Abstract
To effectively target area and population with relatively poorer healthcare access requires information on how access to healthcare varies spatially. Considering hospitals as important components of the healthcare system, this case study of Central Missouri presents a comparison of the relatively underserved areas and population based on the results from three alternative indicators of spatial hospital access calculated at three different levels of geography. Results indicate that the alternative spatial healthcare access indicators show considerably different pictures of the relative ranking of census units, and identification of the relatively underserved areas and population. The relative ranking of census units and the identification of relatively underserved area and population are all critical indicators for policy makers when public resources are limited and distributive choices must be made.
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Notes
We use the term relatively underserved area/population to indicate an area/population that has hospital access score worse than the population weighted regional average of the Central Missouri region. The underserved here is relative to regional averages and does not indicate the level of healthcare access actually received by people residing in a particular census geographic unit in an absolute sense.
County level analysis (or county level indicators) indicates the use of travel time between county centroids and hospital locations in the calculation of the hospital access indicators. Tract level analysis and block group level analysis also should be interpreted in similar manner (i.e. use of tract and block group centroids in the calculation of travel time to hospitals). Tract and block group analysis together are sometimes referred to as sub-county level analysis in the text.
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Gautam, S., Li, Y. & Johnson, T.G. Do alternative spatial healthcare access measures tell the same story?. GeoJournal 79, 223–235 (2014). https://doi.org/10.1007/s10708-013-9483-0
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DOI: https://doi.org/10.1007/s10708-013-9483-0