Abstract
We measured the health resource agglomeration capacities of 31 Chinese provinces (or municipalities) in 2004–2018 based on the entropy weight method. Using a modified spatial gravity model, we constructed and analyzed the spatial correlation network of these health resource agglomeration capacities and their influencing factors through social network analysis. We found that: (i) China’s health resource agglomeration capacity had a gradual strengthening trend, with capacity weakening from east to west (strongest in the eastern region, second strongest in the central region, and weakest in the western region). (ii) The spatial network of such capacities became more densely connected, and the network density and level (efficiency) showed an upward (downward) trend. (iii) In terms of centrality, the high-ranking provinces (or municipalities) were Beijing, Shanghai, Jiangsu, Zhejiang, Guangdong, Shandong, Hunan, Hubei, Fujian, Anhui, Jiangxi, and Tianjin, while the low-ranking were Tibet, Qinghai, Gansu, Ningxia, Inner Mongolia, Heilongjiang, Yunnan, Guizhou, Xinjiang, Hainan, Shaanxi, and Shanxi. (iv) Block 1 (eight provinces or municipalities), including Beijing, Tianjin, and Hebei, had a “net spillover” effect in the spatial network of health resource agglomeration capacities; Block 2, (seven provinces or municipalities), including Shanghai, Jiangsu, and Zhejiang, had a “bidirectional spillover” effect in the spatial network; Block 3 (seven provinces or municipalities), including Anhui, Hubei, and Hunan, had a “mediator” effect in the network; and Block 4, (nine provinces or municipalities), including Sichuan, Guizhou, and Tibet, had a “net beneficial” effect in the network. (v) The economic development, urbanization wage, and financial health expenditure levels, and population size had significant positive correlations with the spatial network of health resource agglomeration capacities. Policy recommendations to enhance the radiating role of health resources in core provinces (or municipalities), rationally allocate health resources, and transform ideas to support public health resource services were provided.
Highlights
In early 2020, the coronavirus disease 2019 (COVID-19) broke out in China
They are both significant at the 1% level, indicating that the level of economic development and urbanization of each province have a facilitating effect on the development of the spatial correlation network of health resource agglomeration capacities
The correlation coefficients of R with Pop, Wag, and expenditure on the health industry (Exp) are 0.2705, 0.1905, and 0.2265, respectively. They are all significant at the 5% level, indicating that the population size, wage level, and financial health expenditure level of each province are positively correlated with the increase in the spatial correlations of health resource agglomeration capacities
Summary
In early 2020, the coronavirus disease 2019 (COVID-19) broke out in China. As of September. Health resource agglomeration capacity refers to the ability of a region to attract various health resources from surrounding regions (even the whole country) to concentrate in the region, thereby creating value-added and spillover effects It mainly includes human, material, and financial resources related to health, and is mainly measured using indicators, such as the number of medical and health institutions, hospital beds, and certified physicians. The Severe Acute Respiratory Syndrome (SARS) outbreak in 2003 prompted the rethinking of a nationwide construction of public health systems Factors, such as imbalances in regional economic development, differences between central and local fiscal investments, income disparities, and regional segmentation of health resources, have led to large differences in the health resource agglomeration capacities of different regions [1]. This study helps deepen the understanding of the spatial correlations among health resource agglomeration capacities in China and provides reference for further implementation of the medical system reform and the rational allocation and utilization of health resources
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