The primary healthcare facilities are among the most basic needs of the residents, huge in quantity and widespread. Their distributions are directly related to people’s health, which affects the sustainable development of cities. The accessibility calculation of primary level healthcare facilities and the equity evaluation of accessibility from the perspective of medical service category and urban population is very important for the decision-making of layout and configuration but has been ignored for a long time. This study took the primary healthcare facilities of Fukuoka city in Japan as research objects; it first used the variable two-step floating catchment area (V2SFCA) method to calculate the healthcare catchment areas (HCAs) of medical service providers and the population catchment area (PCAs) of medical demand locations, and then obtained the accessibility to primary healthcare facilities. Finally, the spatial disparities of accessibility were evaluated from three aspects: overall space distribution by using Global and Local Moran’s I, service quality, and the population to be served. The results showed that HCAs were from 500 m to 6400 m, PCAs ranged from 500 m to 3000 m, the use of variable catchments can improve the accuracy of accessibility assessment results; the accessibility of primary healthcare facilities was clustered and had significant spatial differences, which were high in urban center and low in suburban area; the obvious differences in the accessibility distribution characteristics of clinics in differential diagnosis and treatment departments led to different degrees of unsaturation in the types of medical services obtained by residents; although the elderly’s demand for basic medical care was many times higher than that of other age groups, the accessibility in high-demand areas was generally low, and the situation in severely high-demand areas was more serious. This work puts forward a multi-dimensional realistic evaluation system for equality accessibility of primary healthcare facilities, providing the data support for the medical resources and facilities’ allocation and the intensive land use.
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