ArticleBMC health services research2019
What has driven the spatial spillover of China's out-of-pocket payments?
Article in BMC health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- PROTOCOL: Evidence and Gap Map of Studies of the Effects of Health Interventions to Reduce Out-of-Pocket Expenses.Campbell systematic reviews · 2026Article
- From individual burden to social risk pooling: drivers of the declining out-of-pocket health expenditure share in China (2009-2024).International journal for equity in health · 2026Article
- Spatiotemporal characteristics of health expenditure in mainland China during 2012-2020.BMC health services research · 2026Article
- Distribution dynamics and spatial dependence in healthcare resource allocation efficiency: evidence of path dependence and club formation in China.Frontiers in public health · 2026Article
- Exploring spatial-temporal heterogeneity in new-type urbanization's impact on health expenditure: a GTWR analysis.International journal of health geographics · 2025Article
- Study on the spatial and temporal differences and influencing factors of out-of-pocket payments as a share of total health expenditure in China.BMC health services research · 2025Article
- Costs of Neurological Disorders.Neuroepidemiology · 2024Article
- Determinants of China's health expenditure growth: based on Baumol's cost disease theory.International journal for equity in health · 2021Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEven though China launched a series of measures to alleviate several financial burdens (including health insurance scheme, increased government investment, and so on), the economic burden of health expenditure has still not been alleviated. Out-of-pocket payments (OPPs) show not only a time correlation but also some degree of spatial correlation. The aims of the current study were thus to identify the spatial cluster of OPPs, to investigate the main factors affecting variation, and to explore the spatial spillover sources of China's OPP.
methodsGlobal and local spatial autocorrelation tests were validated to identify the spatial cluster of OPPs using the panel data of 31 provinces in China from 2005 to 2016. The Spatial Durbin Model, established in this paper, measured the spatial spillover effect of OPPs and analyzed the possible spillover sources (demand, supply, and socio-economic factors.
resultsOPPs were found to have a significant and positive spatial correlation. The results of the Spatial Durbin Model showed the direct and indirect effects of demand, supply, and socio- economic factors on China's OPPs. Among the demand factors, the direct and indirect correlation (elasticity) coefficients were positive. Among the supply factors, the direct and indirect effects of the share of primary health beds on residents' OPPs were negative. The ratio of health technicians in hospitals to those in primary health institutions on per capital OPPs had a significant indirect effect. Among the socio-economic factors, the direct effects of GDP, government health expenditure, and urbanization on OPPs were found to be positive. There were no significant indirect effects of socio-economic factors on OPPs.
conclusionThis paper finds that China's OPPs are not randomly distributed but, overall, present a positive spatial cluster, even though a series of measures have been launched to promote health equity. Socio-economic factors and those associated with demand were found to be the main influences of variation in OPPs, while demand was seen to be the driver of the positive spatial spillover of OPPs, whereby effective supply could inhibit these positive spillover effects.
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