementers and organisations involved in digital health and MNCH in LMICs. PROSPERO REGISTRATION NUMBER: CRD420251125682.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.