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基于门诊预约大数据的各类城市医疗服务空间可达性定量评价。

Quantitative Evaluation of Spatial Accessibility of Various Urban Medical Services Based on Big Data of Outpatient Appointments.

机构信息

Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.

University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Int J Environ Res Public Health. 2023 Mar 13;20(6):5050. doi: 10.3390/ijerph20065050.

DOI:10.3390/ijerph20065050
PMID:36981964
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10048955/
Abstract

Equity of urban medical services affects human health and well-being in cities and is important in building 'just' cities. We carried out a quantitative analysis of the spatial accessibility of medical services considering the diverse demands of people of different ages, using outpatient appointment big data and refining the two-step floating catchment area (2SFCA) method. We used the traditional 2SFCA method to evaluate the overall spatial accessibility of medical services of 504 communities in Xiamen city, considering the total population and the supply of medical resources. Approximately half the communities had good access to medical services. The communities with high accessibility were mainly on Xiamen Island, and those with low accessibility were further from the central city. The refined 2SFCA method showed a more diverse and complex spatial distribution of accessibility to medical services. Overall, 209 communities had high accessibility to internal medicine services, 133 to surgery services, 50 to gynecology and obstetrics services, and 18 to pediatric services. The traditional method may over-evaluate or under-evaluate the accessibility of different types of medical services for most communities compared with the refined evaluation method. Our study can provide more precise information on urban medical service spatial accessibility to support just city development and design.

摘要

城市医疗服务公平性影响城市居民的健康和福祉，对建设“公正”城市具有重要意义。本研究考虑不同年龄人群的多样化需求，利用门诊预约大数据，采用改进的两步移动搜索法（2SFCA）对医疗服务的空间可达性进行了定量分析。本研究采用传统的 2SFCA 方法，基于总人口和医疗资源供给，评估了厦门市 504 个社区的医疗服务整体空间可达性。约一半的社区具有较好的医疗服务可达性。高可达性社区主要位于厦门岛内，低可达性社区则离市中心更远。改进的 2SFCA 方法显示，医疗服务可达性的空间分布更加多样和复杂。总体而言，209 个社区具有较高的内科服务可达性，133 个社区具有较高的外科服务可达性，50 个社区具有较高的妇产科服务可达性，18 个社区具有较高的儿科服务可达性。与改进的评价方法相比，传统方法可能会高估或低估大多数社区不同类型医疗服务的可达性。本研究可为城市医疗服务空间可达性提供更精确的信息，支持公正城市的发展和规划。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/73a76bd6ffeb/ijerph-20-05050-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/b629317de6c5/ijerph-20-05050-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/cee3b523a72b/ijerph-20-05050-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/25b1d1c6eddf/ijerph-20-05050-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/7a4493e6c495/ijerph-20-05050-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/4399b6760d92/ijerph-20-05050-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/f6747d8d7193/ijerph-20-05050-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/1ac9e8bd304d/ijerph-20-05050-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/cd0db7183f03/ijerph-20-05050-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/ea9fc5ccabed/ijerph-20-05050-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/17c90ad7cfcb/ijerph-20-05050-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/8adce87f0272/ijerph-20-05050-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/73a76bd6ffeb/ijerph-20-05050-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/b629317de6c5/ijerph-20-05050-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/cee3b523a72b/ijerph-20-05050-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/25b1d1c6eddf/ijerph-20-05050-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/7a4493e6c495/ijerph-20-05050-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/4399b6760d92/ijerph-20-05050-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/f6747d8d7193/ijerph-20-05050-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/1ac9e8bd304d/ijerph-20-05050-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/cd0db7183f03/ijerph-20-05050-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/ea9fc5ccabed/ijerph-20-05050-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/17c90ad7cfcb/ijerph-20-05050-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/8adce87f0272/ijerph-20-05050-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/373b/10048955/73a76bd6ffeb/ijerph-20-05050-g012.jpg

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