Drivers of Utilization, Quality of Care, and RMNCH-N Services in Bangladesh : A Comparative Analysis of Demand and Supply-Side Determinants Using Machine Learning for Investment Decision-Making (English)

Amidst noticeable improvements and achievements in the reproductive, maternal, neonatal, child health, and nutrition (RMNCH-N) landscape in Bangladesh, existing evidence suggests that further accelerated progress hinges on strategic investment decision-making. Addressing the top service utilization determinants that are both context- and time-specific is one cost-effective way of improving the unmet RMNCH-N outcomes in a short timeframe. Against this backdrop, using machine learning analysis, the overall aim of this study was to help Bangladesh identify priority investment areas that could accelerate RMNCH-N utilization, quality and outcomes over the short run, by comparing the relative importance of demand and-supply-side determinants of key RMNCH-N indicators over the last decade (across two time points). Two rounds of the Bangladesh Health Facility Survey and the Demographic and Health Survey (2014 and 2017) were analyzed. Findings indicate that the relative importance of the demand-side determinants (except wealth and education status) have recently declined. Conversely, investments in key supply-side determinants (e.g., availability of skilled staff, readiness for care and quality of care) can provide a thrust towards further increases in utilization. Immediate attention is needed to address the regressive role of wealth status on utilization through, for example, demand-side financing which goes beyond user fee exemptions. Further, developing strategies to improve the engagement of community health workers in RMNCH-N utilization and tapping into the potential of mobile-health technology to support the CHWs' performance and women's awareness can help to boost utilization patterns.