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Medical Treatment Behaviour of the Elderly Population in Shanghai: Group Features and Influencing Factor Analysis

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  • Shangguang Yang

    (School of Business, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China)

  • Danyang Wang

    (School of Business, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China)

  • Chen Li

    (Institute of Future Cities, Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong 999077, China)

  • Chunlan Wang

    (Chinese Modern City Research Center, School of Social Development, East China Normal University, Shanghai 200062, China)

  • Mark Wang

    (School of Geography, The University of Melbourne, Parkville, VIC 3010, Australia)

Abstract

Background: While Chinese cities are pursuing economic development, meeting citizen demand for medical treatment has only gradually been put on the agenda. Theoretically, in the second half of a person’s life, demand for medical treatment will rise sharply. Given limited medical resources, the match between demand and supply becomes more difficult. We conducted questionnaires in Shanghai to describe whether there are obvious group differences in the elderly population’s medical treatment options and provide empirical evidence on the determinants. Method: We collected 439 Shanghai Elderly Medical Demand Characteristics Questionnaires, which included five parts: personal information, health status, elderly person’s medical preference and expectation, satisfaction level for hospitals services, and medical insurance. We set up virtual explanatory variables according to the different medical behaviours of the elderly, and control variables composed of individual characteristics, socioeconomic characteristics, medical needs, medical resource availability, and medical expenditure. We used the MLR model to investigate medical treatment behaviour choice. Results: The medical treatment behaviour of the elderly population in Shanghai is affected by multiple factors. When experiencing physical discomfort, most of them choose to go to the hospital (64.69%). Age, income, household registration, and medical insurance reimbursement policy play a role in their decision-making. For general diseases, the proportion choosing specialist hospitals or community clinics is the highest (40.78%). Age, marital status, residential status, physical state, objective distance, medical expenses, and other factors have a significant impact. For severe diseases, they are more inclined (71.07%) to visit general hospitals, with the individual’s physical condition, living status, and accessibility to hospital resources more likely to affect their behaviour. Conclusion: Firstly, the importance of each factor varies depending on the conditions. Secondly, it may be more appropriate for China’s elderly health insurance system to set reimbursement rates based on the patient’s condition and disease type. Thirdly, medical behaviour has a distance friction effect, but the allocation of public service resources shows a strong centripetal concentration. It is necessary for the government to show due care about the regional distribution of the elderly population and to promote the rational distribution of medical resources in Shanghai.

Suggested Citation

  • Shangguang Yang & Danyang Wang & Chen Li & Chunlan Wang & Mark Wang, 2021. "Medical Treatment Behaviour of the Elderly Population in Shanghai: Group Features and Influencing Factor Analysis," IJERPH, MDPI, vol. 18(8), pages 1-21, April.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:8:p:4108-:d:535413
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    References listed on IDEAS

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    Cited by:

    1. Jiongxun Chen & Linxiu Wang & Tiantian Gu & Chenyang Wang & Enyang Hao, 2023. "Demands for Community Services and Associated Factors among Residents in Smart Communities: A Case Study of Xuzhou City," IJERPH, MDPI, vol. 20(4), pages 1-19, February.
    2. Cao, Wen-Rui & Huang, Qiu-Ru & Zhang, Nan & Liang, Hui-Juan & Xian, Ben-Song & Gan, Xiao-Fang & Xu, Dong Roman & Lai, Ying-Si, 2022. "Mapping the travel modes and acceptable travel time to primary healthcare institutions: A case study in Inner Mongolia Autonomous Region, China," Journal of Transport Geography, Elsevier, vol. 102(C).

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