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

Abstract Background 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...

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Main Authors: Ruijie Zhang, Jinghua Li, Xiaochun Du, Tianjiao Ma, Li Zhang, Qian Zhang, Fang Xia
Format: Article
Language:English
Published: BMC 2019-08-01
Series:BMC Health Services Research
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12913-019-4451-0
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author Ruijie Zhang
Jinghua Li
Xiaochun Du
Tianjiao Ma
Li Zhang
Qian Zhang
Fang Xia
author_facet Ruijie Zhang
Jinghua Li
Xiaochun Du
Tianjiao Ma
Li Zhang
Qian Zhang
Fang Xia
author_sort Ruijie Zhang
collection DOAJ
description Abstract Background 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. Methods 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. Results 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. Conclusion 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.
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spelling doaj.art-c7c411a6136545cf903be80cd962fb372022-12-21T22:04:34ZengBMCBMC Health Services Research1472-69632019-08-0119111210.1186/s12913-019-4451-0What has driven the spatial spillover of China’s out-of-pocket payments?Ruijie Zhang0Jinghua Li1Xiaochun Du2Tianjiao Ma3Li Zhang4Qian Zhang5Fang Xia6School of Public Health, Jilin UniversitySchool of Public Health, Jilin UniversitySchool of Management, Changchun University of Chinese MedicineSchool of Public Health, Jilin UniversitySchool of Public Health, Jilin UniversitySchool of Public Health, Jilin UniversitySchool of Management, Changchun University of Chinese MedicineAbstract Background 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. Methods 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. Results 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. Conclusion 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.http://link.springer.com/article/10.1186/s12913-019-4451-0Out-of-pocket paymentsSpatial clusterSpatial Durbin modelSpatial spillover sources
spellingShingle Ruijie Zhang
Jinghua Li
Xiaochun Du
Tianjiao Ma
Li Zhang
Qian Zhang
Fang Xia
What has driven the spatial spillover of China’s out-of-pocket payments?
BMC Health Services Research
Out-of-pocket payments
Spatial cluster
Spatial Durbin model
Spatial spillover sources
title What has driven the spatial spillover of China’s out-of-pocket payments?
title_full What has driven the spatial spillover of China’s out-of-pocket payments?
title_fullStr What has driven the spatial spillover of China’s out-of-pocket payments?
title_full_unstemmed What has driven the spatial spillover of China’s out-of-pocket payments?
title_short What has driven the spatial spillover of China’s out-of-pocket payments?
title_sort what has driven the spatial spillover of china s out of pocket payments
topic Out-of-pocket payments
Spatial cluster
Spatial Durbin model
Spatial spillover sources
url http://link.springer.com/article/10.1186/s12913-019-4451-0
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