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Issue title: High-Performance Computing
Guest editors: Achyut Shankar
Article type: Research Article
Authors: Tang, Huia; b; c | Yan, Jiea | Pan, Denga | Chen, Yua; b; d; *
Affiliations: [a] College of Architecture and Urban Planning, Hunan City University, Yiyang, China | [b] Key Laboratory of Key Technologies of Digital Urban-Rural Spatial Planning of Hunan Province, Yiyang, China | [c] Key Laboratory of Urban Planning Information Technology of Hunan Province, Yiyang, China | [d] School of Architecture and Planning, Hunan University, Changsha, China
Correspondence: [*] Corresponding author: Yu Chen, School of Architecture and Planning, Hunan University, Changsha, 410000, China. E-mail: [email protected].
Abstract: This paper analyzes the healthcare level and the evolution of spatial and temporal pattern of each district and county in Changsha City by using the entropy value method based on the statistics of the number of healthcare facilities, beds, and health technicians in Changsha City from 2010 to 2018, and evaluates the fairness and trend of healthcare resource distribution in Changsha City over the years in terms of per capita level through the calculation of the Gini coefficient. The results show that the medical level in the southern part of Changsha City is better, the medical level in the northern part is weaker, there are significant differences in the healthcare level between districts and counties and the differences between districts and counties are decreasing year by year; there is a lack of fairness in the level of healthcare technicians in each district and counties in comparison with the level of the number of health care institutions and beds. In this regard, suggestions are made to improve the level of protection of health technical personnel, to equalize the distribution of the internal components of health care, and to improve the construction of the health care system and resource sharing.
Keywords: Health equality, medical health resource allocating, gini coefficient, Changsha City
DOI: 10.1177/18724981241295933
Journal: Intelligent Decision Technologies, vol. 18, no. 4, pp. 3395-3404, 2024
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