Abstract
This paper estimated and evaluated the spatial–temporal evolution of the concentration of healthcare resources (HCRs), in 31 provinces in China between 2004 and 2017, by using the entropy method. The spatial Durbin model (SDM) was used to further analyze the mechanisms behind the spatial driving forces at the national and regional levels. The findings revealed that: (i) The concentration of HCRs differed significantly among eastern, central, and western regions. The eastern, followed by the central region, had the highest concentration. Going east to west, the concentration of HCRs in the first echelon decreased, while it increased in the second and third echelons; (ii) places with higher concentrations clustered, while those with lower concentrations agglomerated; and (iii) economic development, population size, and urbanization promoted concentration. Education facilitated HCR concentration in the eastern and central regions, income stimulated HCR concentration in the eastern and western regions, and fiscal expenditure on healthcare promoted HCR concentration in the eastern region. Economic development inhibited HCR concentration in neighboring regions, population size restrained HCR concentration in neighboring areas in the western region, urbanization and income curbed HCR concentration in neighboring areas in the eastern and western regions, and fiscal expenditure on healthcare hindered HCR concentration in neighboring areas in the eastern region. Policy recommendations were proposed toward optimizing allocation of healthcare resources, increasing support for healthcare and education, and accelerating urbanization.
Highlights
According to the World Health Organization (WHO), everyone has the right to access basic healthcare services, in other words, healthcare accessibility is a universal right
It can be concluded that the gap in healthcare resources (HCRs) concentration between the eastern and central regions gradually reduced under the new healthcare reforms and the HCR concentration in the central region showed great potential for further improvement, while it did not change significantly in the western region. These findings could be attributed to factors such as underdeveloped economy, vast empty areas, and low population density in the western region, resulting in the weak targeting of state fiscal expenditure on healthcare, leading to inadequate infrastructure for medical and health institutions and low HCR concentration
There was a noticeable decreasing trend in spatial correlation coefficients from 2007 to 2009. Such a decline could be due to the fact that the years between 2007 and 2009 were the first three years of implementation of the new healthcare reforms, during which reforms were still undergoing an exploratory phase, and provinces were attempting to determine appropriate paths to achieve the national goal given the current situations of their own healthcare systems; the degree of correlation of HCR concentration between provinces declined
Summary
According to the World Health Organization (WHO), everyone has the right to access basic healthcare services, in other words, healthcare accessibility is a universal right. With the deepening of healthcare reforms, exploring HCR concentration and the mechanisms behind its spatial driving forces from a microscopic perspective has become a research interest. Scholars have introduced spatial analysis methods into healthcare research and achieved a range of results [19,20,21]; there are a few studies in the literature that used such methods to study the mutual influence of HCRs among provinces and cities. Domestic and foreign scholars have adopted spatial econometric models to quantitatively evaluate mechanisms behind the spatial driving forces of various observations Such an approach was rarely adopted in healthcare-related studies. This study employed the entropy weight method to measure the HCR concentration of 31 provinces in China from 2004 to 2017; a spatial weight adjacency matrix based on the obtained data was established and Moran’s I was used to examine spatial autocorrelation of the model; and the spatial Durbin model (SDM) was applied to analyze mechanisms behind the spatial driving forces of HCR concentration in China
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