Evaluating healthcare resource inequality in Beijing, China based on an improved spatial accessibility measurement

Abstract

In the context of rapid development, Beijing, the capital of China, is facing huge challenges in providing fair healthcare resources to residents. Although Beijing has the best healthcare resources nationwide, a highly concentrated population and uneven distribution of hospitals make the supply of medical resources tight and unbalanced. The objective of this study is to explore the healthcare resource inequality in Beijing based on spatial accessibility. The two‐step floating catchment area method was improved to measure healthcare accessibility by defining a novel distance attenuation function that conforms to the specific travel behavior of taxies to hospitals. We explored the inequality among different places and different populations. It was found that the spatial inequality of healthcare resources was evident and typical, with the dominant resources concentrated in the city center. Some regions are always in an advantageous position regardless of traffic conditions. The impact of some social‐economic factors on healthcare accessibility was analyzed, which exhibited significant spatial heterogeneity. Hospital deserts for different vulnerable populations were identified. Besides children with massive hospital deserts at the city fringe, other vulnerable populations have no distinct disadvantage. These results offer profound comprehension of healthcare inequality to assist in healthcare resources management and policy‐making in Beijing.

A Review of Recent Spatial Accessibility Studies That Benefitted from Advanced Geospatial Information: Multimodal Transportation and Spatiotemporal Disaggregation

“…Kernel density [36], Log-logistic distribution [37], exponential function [38], and hybrid function [39]. The second category involves using different catchment sizes to reflect that rural residents travel further than city residents to offset the low density of infrastructures [40].…”

“…Compared to the first suggestion, in which spatiotemporal accessibility was temporally summarized, in this suggestion, the regions are spatially clustered based on their possible temporal changes (i.e., sequence) in the accessibility [80,81]. Therefore, the temporal sequence would facilitate the examination of the socioeconomic phenomenon related to accessibility [39,82] and propose how the spatial disparity of access can be addressed. For example, assume that the temporal changes in accessibility are summarized as follows: Region A has sufficient accessibility in the morning and limited accessibility during the day, Region B has consistent and sufficient accessibility, and Region C consistently has insufficient accessibility.…”

Measuring and validating spatial accessibility to Covid-19 vaccination sites: a case study in England

“…This is different from the original E2SFCA (Luo and Qi 2009) that incorporates 𝑑 𝑡 that defines the catchment area and represents the cutoff effect. The assumption underlying 𝑑 𝑡 is that healthcare sites only provide servics for population within the catchment area, which is not realistic, especially for rural areas (Wang et al 2020, Gong et al 2021. Therefore, 𝑑 𝑡 is not adopted in our E2SFCA and 3SFCA (see below).…”

“…planning of healthcare services). A few studies have calibrated the distance decay function in the FCA models using taxi trip data (Wang et al 2020, Gong et al 2021 or willingness-to-travel survey data (Rader et al 2021).…”

Supply-Demand Matching of Medical Services in Haikou Under the Background of Hierarchical Diagnosis and Treatment - Based on Didi Travel Data

“…In the eld of accessibility and equity research, based on the accessibility theory [12][13][14], scholars mostly use the two-step oating catchment area method, the Gaussian twostep oating catchment area method, the accessibility of gravity coe cient, the improved potential model and other methods to measure the spatial accessibility of medical service facilities [15][16][17][18]. And from the aspects of method improvement [19][20][21], supply evaluation [22,23], transportation modes [24], spatial effects [25], in uencing factors [26] and other multiple dimensions to expand the connotation and extension of medical accessibility research. In the eld of supply-demand matching, scholars have carried out research based on the supply-demand theory.…”