Measuring Spatial Accessibility of Urban Medical Facilities: A Case Study in Changning District of Shanghai in China

Abstract

Medical facilities help to ensure a higher quality of life and improve social welfare. The spatial accessibility determines the allocation fairness and efficiency of medical facilities. It also provides information about medical services that residents can share. Although critical, scholars often overlooked the level of medical facilities, the composition of integrated transportation networks, and the size of service catchment in the literature on accessibility. This study aims to fill this research gap by considering the integrated transportation network, population scale, travel impedance between medical facilities and residential areas, and the impact of medical facilities’ levels on residents’ medical choices. An improved potential model was constructed to analyze the spatial accessibility of medical facilities in Changning District of Shanghai, China. Interpolation analysis was conducted to reveal the spatial accessibility pattern. Cluster and outlier analysis and Getis-Ord Gi* analysis were applied for the cluster analysis. Results show that the spatial accessibility of medical facilities is quite different in different residential areas of Changning District, Shanghai. Among them, the spatial accessibility of medical facilities is relatively high in Hongqiao subdistrict, Xinjing Town, and part of Xinhua Road subdistrict. In addition, residents have overall better access to secondary hospitals than to primary and tertiary hospitals in the study area. This study provides a spatial decision support system for urban planners and policymakers regarding improving the accessibility of healthcare facilities. It extends the literature on spatial planning of public facilities and could facilitate scientific decision making.

Dynamic Demand Evaluation of COVID-19 Medical Facilities in Wuhan Based on Public Sentiment

“…The key to a healthy city is urban healthcare facilities, which are mostly evaluated in existing studies focusing on spatial accessibility, equity [ 73 , 74 , 75 ] and supply-demand balance of healthcare facilities [ 76 , 77 , 78 ]. The outbreak of COVID-19 has reduced the geographic accessibility of medical facilities [ 79 , 80 , 81 , 82 ], and the reduction is greater in the urban periphery than in the central city [ 83 ].…”

Measuring Spatial Accessibility to Hospitals of Acute Myocardial Infarction in Multi Period Scale: A Case Study in Shijingshan District, Beijing, China

“…As far as the study object is concerned, research on hospital accessibility can be roughly divided into four categories: (a) The supply and demand relationship of a specific hospital for a potential population with certain disease [20][21][22][23]; (b) measuring the spatial hospital accessibility for different groups combined social and economic indicators [24][25][26][27][28]; (c) modeling based on population size or facility level to assess and optimize the spatial distribution of medical facilities [29][30][31][32][33]; and (d) spatial comparison of hospital accessibility under different modes of transportation [34][35][36]. For example, Hare and Barcus explored the accessibility of Kentucky's heart-related hospital services by considering the bed-topopulation ratios jointly with the doctor-to-population ratios [20].…”

“…Benevenuto evaluated the accessibility to healthcare centers of low-income groups in rural Brazil using statistical and Geographic Information System (GIS) tools [24]. Cheng analyzed the spatial hospital accessibility in Changning District of Shanghai, China, using the improved potential model (IPM), mainly conducted the cluster and outlier analysis and the Getis-Ord Gi* analysis by ArcGIS tools [29]. Chen used the Gaussian two-step floating catchment area (2SFCA) and the adjusted 2SFCA methods to measure the hospital accessibility of older residents (people aged 60 years or over) who travel mainly by bus in Nanjing, China [34].…”

Spatio-Temporal Disparity and Driving Forces of the Supply Level of Healthcare Service in the Yangtze River Delta

“…As the first law of geography describes that everything is related to everything else, and near things are more related than distant things ( 57 , 58 ), with the more and more obvious spatial trend of humanities and social sciences and the increasingly mature spatial econometric analysis methods, more and more scholars begin to pay attention to spatial dependence, spatial heterogeneity, spatial clustering, and other spatial effects in the study of regional economic growth ( 59 ), environmental and resource efficiency ( 60 ), innovation development ( 61 ), ecological welfare ( 62 ), etc. Moreover, spatial dependence is introduced to identify local spatial cluster and outlier effects of healthcare events ( 63 ), healthcare service industry ( 43 , 64 ), and healthcare facilities ( 65 , 66 ). Although the development of healthcare in the Yangtze River Delta cities is somewhat spatially dependent due to their geographical proximity and similar socioeconomic conditions, the supply of healthcare service is deeply influenced by multidimensional factors that vary considerably across regions and time periods.…”