| 引用本文：杨红燕, 范维珂, 蒋雯静.长期护理保险基金筹资负担的测算——基于8城长护险试点方案的比较分析[J].中国卫生政策研究,2023,16(6):1-9 |
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| 长期护理保险基金筹资负担的测算——基于8城长护险试点方案的比较分析 |
| 投稿时间：2023-03-13 修订日期：2023-05-12 PDF全文浏览 HTML全文浏览 |
| 杨红燕1,2, 范维珂2, 蒋雯静2 |
1. 武汉大学社会保障研究中心 湖北武汉 430072;
2. 武汉大学政治与公共管理学院 湖北武汉 430072 |
| 摘要:本文使用宏观与微观数据，建立马尔可夫模型，预测2021—2030年全国失能老人规模，并对预测结果进行校准缩减误差率。基于试点政策测算第二批8城长护险试点方案的筹资负担，探究长护险筹资方案的完善方向。发现2021—2030年同期重度失能老人规模在校准后增加5%~7%，支出压力上涨6%，收不抵支节点的出现提前1—2年。针对此情况提出北京、开封方案需设置动态筹资增长率，以社会医疗保险缴费基数为基础的南宁、福州方案考虑调整筹资比例等建议。 |
| 关键词:长期护理保险 筹资负担 测算 比较分析 |
| 基金项目:教育部规划基金项目（22YJA630101）；武汉大学自主科研项目（人文社会科学）“中央高校基本科研业务费专项资金”；教育部人文社科重点研究基地自设项目“长期护理保险政策效应研究”；国家自然科学基金面上项目（72274145） |
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| Estimation of the financing burden of long-term care insurance funds: Comparative analysis based on 8 LTC insurance pilot regions |
| YANG Hong-yan1,2, FAN Wei-ke2, JIANG Wen-jing2 |
1. Center for Social Security Studies of Wuhan University, Wuhan Hubei 430072, China;
2. School of Politics Science and Public Administration, Wuhan University, Wuhan Hubei 430072, China |
| Abstract:Based on macro data and micro data, this paper builds Markov model to predict the size of the disabled elderly from 2021 to 2030, and calibrate the prediction results to reduce the error rate. Next, based on the pilot policy, the financing burden of the second batch of long-term care pilot programs in 8 cities was measured, and the improvement direction of long-term care insurance financing programs was explored. After the calibration, it is found that the size of the severely disabled elderly in the same period from 2021 to 2030 increased by 5%~7%, the expenditure risen by 6%, and the node when revenue fails to cover the expenditure advanced by 1~2 years. In response to this situation, it is suggested that the programs of Beijing and Kaifeng need to set dynamic funding growth rates, and the programs of Nanning and Fuzhou which are based on social health insurance contribution base consider adjusting the funding ratio. |
| Key words:Long-term care insurance Financing burden Estimation Comparative analysis |
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