The purpose of this article is to construct a nested matrix of "education economy" to study the spatial effects of Chinese nurses and further explore the influencing factors of the spatial distribution of Chinese nursing staff under the new healthcare reform. We use Monte Carlo simulation method to optimize and screen the nested matrix of "education economy". On this basis, we used Moran index, spatial Gini coefficient, and cold hot spot analysis method to analyze the spatial pattern of nurses in China. We construct a spatial Durbin model to analyze the main influencing factors and spatial spillover effects of nursing staff. The results indicate that the relative density area and relative average area of nursing staff in 31 provinces have significantly increased. The global Moran index has dropped from 0.523 in 2008 to 0.340. The distribution of personnel in hotspots spreads from economically developed areas to the central and western regions, with a significant contraction of cold spots. The level of provincial economic development (direct effect 0.493, indirect effect -1.519), unemployment rate (direct effect -0.118), education resource investment (direct effect 0.538, indirect effect 1.713), and per capita medical expenditure (direct effect 0.45 37) are the influencing factors on the spatial distribution of nursing staff. Therefore, it is more reasonable to use the nested matrix of "education economy" to study the spatial effects of Chinese nurses. After the new healthcare reform, the distribution of nursing staff in China has significantly improved. The health administrative department should pay attention to local economic development, reduce unemployment rate, increase investment in education resources, and reduce per capita medical expenses to ensure the healthy development of medical and health personnel.

Yang Yang, Chengcheng Li, Juanxia Zheng. An Effective Study on Spatiotemporal Differentiation of Chinese Nursing Staff: Spatial Durbin Model. Academic Journal of Medicine & Health Sciences (2023) Vol. 4, Issue 12: 1-9. https://doi.org/10.25236/AJMHS.2023.041201.

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