Machine learning for maternal health: Predicting delivery location in a community health worker program in Zanzibar.

ABSTRACT:

Background

Maternal and neonatal health outcomes in low- and middle-income countries (LMICs) have improved over the last two decades. However, many pregnant women still deliver at home, which increases the health risks for both the mother and the child. Community health worker programs have been broadly employed in LMICs to connect women to antenatal care and delivery locations. More recently, employment of digital tools in maternal health programs have resulted in better care delivery and served as a routine mode of data collection. Despite the availability of rich, patient-level data within these digital tools, there has been limited utilization of this type of data to inform program delivery in LMICs.

Methods

We use program data from 38,787 women enrolled in Safer Deliver

SUBMITTER: Fredriksson A 

PROVIDER: S-EPMC9428344 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature