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Does the fairness of healthcare resource allocation affect utilization efficiency?-an empirical study based on
1School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China.
Objective:
This study aims to measure the fairness and efficiency of healthcare resource allocation in 31 provinces and cities in China from 2014-2019 and explore the relationship between the fairness and efficiency of healthcare resource allocation in China.
Methods:
The Theil index and data envelopment analysis are used to evaluate the fairness and efficiency of healthcare resource allocation in the studied provinces and cities from 2014-2019. The DEA method, including the BCC model for static efficiency analysis and the Malmquist index for dynamic efficiency analysis, provides a comprehensive assessment of healthcare resource allocation efficiency. The Tobit model is employed to analyze the influencing factors.
Results:
The measurement results of fairness indicate that regional disparities are the main factor contributing to the unfairness of healthcare resource allocation in China. Among them, the regional differences in total assets are more pronounced. The results also show that the overall efficiency of healthcare resource allocation has improved during the period of 2014-2019, and low technological level is a major factor affecting the efficiency. Furthermore, considering the dimensions of regional development level, total healthcare resource quantity, and fairness in resource allocation, the study reveals that population density, urbanization rate, number of beds, total assets, fairness in the allocation of healthcare technical personnel, and fairness in the allocation of total assets significantly impact the efficiency of healthcare resource allocation in China.
Conclusion:
The fairness of healthcare resource allocation does have certain impacts on the utilization efficiency of healthcare services. The most important finding is that the fairness in the allocation of healthcare technical personnel has the highest positive impact on the efficiency of healthcare resource allocation. Additionally, the fairness in the allocation of total healthcare assets may decrease its utilization efficiency to some extent. Based on these findings, corresponding improvement strategies and recommendations for optimizing healthcare resource allocation are proposed.
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