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社区医疗保健整合与财政支出：基于合成控制法的证据

Community health care integration and fiscal expenditures: evidence from a synthetic control approach.

作者信息

Xiang Yi, Zhong Guangjing, Lei Xiaofeng, Liu Longqing

机构信息

College of Public Administration and Law, Hunan Agricultural University, Changsha, China.

Institute of Agricultural Economics and Agricultural Zoning, Hunan Academy of Agricultural Sciences, Changsha, China.

出版信息

Front Public Health. 2025 May 23;13:1524984. doi: 10.3389/fpubh.2025.1524984. eCollection 2025.

DOI:10.3389/fpubh.2025.1524984
PMID:40487521
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12143234/
Abstract

BACKGROUND

Does the implementation of community healthcare integration policies affect fiscal expenditures as a key measure in addressing older healthcare demands and promoting healthy aging?

METHODS

This study utilizes the implementation of community healthcare integration in Yantai, a prefecture-level city in China, as a natural experiment to analyze its fiscal expenditure consequences by using the synthetic control approach.

RESULTS

Our empirical findings indicate that the program implementation markedly decreased fiscal expenditures in pilot cities. The decrease in expenditure is solely due to policy execution, with no confounding variables detected. The program implementation negatively impacted fiscal expenditures mainly by decreasing government healthcare spending in pilot zones.

CONCLUSION

Consequently, in the ongoing effort to enhance community healthcare integration, local governments must devise context-tailored implementation strategies to attain sustainable growth, alleviate fiscal burdens, and improve older adult care services.

摘要

背景

实施社区医疗整合政策作为应对老年人医疗需求和促进健康老龄化的关键举措，是否会影响财政支出？

方法

本研究以中国地级市烟台实施的社区医疗整合为自然实验，采用合成控制法分析其财政支出后果。

结果

我们的实证研究结果表明，该项目实施显著降低了试点城市的财政支出。支出减少完全是由于政策执行，未检测到混杂变量。该项目实施主要通过减少试点地区的政府医疗支出对财政支出产生负面影响。

结论

因此，在持续推进社区医疗整合的过程中，地方政府必须制定因地制宜的实施策略，以实现可持续增长、减轻财政负担并改善老年人护理服务。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/28b35a8e7964/fpubh-13-1524984-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/bd41a9005502/fpubh-13-1524984-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/cb6a371645f9/fpubh-13-1524984-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/6f76aa71d8c3/fpubh-13-1524984-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/f67bfcc8e124/fpubh-13-1524984-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/546c1b64e987/fpubh-13-1524984-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/28b35a8e7964/fpubh-13-1524984-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/bd41a9005502/fpubh-13-1524984-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/cb6a371645f9/fpubh-13-1524984-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/6f76aa71d8c3/fpubh-13-1524984-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/f67bfcc8e124/fpubh-13-1524984-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/546c1b64e987/fpubh-13-1524984-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a27b/12143234/28b35a8e7964/fpubh-13-1524984-g006.jpg

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