Quantitative evaluation of long-term care insurance policy in China's deeply aging areas:based on PMC index model
LIU Jiahui
YANG Mengjiao
WANG Yifan
WANG Ruixuan
SONG Jing
LI Xiaochun
YANG Chunxiao
FENG Zhiqiang
XIE Yuwei
SANG Xin'gang
YIN Wenqiang
Abstract：Objective To quantitatively evaluate the structure and content of the long-term care insurance(LTCI)policy in China's deeply aging areas.
Methods Using the Policy Modeling Consistency(PMC)index model indicator design method,a LTCI policy evalua-tion index system was constructed,consisting of nine primary indicators and 34 secondary indicators.A total of 123 provincial-level LTCI policies issued in deeply aging regions of China between June 1,2014,and October 1,2024 were analyzed.High-frequency word extraction was performed using ROSTCM 6.0,and a social network diagram of LTCI policies was created.The policy structure and content were quantitatively evaluated and ana-lyzed based on the established policy evaluation index system.
Results The main content of LTCI policies in deeply aging areas of China covered services,institutions and assessment.The highest policy score was 7.28,and the lowest was 2.20,with an average score of 5.00.There were 25 perfect policies,63 excellent policies,28 good policies and seven qualified policies.In the dimension of policy content,the indexes of five primary indicators of policy evaluation,policy target groups,policy nature,policy perspective and policy tools were 0.60 or more;while the indexes of four primary indicators of policy content,incentives and constraints,policy timeliness,and policy level were 0.50 or less.
Conclusion LTCI policies issued in China's deeply aging areas provide comprehensive coverage in aspects such as poli-cy evaluation,policy target groups and policy nature,and need to be improved in policy tool selection and the construction of incentive and constraint mechanisms.
Keywords：aginglong-term care insurancepolicy evaluationPolicy Modeling Consistency index model
Publication Date：2025-03-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 314-323 )