Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.
Department of Geomatic Engineering and Geospatial Information System (GEGIS), Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya.
Int J Health Geogr. 2023 Mar 27;22(1):6. doi: 10.1186/s12942-023-00327-6.
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.
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.
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.
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.
评估获取基本卫生干预措施的差距有助于分配和优先考虑卫生资源。获得输血是一项重要的紧急卫生需求。在此，我们在肯尼亚西部邦戈马县开发了输血服务可达性和竞争力的地理空间模型。
从更新的地理编码设施数据库中确定了提供输血服务的医院。使用 AccessMod 定义了每个普查区（EA）的就诊者到最近的输血服务的出行时间。使用模型化的出行时间、医院的人口需求和供应，定义了每个 EA 的空间可达性指数，假设该县紧急情况发生的风险是均匀的。为了确定被输血服务边缘化的人群，计算了 1 小时出行时间以外的人数和可达性指数较低的 EA 中居住的人数，按县进行细分。使用空间竞争指数来估计转输医院之间的竞争，该指数提供了每个医院吸引力水平的度量。为了了解竞争激烈的医院是否具有更好的输血服务能力，对计算得出的竞争指标与医院接收和转输的血液单位数量进行了相关性检验。
邦戈马县有 15 家医院提供输血服务，但分布不均。全县到输血中心的平均出行时间为 33 分钟，5%的人口居住在 1 小时出行时间以外。根据可达性指数，38%的 EA 被归类为可达性较低，代表 34%的人口，其中一个县的人口被边缘化比例最高。计算得出的竞争指数表明，城市地区的医院相对于农村地区的医院具有空间竞争优势。
模型化的空间可达性提高了对卫生规划至关重要的卫生保健差距的认识。医院竞争在一定程度上影响了卫生服务的提供，因此应被视为影响现有服务交付和重新设计的重要外部因素。
