Interpretation of China’s 2017 health expenditure: a latent profile analysis of panel data
Interpretation of China’s 2017 health expenditure: a latent profile analysis of panel data
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DOI：
10.1136/bmjopen-2019-035512
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发表时间：
2020-06
期刊：
影响因子：
2.9
通讯作者：
Shuang Zang;Meizhen Zhao;OuYang Jing;Xin Wang
中科院分区：
文献类型：
--
作者：
Shuang Zang;Meizhen Zhao;OuYang Jing;Xin Wang
目的探讨中国各省、自治区、直辖市卫生筹资的潜在结构和卫生费用（以住院费用为重点）的机构分布，并分析其外部化和内部化特征。研究设计本研究使用了《2018年中国国民健康账户报告》中的面板数据。方法对2017年中国大陆省级卫生费用数据进行分析。采用潜在剖面分析法对我国卫生筹资和医院卫生支出进行了分析。此外，秩和检验用于了解亚组之间的社会经济指标的差异。结果人均卫生筹资的最佳拟合模型为三个剖面，政府卫生支出（χ2= 10.137，p =0.006）和社会卫生支出（χ2= 6.899，p =0.032）在不同剖面间差异显著。医院卫生费用存在两个流向，流向城市医院、县级医院和社区卫生服务中心的卫生费用在两个流向之间存在显著性差异（p<0.001）。结论不同地区的人均卫生筹资和医疗卫生支出具有不同的社会经济特征，这可能与宏观经济因素和政府政策有关。本研究为我国卫生筹资和卫生政策调控提供了新的思路。
Objective To explore the latent structure of health financing and the institutional distribution of health expenditure (focused on hospital expenditure) in provinces, autonomous regions and municipalities of mainland China, and to examine how these profiles may be related to their externalising and internalising characteristics. Study design The study used panel data harvested from the China National Health Accounts Report 2018. Methods Mainland China’s provincial data on health expenditure in 2017 was studied. A latent profile analysis was conducted to identify health financing and hospital health expenditure profiles in China. Additionally, rank-sum tests were used to understand the difference of socioeconomic indicators between subgroups. Results A best-fitting three-profile solution for per capita health financing was identified, with government health expenditure (χ2=10.137, p=0.006) and social health expenditure (χ2=6.899, p=0.032) varying significantly by profiles. Health expenditure in hospitals was subject to a two-profile solution with health expenditure flow to urban hospitals, county hospitals and community health service centres having significant differences between the two profiles (p<0.001). Conclusions Per capita health financing and health expenditure spent in hospitals have discrepant socioeconomic characteristics in different profiles, which may be attributed to macroeconomic factors and government policies. The study provided new and explicit ideas for health financing and health policy regulation in China.