BMC Health Services Research (Jun 2022)

Delineating natural catchment health districts with routinely collected health data from women’s travel to give birth in Ghana

  • Winfred Dotse-Gborgbortsi,
  • Andrew J. Tatem,
  • Zoë Matthews,
  • Victor Alegana,
  • Anthony Ofosu,
  • Jim Wright

DOI
https://doi.org/10.1186/s12913-022-08125-9
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 12

Abstract

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Abstract Background Health service areas are essential for planning, policy and managing public health interventions. In this study, we delineate health service areas from routinely collected health data as a robust geographic basis for presenting access to maternal care indicators. Methods A zone design algorithm was adapted to delineate health service areas through a cross-sectional, ecological study design. Health sub-districts were merged into health service areas such that patient flows across boundaries were minimised. Delineated zones and existing administrative boundaries were used to provide estimates of access to maternal health services. We analysed secondary data comprising routinely collected health records from 32,921 women attending 27 hospitals to give birth, spatial demographic data, a service provision assessment on the quality of maternal healthcare and health sub-district boundaries from Eastern Region, Ghana. Results Clear patterns of cross border movement to give birth emerged from the analysis, but more women originated closer to the hospitals. After merging the 250 sub-districts in 33 districts, 11 health service areas were created. The minimum percent of internal flows of women giving birth within any health service area was 97.4%. Because the newly delineated boundaries are more “natural” and sensitive to observed flow patterns, when we calculated areal indicator estimates, they showed a marked improvement over the existing administrative boundaries, with the inclusion of a hospital in every health service area. Conclusion Health planning can be improved by using routine health data to delineate natural catchment health districts. In addition, data-driven geographic boundaries derived from public health events will improve areal health indicator estimates, planning and interventions.

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