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Care providers, access to care, and the Long-term Care Nursing Insurance in China: An agent-based simulation

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  • Chang, Shuang
  • Yang, Wei
  • Deguchi, Hiroshi

Abstract

China piloted a publicly funded Long-term Care Nursing Insurance (LTCNI) with an aim to improve access to long-term care (LTC) for older people in China in 2012. Existing studies showed that the scheme has been successful in meeting some goals, but little is known on how the availability, price and quality of the local care providers affect access to care. Using an Agent-based Modelling approach, this paper simulates the effects of the LTCNI on access to care by considering quality, costs and availability of the local care providers. Our simulation is based on Qingdao city—the first city in China that piloted the LTCNI. We found considerable discrepancies in terms of access to services among the LTCNI beneficiaries. The poor are more likely to choose nursing home care with low costs albeit these services may be of poor quality. The demand for home-based services is high, but these services are not distributed according to population needs and are not available in some districts with high concentration of older people. Consequently, a large proportion of disabled older people have no access to home-based services. We urge policy makers to improve the benefit package of the LTCNI, especially for the poor. We also suggest that more resources should be directed to promote and improve the availability of home-based services in areas with a large number of older people.

Suggested Citation

  • Chang, Shuang & Yang, Wei & Deguchi, Hiroshi, 2020. "Care providers, access to care, and the Long-term Care Nursing Insurance in China: An agent-based simulation," Social Science & Medicine, Elsevier, vol. 244(C).
    • Handle: RePEc:eee:socmed:v:244:y:2020:i:c:s0277953619306628
    DOI: 10.1016/j.socscimed.2019.112667
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    References listed on IDEAS

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    1. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    2. Stefan Holm & Renato Lemm & Oliver Thees & Lorenz M. Hilty, 2016. "Enhancing Agent-Based Models with Discrete Choice Experiments," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(3), pages 1-3.
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    Cited by:

    1. Xiaotian Zhang & Xiaoyun Liu & Yang Wang & Lulin Zhou & Xiaoran Cheng, 2022. "Sustainable Development of China’s Maternity Insurance System in the Context of Population Policy Changes: Using a Grounded Theory Approach," Sustainability, MDPI, vol. 14(4), pages 1-19, February.
    2. Liangwen Zhang & Sijia Fu & Ya Fang, 2020. "Prediction of the Number of and Care Costs for Disabled Elderly from 2020 to 2050: A Comparison between Urban and Rural Areas in China," Sustainability, MDPI, vol. 12(7), pages 1-13, March.
    3. Run-Ping Che & Mei-Chun Cheung, 2022. "Community-Dwelling Older Adults’ Intended Use of Different Types of Long-Term Care in China and Its Associated Factors Based on the Andersen Behavioral Model," IJERPH, MDPI, vol. 19(18), pages 1-16, September.
    4. Liangwen Zhang & Sijia Fu & Ya Fang, 2020. "Prediction the Contribution Rate of Long-Term Care Insurance for the Aged in China Based on the Balance of Supply and Demand," Sustainability, MDPI, vol. 12(8), pages 1-12, April.
    5. Xueqin Deng & Jiaxin Liao & Rong Peng & Jiahao Chen, 2022. "The Impact of Long-Term Care Insurance on Medical Utilization and Expenditures: Evidence from Jingmen, China," IJERPH, MDPI, vol. 19(19), pages 1-18, September.
    6. Lei, Xiaoyan & Bai, Chen & Hong, Jingpeng & Liu, Hong, 2022. "Long-term care insurance and the well-being of older adults and their families: Evidence from China," Social Science & Medicine, Elsevier, vol. 296(C).

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