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.