Study on the spatial and temporal differences and influencing factors of out-of-pocket payments as a share of total health expenditure in China.

IF 3 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES BMC Health Services Research Pub Date : 2025-03-29 DOI:10.1186/s12913-025-12631-x
Xiaoyu Dong, Huaizhi Cheng, Ruotong Tian, Lingxiao Gao, Wenpei Lyu, Jiaqi Zhang, Doudou Huang, Bin Guo
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Abstract

Background: Globally, Out-of-pocket (OOP) payments as a share of Total Health Expenditure (THE) has always been a focus of attention in the field of health economics, which affects the economic burden of medical treatment for residents. At present, countries around the world have widely used spatial econometric models to conduct in-depth discussions and analyses of their own OOP, exploring the spatial distribution characteristics and influencing factors of OOP in different regions. However, in China, research in this area is relatively scarce, and few studies have been conducted from a macro perspective and space-time dimension.

Methods: Based on the panel data of 31 provinces in China, the spatiotemporal distribution characteristics of the proportion of OOP payments in China from 2013 to 2022 were analyzed using spatial autocorrelation. The spatial Durbin model (SDM) was employed to explore the factors influencing OOP payments as a share of THE in China.

Results: The results indicate that the proportion of OOP in China shows a decreasing trend, and there is a significant spatial positive correlation. The change in spatial agglomeration is relatively stable, and only some provinces have a slight change. SDM shows that the main factors affecting the inter-provincial differences in the OOP proportion in China include the elderly dependency ratio (direct effect - 0.181, indirect effect - 0.585), the child dependency ratio (direct effect 0.292, indirect effect 0.686), per capita GDP(direct effect 11.235), and the proportion of government health expenditure to fiscal expenditure (direct effect - 0.254, indirect effect - 0.994), the average number of medical visits per year (direct effect - 0.444), the expenditure of basic medical insurance (direct effect - 1.519, indirect effect - 3.940), and the average medical cost of outpatients (direct effect 3.142, indirect effect - 10.064). These factors collectively influence the spatial variation in OOP payments across provinces in China.

Conclusion: The spatial distribution difference of OOP proportion in China is obvious. Factors such as demographics, economics, policy, and health service utilization can all significantly influence OOP. The government should further implement differentiated medical security policies, optimize the allocation structure of health resources, enhance the capacity of primary medical services, promote cross-provincial medical cooperation, and ensure that local residents can enjoy equal access to high-quality medical services and reduce their medical burden.

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中国自费医疗费用占卫生总支出的时空差异及影响因素研究
背景:在全球范围内,自付医疗费用占卫生总支出(THE)的比例一直是卫生经济学领域关注的焦点,它影响着居民的医疗经济负担。目前,世界各国已广泛运用空间计量模型对本国面向对象进行深入探讨和分析,探索不同地区面向对象的空间分布特征及其影响因素。然而,在国内,这方面的研究相对较少,很少从宏观角度和时空维度进行研究。方法:基于中国31个省份的面板数据,利用空间自相关分析2013 - 2022年中国面向对象支付比例的时空分布特征。采用空间Durbin模型(spatial Durbin model, SDM)探讨了影响面向对象支付占国内生产总值比重的因素。结果:结果表明,中国OOP的比例呈下降趋势,且存在显著的空间正相关关系。空间集聚变化较为稳定,个别省份变化不大。SDM结果表明,影响中国省际OOP比例差异的主要因素包括老年人抚养比(直接效应为0.181,间接效应为0.585)、儿童抚养比(直接效应为0.292,间接效应为0.686)、人均GDP(直接效应为11.235)、政府卫生支出占财政支出的比例(直接效应为0.254,间接效应为0.994)、人均年就诊次数(直接效应为0.444)、基本医疗保险支出(直接效应1.519,间接效应3.940),门诊平均医疗费用(直接效应3.142,间接效应10.064)。这些因素共同影响了中国各省面向对象支付的空间差异。结论:中国OOP比例的空间分布差异明显。人口、经济、政策和卫生服务利用等因素都可以显著影响面向对象服务。政府应进一步实施差别化医疗保障政策,优化卫生资源配置结构,提升基层医疗服务能力,促进跨省医疗合作,确保当地居民平等享有优质医疗服务,减轻医疗负担。
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来源期刊
BMC Health Services Research
BMC Health Services Research 医学-卫生保健
CiteScore
4.40
自引率
7.10%
发文量
1372
审稿时长
6 months
期刊介绍: BMC Health Services Research is an open access, peer-reviewed journal that considers articles on all aspects of health services research, including delivery of care, management of health services, assessment of healthcare needs, measurement of outcomes, allocation of healthcare resources, evaluation of different health markets and health services organizations, international comparative analysis of health systems, health economics and the impact of health policies and regulations.
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