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The Health Status Transition and Medical Expenditure Evaluation of Elderly Population in China

Author

Listed:
  • Lianjie Wang

    (School of Public Administration, Zhejiang University of Finance and Economics, Hangzhou 310018, China)

  • Yao Tang

    (School of Public Administration, Zhejiang University of Finance and Economics, Hangzhou 310018, China)

  • Farnaz Roshanmehr

    (Shibata Laboratory, School of Advanced Science and Engineering, Waseda University, Tokyo 162-8480, Japan
    Kagawa Nutrition University, Saitama 350-0288, Japan)

  • Xiao Bai

    (School of Finance, Zhejiang University of Finance and Economics, Hangzhou 310018, China)

  • Farzad Taghizadeh-Hesary

    (Clinical Oncology Department, Shahid Beheshti University of Medical Sciences, Tehran 19857-17443, Iran)

  • Farhad Taghizadeh-Hesary

    (Social Science Research Institute, Tokai University, Tokyo 259-1292, Japan)

Abstract

(1) Background: Because of the rapid expansion of the aging population in China, their health status transition and future medical expenditure have received increasing attention. This paper analyzes the health transition of the elderly and how their health transition impacts medical expenditures. At the same time, feasible policy suggestions are provided to respond to the rising medical expenditure and the demand for social care. (2) Methods: The data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2015 and analyzed using the Markov model and the Two-Part model (TPM) to forecast the size of the elderly population and their medical expenditures for the period 2020–2060. (3) Results: The study indicates that: (1) for the elderly with a mild disability, the probability of their health improvement is high; in contrast, for the elderly with a moderate or severe disability, their health deterioration is almost certain; (2) the frequency of the diagnosis and treatments of the elderly is closely related to their health status and medical expenditure; alternatively, as the health status deteriorates, the intensity of the elderly individuals’ acceptance of their diagnosis and treatment increases, and so does the medical expense; (3) the population of the elderly with mild and moderate disability demonstrates an inverted “U”-shape, which reaches a peak around 2048, whereas the elderly with severe disability show linear growth, being the target group for health care; (4) with the population increase of the elderly who have severe disability, the medical expenditure increases significantly and poses a huge threat to medical service supply. Conclusions: It is necessary to provide classified and targeted health care according to the health status of the elderly. In addition, improving the level of medical insurance, establishing a mechanism for sharing medical expenditure, and adjusting the basic demographic structure are all important policy choices.

Suggested Citation

  • Lianjie Wang & Yao Tang & Farnaz Roshanmehr & Xiao Bai & Farzad Taghizadeh-Hesary & Farhad Taghizadeh-Hesary, 2021. "The Health Status Transition and Medical Expenditure Evaluation of Elderly Population in China," IJERPH, MDPI, vol. 18(13), pages 1-14, June.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:13:p:6907-:d:583391
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    References listed on IDEAS

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    Cited by:

    1. Mo Hu & Zhiyuan Hao & Yinrui Yin, 2022. "Promoting the Integration of Elderly Healthcare and Elderly Nursing: Evidence from the Chinese Government," IJERPH, MDPI, vol. 19(24), pages 1-18, December.
    2. Lu Chen & Miaoting Cheng, 2022. "Exploring Chinese Elderly’s Trust in the Healthcare System: Empirical Evidence from a Population-Based Survey in China," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    3. Lianjie Wang & Yao Tang, 2024. "RETRACTED ARTICLE: The impact of long-term care insurance on household consumption and sustainability among aged people in China," Economic Change and Restructuring, Springer, vol. 57(2), pages 1-32, April.
    4. Shujie Zou & Chiawei Chu & Ning Shen & Jia Ren, 2023. "Healthcare Cost Prediction Based on Hybrid Machine Learning Algorithms," Mathematics, MDPI, vol. 11(23), pages 1-13, November.
    5. Lianjie Wang & Yao Tang, 2023. "Changing Trends and the Effectiveness of Informal Care Among Rural Elderly Adults in China," SAGE Open, , vol. 13(4), pages 21582440231, October.

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