Presenter: Rahul Dev Bhawsar, FHI360
Background: GIS (Geographical Information System) created new opportunities to enhance monitoring and decision making in public health as GIS data visualization empowers health managers. High maternal (MMR-221) and child mortality (U5MR-83) is a cause of concern in Madhya Pradesh (M.P.) state of India. Panna district of M.P. has highest IMR of 85 and U5MR of 127 in country. Meeting MDG 4 & 5 requires attention. Reporting on maternal and child deaths by field functionaries is scarce and inappropriate in HMIS. Paucity of reliable and complete data poses challenge to plan and implement programs effectively. GIS tool for tracking maternal and child deaths implemented for evidence-based decisions to improve MNH care. Study objectives were to: 1. present GIS as analytical tool for tracking maternal and child mortality and as decision support tool, and; 2. conduct spatial analysis through mapping mortality and health resources using GIS layers to identify high burden pockets for informed decisions.
Methodology: Data was collected from Census, HMIS, facility records and community. Data geotagged and web-based GIS application developed using open source QGIS software to map and identify high burden pockets. HMIS data of pregnant mothers and delivery collated for tracking maternal and child mortality. GIS analytics used 15 layers. GIS-MIS has features like dashboard, query and display, data summarization.
Results: All 956 villages in the district, 146 health facilities, 1550 health staff & pregnancies mapped. Seventy maternal deaths and 1865 child deaths tracked. Analysis showed maternal and child mortality un-evenly distributed and health centers catchment area are geographically improper. GIS mapping identified mortality pockets, underserved areas, and socio-demographic factors affecting access and service uptake. GIS improved mortality reporting by 25%.
Conclusions: GIS application is strong analytical tool that empowers health managers for data driven decision making. It helps need based resource planning for better targeting health interventions.