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Equity and Driving Factors of Medical Service Supply–Demand Balance for the Elderly in Rapidly Urbanized Communities Based on Big Data Analysis—A Case Study of Xiamen City

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  • Jinling Sui

    (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)

  • Tao Lin

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
    Xiamen Key Laboratory of Smart Management on the Urban Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

  • Guoqin Zhang

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
    Xiamen Key Laboratory of Smart Management on the Urban Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

  • Hong Ye

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
    Xiamen Key Laboratory of Smart Management on the Urban Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

  • Meixia Lin

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
    Xiamen Key Laboratory of Smart Management on the Urban Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

  • Hongkai Geng

    (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)

  • Yukui Zhang

    (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)

Abstract

Against the backdrop of rapid population aging and significant demographic changes, cities are facing great challenges in providing healthcare resources for the elderly. Understanding the equity and spatial differentiation mechanisms between the demand and supply of healthcare resources for the elderly in cities, especially in rapidly urbanized areas, can help policymakers to promote the planning and construction of a ‘Just City’ and ‘Age-Friendly City’, safeguarding the human well-being of the elderly. This study combines outpatient appointment data classified by service type with community-scale demographic data to assess the equity in the supply of medical resources for the elderly in the city using a refined two-step moving search method. Taking Xiamen City as an example, we analyzed the spatial heterogeneity in the equity in the supply of different types of health care services for potential elderly patients in each community in the city. Then, we selected six driving factors to explore the underlying driving factors. The results showed that there were 308 communities (61.11%) with a high medical service balance of the internal medicine type for the elderly in Xiamen City, concentrated in the southwest of the whole area. There are only 157 communities with high medical service balance for the surgical type of medical services, concentrated in the central part and southwest of Xiamen City. For these two types of medical services, the number of communities with low medical service balance is 30 (5.95%) and 182 (36.11%), respectively. These communities are far away from the central city. Economic vitality is the most important driving factor in the spatial distribution pattern of equity in the balance of medical services for the elderly. Our study can provide quantitative information on the current situation evaluation and decision support for the development and design of a ‘Just City’ and ‘Age-Friendly City’ Planning.

Suggested Citation

  • Jinling Sui & Tao Lin & Guoqin Zhang & Hong Ye & Meixia Lin & Hongkai Geng & Yukui Zhang, 2023. "Equity and Driving Factors of Medical Service Supply–Demand Balance for the Elderly in Rapidly Urbanized Communities Based on Big Data Analysis—A Case Study of Xiamen City," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:8014-:d:1147054
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    References listed on IDEAS

    as
    1. Jinling Sui & Guoqin Zhang & Tao Lin & Nicholas A. S. Hamm & Chunlin Li & Xian Wu & Kaiqun Hu, 2023. "Quantitative Evaluation of Spatial Accessibility of Various Urban Medical Services Based on Big Data of Outpatient Appointments," IJERPH, MDPI, vol. 20(6), pages 1-18, March.
    2. Jiansheng Wu & Jiayi Fu & Hongliang Wang & Yuhao Zhao & Tengyun Yi, 2022. "Identifying Spatial Matching between the Supply and Demand of Medical Resource and Accessing Carrying Capacity: A Case Study of Shenzhen, China," IJERPH, MDPI, vol. 19(4), pages 1-22, February.
    3. E. Van de Poel & O. O'Donnell & E. Van Doorslaer, 2012. "Is there a health penalty of China's rapid urbanization?," Health Economics, John Wiley & Sons, Ltd., vol. 21(4), pages 367-385, April.
    4. Gerardo Carpentieri & Carmen Guida & Houshmand E. Masoumi, 2020. "Multimodal Accessibility to Primary Health Services for the Elderly: A Case Study of Naples, Italy," Sustainability, MDPI, vol. 12(3), pages 1-15, January.
    5. Kanuganti, Shalini & Sarkar, Ashoke Kumar & Singh, Ajit Pratap, 2016. "Evaluation of access to health care in rural areas using enhanced two-step floating catchment area (E2SFCA) method," Journal of Transport Geography, Elsevier, vol. 56(C), pages 45-52.
    6. Yu Zhao & Guoqin Zhang & Tao Lin & Xiaofang Liu & Jiakun Liu & Meixia Lin & Hong Ye & Lingjie Kong, 2018. "Towards Sustainable Urban Communities: A Composite Spatial Accessibility Assessment for Residential Suitability Based on Network Big Data," Sustainability, MDPI, vol. 10(12), pages 1-18, December.
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