摘要
目的:扎实推进我国长期护理保险制度建设是健全社会保障体系的重要内容,也是建设健康中国的关键举措。方法:本文基于政策扩散理论,采用时序分析法与政策文献参照网络分析法,对2012年至2024年间我国长期护理保险政策进行量化研究,旨在揭示政策扩散的过程与特点。结果:长期护理保险政策扩散强度呈现出时序性聚集特点,主要集中于2016年至2021年,并呈现出多中心的雪花型扩散网络结构;政策扩散强度与广度位列前两位的均为国家部委意见类政策,且地方政策呈现出较强的区域特性;通过关键词时序分析发现,长期护理保险政策呈现“先自下而上,后自上而下”的扩散特征。结论:本研究展现了我国长期护理保险政策扩散的复杂性和多层次性,有助于揭示国家健康战略贯彻到地方养老政策的过程,为未来长期护理保险政策的制定和实施提供有益的启示。
Objective:Solidly promoting the construction of China's long-term care insurance system is an important part of improving the social security system and a key measure to build Healthy China.Methods:Based on the policy diffusion theory,this paper uses the time series analysis method and the policy literature reference network analysis method to quantitatively study the long-term care insurance policies in China from 2012 to 2024,revealing the process and characteristics of policy diffusion.Results:The diffusion intensity of long-term care insurance policies shows the characteristics of temporal aggregation,mainly concentrated on the year from 2016 to 2021,and presents a multi-center snowflake-shaped diffusion network structure.The top two policies in terms of diffusion intensity and breadth are all opinion policies from national ministries and commissions,and local policies show strong regional characteristics.Through keyword time series analysis,it is found that long-term care insurance policies show the diffusion characteristics of"first bottom-up,then top-down".Conclusion:This study shows the complexity and multi-level nature of the diffusion of long-term care insurance policies in China,which is helpful to reveal the process of implementing the national health strategy into local pension policies,and provides useful enlightenment for the formulation and implementation of long-term care insurance policies in the future.
出处
《中国医疗保险》
2024年第11期82-90,共9页
China Health Insurance
基金
江西省智库研究重点项目基金支持“‘一带一路’背景下推动江西特色中医药文化对外传播研究”(23ZB07)
江西省自然科学基金管理科学类项目基金支持“科研经费‘包干制’政策研究”(20212BAA10004)。
关键词
长期护理保险
政策扩散
政策文本计量
long-term care insurance
policy diffusion
policy text measurement