Equity and efficiency of public hospitals’ health resource allocation in Guangdong Province, China

Abstract

Background To better meet people’s growing demand for medical and health services, 21 cities in Guangdong Province were involved in the reform of public hospitals in 2017. This paper evaluates the equity and efficiency of public hospitals’ health resource allocation in Guangdong Province and explores ways to change the current situation. Methods Data were collected from the Guangdong Health Statistical Yearbook 2016–2020 and Guangdong Statistical Yearbook 2017–2021. The Gini coefficient (G), Theil index (T), and health resource density index (HRDI) were used to measure the equity of health resource allocation. An improved three-stage DEA method was applied in efficiency evaluation. The entropy weight method was employed to calculate the weight of different indicators to obtain a comprehensive indicator representing the overall volume of health resources in each city. A two-dimensional matrix was drawn between the HRDI of the comprehensive indicator and efficiency and the per capita government financial subsidies and efficiency to observe the coordination of equity and efficiency across regions. Results From 2016 to 2020, the G of public hospital, bed, and health technician allocation by population remained below 0.2, while that by geographical area ranged from 0.4 to 0.6; the G of government financial subsidies by population was above 0.4, while that by geographical area was greater than 0.7. The results for T showed that inequality mainly comes from intraregional differences, and the Pearl River Delta contributes most to the overall differences. Although the HRDI of the Pearl River Delta is far greater than that of other regions, obvious differences exist across cities in the region. Only 38.1% of cities were found to be efficient in 2020. The Pearl River Delta was in the first quadrant, and the other three regions were in the third quadrant, accounting for a large proportion. Conclusion The equity of government financial subsidies allocation was the worst, and there were distinct regional differences in the geographical distribution of health resources. The development of healthcare within the Pearl River Delta was highly unbalanced. The development of healthcare was uneven between the Pearl River Delta, eastern, western, and mountainous regions. In addition, most cities in the eastern, western, and mountainous regions bore the dual pressures of relatively insufficient health resources and inefficiency.

Equity and efficiency of public maternal and child health institution’ health resource allocation in Henan Province, China

“…The results of e ciency and productivity show that the allocation e ciency of MCH resources in Henan Province is not high. The average TE for MCH institutions for 2016-2020 was 0.827, lower than studies in South Korea (0.886), Palestine (0.853) 37 , and other Chinese Provinces, including Guangdong (0.891) 9 , Jiangsu (0.920) 8 , Taiwan (0.973) 38 , and Wuhan (0.899) 39 , but still higher than Oman (0.692), Serbia (0.782) 40 , Turkey (0.724) 41 , Saudi Arabia (0.760) 42 , and Jordan (0.547). In 2016-2020, no more than half of the cities in Henan Province are DEA e cient each year, indicating that health resources in most cities are not being fully utilized.…”

Efficiency and equity of hospital services in mainland China: based on data from 2017 to 2021

“…Compared with the West, the Central has not bene ted from preferential regional policies, making it the most vulnerable region. Meanwhile, the western region has a limited level of technology, but relatively appropriate and fully utilized inputs [56][57].…”

Bed Management Strategies in Hospital during the COVID-19 Pandemic

“…A systematic literature review showed that among approximately 218 indicators used in hospital performance evaluations, the average LoS and BOR are the most frequently used [12]. Currently, there are several indicators available that can objectively re ect the allocation and utilization of bed resources, including average LoS, bed turnover times, and occupancy rate [13,14]. In this study, bed-related and economic indicators, including the BOR, bed turnover time, LoS, waiting time, and total patient hospitalization cost, were used for statistical analysis.…”