How to evaluate long-term care insurance policy based on policy tools and PMC index model: evidence from pilot cities in China

如何基于政策工具和PMC指数模型评价长期护理保险政策:来自中国试点城市的证据

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Abstract

OBJECTIVE: To address the risk of disability arising from population aging, the long-term care insurance (LTCI) policy in China has been progressively piloted and expanded. This study aims to examine the tool combination and strengths and weaknesses of the LTCI policy through a textual quantitative analysis of policies issued in 29 pilot cities, thereby providing a reference for refining the policy framework. METHODS: Seventy-nine LTCI policies were analyzed based on the two-dimensional analytical framework regarding policy tools and policy ratings. Policy texts were coded and analyzed according to the connotative elements of supply-, environment- and demand-based policy tools, while policy ratings with strengths and weaknesseswere analyzed according to the Policy Modeling Consistency (PMC) index model. RESULTS: LTCI policies of the 29 pilot cities all showed that the use of environment-based policy tools accounted for more than 70%, and supply- and demand-based policy tools ranged from 10 to 16%. The mean of the PMC index for the 79 policies was 7.701, with low scores across variables such as policy timeliness, policy level, and incentive and constraint, and an overall policy rating of good. Among these, the policies issued by the second batch of pilot cities had the highest PMC index value of 7.781. CONCLUSION: Pilot cities were over-utilizing environment-based policy tools and under-utilizing supply- and demand-based policy tools, which can be attributed to the reliance on environmental shaping during the policy pilot phase. LTCI policies of pilot cities can promote the development and improvement of the LTCI system, but there is still room for refinement in terms of policy authority, timeliness, coverage, and incentive measures. LTCI policies of the second batch of pilot cities were rated relatively higher, with higher-rated policies making more even use of various policy tools.

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