Evidence map›Paper›PMID 35698112›Full record

ArticleBMC health services research2022

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

Abstract read
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Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Winfred Dotse-GborgbortsiSchool of Geography and Environmental Science, University of Southampton, Southampton, S017 1BJ, UK. w.w.dotse-gborgbortsi@soton.ac.uk.
Andrew J TatemSchool of Geography and Environmental Science, University of Southampton, Southampton, S017 1BJ, UK.
Zoë MatthewsDepartment of Social Statistics and Demography, University of Southampton, Southampton, UK.
Victor AleganaPopulation Health Unit, Kenya Medical Research Institute - Wellcome Trust Research Programme, Nairobi, Kenya.
Anthony OfosuGhana Health Service, Headquarters, Accra, Ghana.
Jim WrightSchool of Geography and Environmental Science, University of Southampton, Southampton, S017 1BJ, UK.

Funding

Economic and Social Research Council ES/P000673/1Wellcome TrustWellcome Trust 211208
6 · The paper itself

Abstract

backgroundHealth 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.

methodsA 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.

resultsClear 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.

conclusionHealth 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.

Indexed as

Maternal Health ServicesRoutinely Collected Health DataCatchment Area, HealthCross-Sectional StudiesFemaleGhanaHealth Services AccessibilityHumansPregnancyGeographic information systemsHealth catchment areasHealth information systemsHealth services accessibilityHealth systems plansMaternal health services

Identifiers

PMID35698112
PMCPMC9190150

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.