What has driven the spatial spillover of China's out-of-pocket payments?

• Published in: BMC health services research Vol. 19; no. 1; p. 610
• Main Authors: Zhang, Ruijie, Li, Jinghua, Du, Xiaochun, Ma, Tianjiao, Zhang, Li, Zhang, Qian, Xia, Fang
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 30.08.2019; BioMed Central; BMC
• Subjects: Analysis; China; Control; Gross domestic product; Health care costs; Health Equity - economics; Health Equity - statistics & numerical data; Health Expenditures - statistics & numerical data; Health insurance; Hospitals; Humans; Insurance; Insurance, Health - economics; Insurance, Health - statistics & numerical data; Investments; Medical care utilization; Medical economics; Medical personnel; Out-of-pocket payments; Public enterprises; Public expenditures; Spatial cluster; Spatial Durbin model; Spatial spillover sources; Spatio-Temporal Analysis; Urbanization; China; Spatial spillover sources; Spatial Durbin model; Out-of-pocket payments; Spatial cluster
• ISSN: 1472-6963; 1472-6963
• DOI: 10.1186/s12913-019-4451-0

Even 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. Global 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. OPPs 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. This 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.