Assessment of multi-level urban healthcare facility accessibility from a human-centric perspective:A case study of Nanjing
Public healthcare service is a key focus in the construction of healthy cities.The rational allocation of urban healthcare facilities(UHCFs)is crucial for promoting urban equity and enhancing residential satisfaction.Urban big data provides support for evaluating the accessibility of public facilities,while numerous studies have been conducted on UHCFs,there are two main issues to be solved.First,the healthcare service system,comprising public health services,medical services,and pharmaceutical supply,forms a hierarchical and collaborative structure,thus the consideration of differences and coordination across the level is required in researches on UHCFs allocation.Second,existing studies often reflect evaluation results in larger urban units such as districts,streets,and communities,which fail to accurately measure the accessibility of primary healthcare services and reflect residents'needs and living differences.Therefore,this study aims to propose a human-centric accessibility evaluation system on multi-level UHCFs.In advance of large-scale and high-precision new data,this study evaluates residents'accessibility to resources from a more micro perspective with residential neighborhoods used as the analytical unit.Based on existing types of healthcare facilities and residents'daily healthcare behaviors,it categorizes the facilities into three types:city hospitals,primary healthcare facilities(including clinics,health centers,and community health service centers),and other healthcare facilities(such as pharmacies and health service shops).It then proposes three indicators—richness,convenience,and matching,to reflect different aspects of residents'needs.The richness index quantifies the diversity of resources available to residents,measured by the number of accessible facilities around a residential area.The convenience index reflects the shortest distance from various levels of facilities to residential points.Considering competition for high-quality resources,the matching index assesses the alignment between resource supply and residents'needs,using the three-step floating catchment area(3SFCA)method.Overall,the accessibility evaluation system comprises eight indicators at the city and community levels.This methodology was applied to the central area of Nanjing,revealing the spatial and quantitative distribution of residential units with varying accessibility.Subsequently,K-means clustering of residential units was employed to understand the characteristics of multi-indicator accessibility types.The research results indicate significant differences in the distribution and spatial patterns of various indicators.The indicators of each dimensions are distinctly directional,revealing differences in outcomes.For instance,in the city center where hospital distribution is dense,the high attraction of medical facilities and population density leads to intense competition,resulting in lower matching scores.The spatial patterns of accessibility for different types of facilities is not consistent.City hospitals in the central area of Nanjing are well-planned spatially,showing minimal disparities in accessibility across different regions.Conversely,the accessibility of primary healthcare facilities is significantly influenced by location.The accessibility of other healthcare facilities,in particular,varies greatly due to market-driven factors and a lack of macro-level regulation.However,some indicators exhibit cross-tier correlations,with a clear relationship between the richness of different levels of facilities.Various levels of healthcare facilities work in tandem to ensure residents'daily health needs.These findings validate the necessity of a multi-tiered,multi-perspective evaluation approach.The evaluation results for the city center exhibit a gradual trend,while the peripheral areas show more drastic changes.Based on accessibility indices,residential units were clustered into eight groups.Types 1 to 5 have relatively balanced indices,whereas Types 6 to 8 display significant deviations from the average.These clusters exhibit distinct spatial distribution characteristics within the city.Representative residential units from each cluster were selected to analyze the relationship between accessibility landscapes and residential population characteristics.Subsequently,targeted measures were proposed to enhance livability for each cluster.This demonstrates the advantage of using residential units as the basis for reflecting the residents'perspective and for conducting refined evaluations.Overall,the evaluation method proposed in this study provides an effective means for fine-grained understanding of resource distribution,helping to reveal disparities in public health resource accessibility among different residential groups and offering targeted improvement suggestions.This method can be applied in future research to establish a comprehensive information platform,addressing issues such as the updating of urban medical resources,urban area expansion,and population growth,ensuring timely review and feedback.It provides scientific basis and decision support for urban public health resource planning and encourages residents to understand and participate in community development.
healthcare service facilitiesresident's perspective3SFCAurban big dataclustering analysis
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