Equity analysis of Chinese physician allocation based on Gini coefficient and Theil index

Abstract

Background Unequal allocation of medical physician resource represents one of major problems in the current medical service management in China and many other countries. This study is designed to analyze the current distribution of physicians in 31 provincial administrative regions in China, to estimate the fairness of the distribution of physicians and provide a theoretical basis for the improvement of the allocation of physicians. Methods This study took physicians from 31 provincial administrative regions in China as the study objects, and the data were obtained from the China Health Statistics Yearbook 2019 and the official website of the National Bureau of Statistics of China. Calculation of the Gini coefficient (G) and the Theil index (T) were carried out by drawing the Lorenz curve. The fairness of present physician location in 31 provincial administrative regions in China was analyzed from the perspective of distribution by both population and service area. Results The Gini coefficients of medical physicians in China are 0.003 and 0.88 by population and by service area, respectively. This shows that the distribution of medical physicians is fair basing on population, and there is little difference in the number of physicians per 1000 population in different regions. However, the physician distribution basing on service area is highly unfair and shows a large gap in the number of physicians per square kilometer between different regions. In general, Beijing, Zhejiang, Shanghai, Jiangsu, Shandong, and Tianjin are higher than the overall level of 31 provincial administrative regions. In addition, the number of medical physicians in Zhejiang, Shandong, Beijing and Jiangsu is over-provisioned. Conclusion Bridging the number of medical physicians in different regions is a key step to improve the equity of physicians’ resource allocation. Thus, findings from this study emphasize the need to take more measures to reduce physician quality differences between regions, balance and coordinate medical resources. This will increase the access of all citizens to quality medical services.

Second victim experience and support desire among nurses working at regional levels in China

“…In China, inequity remains between provincial and regional regions regarding the allocation/usability/accessibility of health resources (Yi et al, 2020;Yu et al, 2021). For example, although urban areas have high quality/quantity of health care workers, remote rural areas tend to be understaffed (Wu & Yang, 2019).…”

Regional Economic Differences and Coordinated Development Based on Panel Data Model

“…Various studies have been conducted wherein the Theil and Gini indices have been used to perform economic analysis. As an example, the study in [32] analyzed the present distribution of physicians in 31 administrative regions of China wherein the Theil and Gini indices were used [32,33].…”

“…The formula used to measure the absolute error of the regional economy is a standard deviation index [32,33].…”

“…The Theil index can decompose the regional differences into two parts: intragroup differences and intergroup differences, which can clearly see the contribution of intragroup differences and intergroup differences to the overall differences. Therefore, in this paper, we choose the Theil index decomposition method to study the differences between several prefecture-level cities in Jiangxi Province and the differences within each of them, and we can obtain the Theil index from the concept of entropy in information theory, which is calculated as follows [32,33].…”

Temporal and Spatial Differentiation of Cultivated Land and Its Response to Climatic Factors in Complex Geomorphic Areas—A Case Study of Sichuan Province of China

“…Since 37 geomorphic areas are defined in the study area, the value range of the integer i is 0 < i < 37. The smaller the Gini coefficient, the more evenly distributed the cultivated land in various geomorphic areas; conversely, the more unevenly distributed is the cultivated land [24].…”