About: Study of influential factors of provincial health expenditure -analysis of panel data after the 2009 healthcare reform in China

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Study of influential factors of provincial health expenditure -analysis of panel data after the 2009 healthcare reform in China
Creator	Li, Jing Wang, Yue Zhang, Yun Hou, Jifei Liu, Yanzheng Tian, Liqi
Source	Medline; PMC
abstract	BACKGROUND: Total Healthcare Expenditure (THE) has increased substantially in all countries. Since the health system reform and health policy environment differ from each country, it is necessary to analyze the motivations of THE in a specific country. METHODS: The objective of this study was to analyze the influential factors of Provincial THE (PTHE) per capita in China by using spatiotemporal panel data across 31 provinces (including provinces, autonomous regions, and municipalities, all called provinces in here) from 2009 to 2016 at the provincial and annual level. Generalized Estimating Equation (GEE) was used to identify the influential factors of PTHE per capita. RESULTS: The number of beds per 10,000 population explained most of the variation of PTHE per capita. The results also showed that health expenditure in China reacts more to mortality compared with the Gross Domestic Product (GDP) per capita. But mortality and Out-Of-Pocket Payments (OOP) as a percentage of THE were associated with PTHE per capita negatively. The rate of infectious diseases and THE as a percentage of GDP had no statistical significance. And the Proportion of the Population Aged 65 and Over (POP65) impact PTHE per capita positively. But the coefficient was small. CONCLUSIONS: In response to these findings, we conclude that the impact of the increasing percentage of OOP in THE diminishes the PTHE. Furthermore, we find that both the “baseline” health level and health provision are positively correlated with PTHE, which outweighs the effect of GDP.
has issue date	2020-07-01(xsd:dateTime)
bibo:doi	10.1186/s12913-020-05474-1
bibo:pmid	32611335
has license	cc-by
sha1sum (hex)	85af921bac0d7daf1d70095d7f02f80c1b1e39b8
schema:url	https://doi.org/10.1186/s12913-020-05474-1
resource representing a document's title	Study of influential factors of provincial health expenditure -analysis of panel data after the 2009 healthcare reform in China
has PubMed Central identifier	PMC7327486
has PubMed identifier	32611335
schema:publication	BMC Health Serv Res
resource representing a document's body	covid:85af921bac0d7daf1d70095d7f02f80c1b1e39b8#body_text
is schema:about of	named entity 'Generalized' named entity 'motivations' named entity 'THE' named entity 'panel data' named entity 'TO IDENTIFY' named entity 'HEALTHCARE' named entity 'LEVEL' named entity 'HEALTHCARE REFORM' named entity 'capita' named entity 'GEE' named entity 'China' named entity 'Equation' named entity 'Expenditure' named entity 'annual' named entity 'health policy' named entity 'older people' named entity 'health expenditure' named entity 'mortality rates' named entity 'econometric models' named entity 'health services' named entity 'global outbreak' named entity 'health services' named entity 'GDP per capita' named entity 'current health' named entity 'China' named entity 'CPI' named entity 'CND' named entity 'demographic' named entity 'significant effect' named entity 'p-value' named entity 'long-term' named entity 'life expectancy' named entity 'starting time' named entity 'Future research' named entity 'primary care' named entity 'population aging' named entity 'sensitivity analysis' named entity 'SAARC' named entity 'inflation' named entity 'out-of-pocket' named entity 'population aging' named entity 'population aging' named entity 'negative correlation' named entity 'national health' named entity 'GDP' named entity 'preventive health' named entity 'economic growth' named entity 'fixed effects' named entity 'statistical significance' named entity 'response variable' named entity 'OOP' named entity 'positive relationship' named entity 'China' named entity 'GDP' named entity 'p-value' named entity 'time-invariant' named entity 'OOP' named entity 'OOP' named entity 'health outcomes' named entity 'GDP' named entity 'Dormont' named entity 'response variable' named entity 'GDP' named entity 'infectious disease' named entity 'empirical study' named entity 'GDP' named entity 'GDP per capita' named entity 'Chongqing' named entity 'European Union' named entity 'GDP' named entity 'statistical methods' named entity 'Population aging' named entity 'infectious diseases' named entity 'econometric methods' named entity 'Health Expenditure' named entity 'health costs'

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