Measuring spatial accessibility and equity to healthcare services using fuzzy inference system

The inequity in accessibility to healthcare services and their distribution for urban and rural populations are always major challenges for health planners and policy makers. The present study focuses on challenges associated with estimating the geographical scope of access to health services in rural and remote areas. Assuming that measuring GIS-based accessibility for rural health services varies across a geographic analysis unit, estimating techniques can influence the analysis and interpretation of spatial access to rural healthcare services. Thus, this study aims to provide a spatial model for accessibility measurement of health services based on the fuzzy inference system (FIS). Accessibility to health services is not distributed equitably across the study area. The results revealed that higher levels of accessibility to health services appear in the central parts of the Fars province while lower levels of exist in its northern and southern parts, except a few small regions adjacent to the southern borders of the province. The level of accessibility is high around the urban centers, where there is a high concentration of services and population, but it reaches its minimum on the margins. The minimum travel time to health services tends to increase from urban centers and populated villages to more rural and remote areas. About 62.8 percent of the rural population was found to have high accessibility (very high and high classes) to healthcare, while 14.5 percent of the rural population have low accessibility (very low and low classes). This method of analysis can be used as a guide for planners to strategically plan infrastructure investment for areas with lower accessibility to healthcare services. It also provides adequate healthcare options required in targeted locations.