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Analysis of the Differentiation of Medical Resource Allocation and Its Influencing Factors

Quanlv Guo () and Xiuli Zhang ()
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Quanlv Guo: College of Mathematics and Statistics Chongqing Technology and Business University
Xiuli Zhang: College of Big Data Statistics Guizhou University of Finance and Economics

A chapter in Proceedings of 2024 4th International Conference on Public Management and Big Data Analysis (PMBDA 2024), 2025, pp 47-57 from Springer

Abstract: Abstract To allocate medical resources more reasonably and effectively, and to promote the sustainable development of health initiatives, this paper analyzes data on the number of medical and health institutions in China from 1990 to 2023. It explores the spatial and temporal differences in the allocation of medical resources through the analysis of Global and Local Moran’s I, as well as non-parametric KDE. Additionally, Random Forest Regression model is employed to identify the key factors influencing the number of medical and health institutions. The findings indicate that the national level of healthcare resource allocation has increased significantly and stabilized after 2010, with the greatest degree of differentiation observed among provinces in the central and western regions. Furthermore, Per capita disposable income and population mortality rate are identified as key factors affecting the number of medical and health institutions.

Keywords: Global Moran’s I; Local Moran’s I; Non-parametric KDE; Random Forest Regression (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-656-7_6

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DOI: 10.2991/978-94-6463-656-7_6

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