Combining Transportation Network Models with Kernel Density Methods to Measure the Relative Spatial Accessibility of Pediatric Primary Care Services in Jefferson County, Kentucky

When considering access to healthcare, the question of whether the provider is available and accessible must be answered before the question of cost. Most contemporary techniques of estimating the spatial accessibility of healthcare cannot simultaneously take into account transportation times and the spatially distributed service capacity of healthcare providers. This paper creates the Comprehensive Spatial Accessibility Rank (CSAR) model to calculate a relative estimate of spatial accessibility that can account for both public and private transportation and the spatial distribution of a service provider’s capacity for service in relation to the distribution of a study area’s population. It uses data for Jefferson County, Kentucky to show how the CSAR model could be used to identify possible disparities in accessing pediatric primary healthcare services. The CSAR model is able to detect relative disparities between defined subpopulations and or geographic regions, allowing for the comparison of the effects of physical infrastructure in access. Combining Transportation Network Models with Kernel Density Methods to Measure the Relative Spatial Accessibility of Pediatric Primary Care Services in Jefferson County, Kentucky