Background: Facing the problems of unreasonable allocation of medical resources and health inequity, the layout of elite hospitals in China deserves further attention. This paper explores the unbalanced allocation of high-quality resources and its influencing factors in the development of China's health system , so as to provide reference for the rational distribution of high-quality medical resources in China and other countries, from the perspective of space.
Methods: This study investigated 706 elite hospitals in 31 provinces, cities and autonomous regions in 2017. In this paper, geographic weighted regression (GWR), spatial lag model and spatial error model are used to study the influencing factors and spatial heterogeneity of spatial pattern.
Results: Spatial auto-correlation of elite hospitals in China is of great significance and the results of OLS regression showed that city level, number of medical schools, urban population and resident population were its significant variables. Further, its spatial agglomeration phenomenon were confirmed through SEM and SLM model. Among them, the city level is the most important factor affecting the spatial distribution of elite hospitals in China. The influence intensity of urban level gradually weakened from northeast to southwest. And medical colleges, whose degree of influence is gradually increasing from northeast to southwest, is the second influence factor. There is a weak relationship between the distribution of elite hospitals and population size,which indicates other factors' important impact.
Conclusion: China's elite hospitals are unevenly distributed and have obvious spatial heterogeneity. Therefore, we suggest that we should pay attention to the spatial governance of high-quality medical resources, attract medical elites in the region, increase investment in medical education in the scarce areas of elite hospitals and develop tele-medicine service. Through these means, we can solve the problem of unbalanced spatial distribution of medical resources and the demand of areas lacking high-quality medical resources.