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
Amid noticeable improvements and achievements in the reproductive, maternal, neonatal, child health, and nutrition 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 reproductive, maternal, neonatal, child health, and nutrition 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 reproductive, maternal, neonatal, child health, and nutrition utilization, quality, and outcomes over the short run, by comparing the relative importance of demand- and-supply-side determinants of key reproductive, maternal, neonatal, child health, and nutrition indicators over the past decade (across two time points). Two rounds of the Bangladesh Health Facility Survey and the Demographic and Health Survey (2014 and 2017) were analyzed. The 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 (for example, availability of skilled staff, readiness for care, and quality of care) could provide a thrust toward further increases in utilization. Immediate attention is needed to address the regressive role of wealth status on utilization through, for example, demand-side financing that goes beyond user fee exemptions. Further, developing strategies to improve the engagement of community health workers in reproductive, maternal, neonatal, child health, and nutrition utilization and tapping into the potential of mobile health technology to support community health workers’ performance and women’s awareness could help to boost utilization patterns.
| Main Authors: | , , |
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| Format: | Working Paper biblioteca |
| Language: | English |
| Published: |
World Bank, Washington, DC
2021-09
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| Subjects: | MATERNAL HEALTH, FAMILY PLANNING, CHILD HEALTH, NUTRITION, UTILIZATION DETERMINANTS, HEALTH CARE QUALITY, INVESTMENT DECISIONS, MACHINE LEARNING, |
| Online Access: | http://documents.worldbank.org/curated/undefined/840071632486368769/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 http://hdl.handle.net/10986/36310 |
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| Summary: | Amid noticeable improvements and
achievements in the reproductive, maternal, neonatal, child
health, and nutrition 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 reproductive, maternal, neonatal, child health, and
nutrition 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 reproductive,
maternal, neonatal, child health, and nutrition utilization,
quality, and outcomes over the short run, by comparing the
relative importance of demand- and-supply-side determinants
of key reproductive, maternal, neonatal, child health, and
nutrition indicators over the past decade (across two time
points). Two rounds of the Bangladesh Health Facility Survey
and the Demographic and Health Survey (2014 and 2017) were
analyzed. The 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 (for example, availability of
skilled staff, readiness for care, and quality of care)
could provide a thrust toward further increases in
utilization. Immediate attention is needed to address the
regressive role of wealth status on utilization through, for
example, demand-side financing that goes beyond user fee
exemptions. Further, developing strategies to improve the
engagement of community health workers in reproductive,
maternal, neonatal, child health, and nutrition utilization
and tapping into the potential of mobile health technology
to support community health workers’ performance and women’s
awareness could help to boost utilization patterns. |
|---|