《中国康复理论与实践》 ›› 2025, Vol. 31 ›› Issue (3): 314-323.doi: 10.3969/j.issn.1006-9771.2025.03.008

• 康复政策与发展 • 上一篇    下一篇

我国深度老龄化地区长期护理保险政策的量化评价:基于PMC指数模型分析

刘嘉慧1a,2,3, 杨梦娇1a,2,3, 王伊凡1a,2,3, 王瑞璇1b,2,3, 宋婧1b,2,3, 李晓纯1b,2,3, 杨春晓1b,2,3, 丰志强4, 谢雨薇4, 桑新刚5(), 尹文强1a,2,3()   

  1. 1.山东第二医科大学,a.管理学院;b.公共卫生学院,山东潍坊市 261053
    2.“健康山东”重大社会风险预测与治理协同创新中心,山东潍坊市 261053
    3.国民健康社会风险预警协同创新中心,上海市 200032
    4.国家卫生健康委卫生发展研究中心,北京市 100044
    5.潍坊市卫生健康委员会,山东潍坊市 261061
  • 收稿日期:2024-11-28 修回日期:2025-01-31 出版日期:2025-03-25 发布日期:2025-03-25
  • 通讯作者: 桑新刚(1983-),男,博士,主要研究方向:卫生管理与政策研究,E-mail:sangxingang@163.com;尹文强(1969-),男,博士,教授,主要研究方向:卫生管理与政策研究,E-mail:yinwq1969@126.com
  • 作者简介:刘嘉慧(2002-),女,汉族,山东潍坊市人,硕士研究生,主要研究方向:卫生管理与政策研究。
  • 基金资助:
    1.教育部人文社会科学研究规划基金项目(22YJAZH137);2.山东省重点研发计划项目(2022RKY07002);3.潍坊市公立医院改革与高质量发展示范项目(SDGP370700000202402000604A 001)

Quantitative evaluation of long-term care insurance policy in China's deeply aging areas: based on PMC index model

LIU Jiahui1a,2,3, YANG Mengjiao1a,2,3, WANG Yifan1a,2,3, WANG Ruixuan1b,2,3, SONG Jing1b,2,3, LI Xiaochun1b,2,3, YANG Chunxiao1b,2,3, FENG Zhiqiang4, XIE Yuwei4, SANG Xin'gang5(), YIN Wenqiang1a,2,3()   

  1. 1. a. School of Management; b. School of Public Health, Shandong Second Medical University, Weifang, Shandong 261053, China
    2. "Health Shandong" Severe Social Risk Prevention and Management Synergy Innovation Center, Weifang, Shandong 261053, China
    3. Collaborative Innovation Center of Social Risks Governance in Health, Shanghai 200032, China
    4. Health Development Research Center, National Health Commission, Beijing 100044, China
    5. Weifang Municipal Health Commission, Weifang, Shandong 261061, China
  • Received:2024-11-28 Revised:2025-01-31 Published:2025-03-25 Online:2025-03-25
  • Contact: SANG Xin'gang, E-mail: sangxingang@163.com; YIN Wenqiang, E-mail: yinwq1969@126.com
  • Supported by:
    Ministry of Education of China Humanities and Social Sciences Planning(22YJAZH137);Shandong Provincial Key Research and Development Project(2022RKY07002);Weifang Public Hospital Reform and High-quality Development Demonstration Project(SDGP370700000202402000604A 001)

摘要:

目的 量化分析我国深度老龄化地区长期护理保险政策,分析政策结构和内容。

方法 采用政策建模一致性(PMC)指数模型指标设计方法,构建由9个一级指标和34个二级指标组成的长期护理保险政策评价指标体系。以我国深度老龄化地区2014年6月1日至2024年10月1日出台的123份省级长期护理保险政策为研究对象,采用ROSTCM 6.0进行高频词提取,绘制长期护理保险政策社会网络图,采用政策评价指标体系对政策结构和内容进行量化评价和分析。

结果 我国深度老龄化地区长期护理保险政策的主要内容涉及服务、机构、评估等。政策最高7.28分,最低2.20分,平均5.00分。共有25项完美政策、63项优秀政策、28项良好政策和7项合格政策。政策评价、政策对象、政策性质、政策视角和政策工具5个一级变量的平均分均> 0.60;政策内容、激励约束、政策时效和政策级别4个一级变量的平均分均< 0.50。

结论 我国深度老龄化地区出台的长期护理保险政策在政策评价、政策对象、政策性质等方面覆盖较为全面,在政策工具选择和激励约束机制构建方面仍需提升。

关键词: 老龄化, 长期护理保险, 政策评价, 政策建模一致性指数模型

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 evaluation 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 analyzed 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 policy evaluation, policy target groups and policy nature, and need to be improved in policy tool selection and the construction of incentive and constraint mechanisms.

Key words: aging, long-term care insurance, policy evaluation, Policy Modeling Consistency index model

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