This project is no longer supported by CEDIL due to UK aid cuts during COVID-19.

Technology-based innovative solutions for improving perinatal care utilisation: a network meta-analysis

Programme of work

Evaluating complex interventions

Principal investigator(s)

Md Mizanur Rahman

Host institution

Department of Global Health Policy, The University of Tokyo

Other institutions

Department of Global Health Nursing, St Luke’s International
University, Japan
Global Public Health Research Foundation, Bangladesh


February 2020 to August 2021 (TBC)

Project type

Evidence synthesis


Low- and middle-income countries

Research question

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).

Research design

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.

Data source

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.

Policy relevance

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.