Technology-based innovative solutions for improving perinatal care utilisation: a network meta-analysis
Programme of work
Evaluating complex interventions
Md Mizanur Rahman
Department of Global Health Policy, The University of Tokyo
Department of Global Health Nursing, St Luke’s International
Global Public Health Research Foundation, Bangladesh
February 2020 to August 2021 (TBC)
Low- and middle-income countries
This study will examine the impact of technology-based interventions in improving antenatal, postnatal and delivery care services in low- and middle-income countries (LMICs).
This systematic review will use meta-analysis to provide a comprehensive review of associated outcomes with regards to target populations. It will then explore how interactions take place and produce causal outcomes along the antenatal–delivery–postnatal pathway.
Bayesian random effects meta-analysis will then be used to summarise the effect size of individual interventions for each outcome, separately.
Bayesian network meta-analysis will also be used to identify the most effective interventions for each outcome.
Sub-group analysis will be used to estimate the pooled effect for each intervention (e.g. by country, region, age group, year of publication, survey year). Funnel plots and the Egger test will assess publication bias.
The study will draw on published evidence (British Nursing Index, CINAHL PLUS, Cochrane Library, EMBASE, MEDLINE, POPLINE, PsycINFO, PubMed and Web of Science) and publicly available data.
The study will provide insights and evidence-informed recommendations for the utilisation of technology-based interventions in addressing maternal health-care challenges in LMICs. It will assess the impact of technology-based interventions by comparing the country-income level and population demographics.