Evidence map›Paper›PMID 40158076›Full record

ArticleBMC health services research2025

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

Xiaoyu Dong, Huaizhi Cheng, Ruotong Tian, Lingxiao Gao, Wenpei Lyu, Jiaqi Zhang, Doudou Huang, Bin Guo

Abstract read
In one paragraph

Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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7citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xiaoyu Dong *Harbin Medical University-Daqing, Daqing, 163319, China.
Huaizhi Cheng *Harbin Medical University-Daqing, Daqing, 163319, China.
Ruotong TianHarbin Medical University-Daqing, Daqing, 163319, China.
Lingxiao GaoHarbin Medical University-Daqing, Daqing, 163319, China.
Wenpei LyuHarbin Medical University-Daqing, Daqing, 163319, China.
Jiaqi ZhangHarbin Medical University-Daqing, Daqing, 163319, China.
Doudou HuangHarbin Medical University-Daqing, Daqing, 163319, China.
Bin GuoHarbin Medical University-Daqing, Daqing, 163319, China. guobinlover@163.com.

Funding

Daqing Philosophy and Social Science Planning Research Project, China DSGB2024034the Natural Science Foundation of Heilongjiang Province, China LH2023G006
6 · The paper itself

Abstract

backgroundGlobally, 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.

methodsBased 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.

resultsThe 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.

conclusionThe 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.

Indexed as

Financing, PersonalHealth ExpendituresChinaFemaleHumansMaleSpatio-Temporal AnalysisChinaInfluencing factorOut-of-pocket paymentsSpatial dubin modelSpatial-temporal difference

Identifiers

PMID40158076
PMCPMC11954350

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.