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

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 t...

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Autores principales: Zhang, Ruijie, Li, Jinghua, Du, Xiaochun, Ma, Tianjiao, Zhang, Li, Zhang, Qian, Xia, Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6716932/
https://www.ncbi.nlm.nih.gov/pubmed/31470846
http://dx.doi.org/10.1186/s12913-019-4451-0
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author Zhang, Ruijie
Li, Jinghua
Du, Xiaochun
Ma, Tianjiao
Zhang, Li
Zhang, Qian
Xia, Fang
author_facet Zhang, Ruijie
Li, Jinghua
Du, Xiaochun
Ma, Tianjiao
Zhang, Li
Zhang, Qian
Xia, Fang
author_sort Zhang, Ruijie
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12913-019-4451-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-67169322019-09-04 What has driven the spatial spillover of China’s out-of-pocket payments? Zhang, Ruijie Li, Jinghua Du, Xiaochun Ma, Tianjiao Zhang, Li Zhang, Qian Xia, Fang BMC Health Serv Res Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12913-019-4451-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-08-30 /pmc/articles/PMC6716932/ /pubmed/31470846 http://dx.doi.org/10.1186/s12913-019-4451-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zhang, Ruijie
Li, Jinghua
Du, Xiaochun
Ma, Tianjiao
Zhang, Li
Zhang, Qian
Xia, Fang
What has driven the spatial spillover of China’s out-of-pocket payments?
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 Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6716932/
https://www.ncbi.nlm.nih.gov/pubmed/31470846
http://dx.doi.org/10.1186/s12913-019-4451-0
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