Assessing the Sustainability of Long-Term Care Insurance Systems Based on a Policy-Population-Economy Complex System: The Case Study of China

Int J Environ Res Public Health. 2022 May 27;19(11):6554. doi: 10.3390/ijerph19116554.

Abstract

Although China launched long-term care insurance (LTCI) pilot program in 2016, there are great challenges associated with developing a sustainable LTCI system due to limited financial resources and a rapid increase in the aging population. This study constructed an LTCI policy−population−economics (PPE) system to assess the sustainability of the LTCI system in China. Based on the latest 76 LTCI policy documents published between 2016 and 2021, this study evaluated the strength of LTCI policy modeling in 14 pilot cities by constructing a policy modeling consistency (PMC) index containing 9 main variables and 36 sub-variables. The coupling coordination model was used to evaluate the interaction between LTCI policy, population aging, and economic development. The results showed that the PMC index ranged from 0.527 to 0.850. The policy strength of Qingdao, Nantong, and Shanghai was the highest (PMC > 0.8). Anqing, Qiqihaer, Chongqing, and Chengdu had the lowest level of policy strength (PMC < 0.6). The main policy weaknesses were the coverage of the LTCI, the sources of funds, the scope of care services, and benefit eligibility. The coupling coordination degree of PPE systems varied from 0.429 to 0.921, with a mean of 0.651. Shanghai, Nantong, and Suzhou had the highest level of coordination. The coordination between subsystems of PPE in most pilot cities (12 of 14 cities) was at a basic or low level. The findings from this study concluded that the coordination within the PPE system should be improved to develop a sustainable LTCI system. To improve the coordination of the PPE system, it is suggested that the country should maintain sustainable economic growth and modify LTCI policies based on demographic transitions and economic development.

Keywords: coupling coordination degree; long-term care insurance; pilot scheme; policy modeling; policy strength.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aging*
  • China
  • Cities
  • Humans
  • Insurance, Long-Term Care*
  • Long-Term Care
  • Policy

Grants and funding

This research was funded by the National Natural Science Foundation of China (grant number 72074055), the Innovation Team Project of Guangdong Provincial Department of Education (grant number 2020WCXTD014), and the Scientific Research Project of the Guangdong Provincial Department of Education (grant number 2018WZDXM004).