Geographic accessibility and hospital competition for emergency blood transfusion services in Bungoma, Western Kenya.

Autor: Mumo E; Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya. eddahwangui84@gmail.com.; Department of Geomatic Engineering and Geospatial Information System (GEGIS), Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya. eddahwangui84@gmail.com., Agutu NO; Department of Geomatic Engineering and Geospatial Information System (GEGIS), Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya., Moturi AK; Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya., Cherono A; Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya., Muchiri SK; Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya., Snow RW; Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK., Alegana VA; Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.
Jazyk: angličtina
Zdroj: International journal of health geographics [Int J Health Geogr] 2023 Mar 27; Vol. 22 (1), pp. 6. Date of Electronic Publication: 2023 Mar 27.
DOI: 10.1186/s12942-023-00327-6
Abstrakt: Background: Estimating accessibility gaps to essential health interventions helps to allocate and prioritize health resources. Access to blood transfusion represents an important emergency health requirement. Here, we develop geo-spatial models of accessibility and competition to blood transfusion services in Bungoma County, Western Kenya.
Methods: Hospitals providing blood transfusion services in Bungoma were identified from an up-dated geo-coded facility database. AccessMod was used to define care-seeker's travel times to the nearest blood transfusion service. A spatial accessibility index for each enumeration area (EA) was defined using modelled travel time, population demand, and supply available at the hospital, assuming a uniform risk of emergency occurrence in the county. To identify populations marginalized from transfusion services, the number of people outside 1-h travel time and those residing in EAs with low accessibility indexes were computed at the sub-county level. Competition between the transfusing hospitals was estimated using a spatial competition index which provided a measure of the level of attractiveness of each hospital. To understand whether highly competitive facilities had better capacity for blood transfusion services, a correlation test between the computed competition metric and the blood units received and transfused at the hospital was done.
Results: 15 hospitals in Bungoma county provide transfusion services, however these are unevenly distributed across the sub-counties. Average travel time to a blood transfusion centre in the county was 33 min and 5% of the population resided outside 1-h travel time. Based on the accessibility index, 38% of the EAs were classified to have low accessibility, representing 34% of the population, with one sub-county having the highest marginalized population. The computed competition index showed that hospitals in the urban areas had a spatial competitive advantage over those in rural areas.
Conclusion: The modelled spatial accessibility has provided an improved understanding of health care gaps essential for health planning. Hospital competition has been illustrated to have some degree of influence in provision of health services hence should be considered as a significant external factor impacting the delivery, and re-design of available services.
(© 2023. The Author(s).)
Databáze: MEDLINE
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