Abstract
BACKGROUND: To analyze the regional disparities, dynamic evolution, and influencing factors of medical resource allocation efficiency in TCM hospitals across China from 2016 to 2022, providing references for optimizing resource allocation in TCM hospitals. METHODS: The study employed a super-efficiency Slack-Based Measure (SBM) model considering undesirable outputs to assess regional equity in efficiency, utilized the Dagum Gini coefficient to measure regional disparities in efficiency, and applied kernel density estimation and spatial econometric models to analyze the dynamic evolution and spatial spillover effects of medical resource allocation efficiency in TCM hospitals. RESULTS: In 17 provinces, the efficiency is higher than the average value of 0.839, and in 8 provinces, the average value has exceeded 1. The regional pattern of efficiency shows a gradient characteristic of "high in the east and stable in the west, with the Northeast lagging behind." There is a significant spatial difference in the efficiency of resource allocation. The overall difference in the allocation of resources for traditional Chinese medicine (TCM) hospitals shows a fluctuating upward trend. The contribution rate of regional differences reaches 53.45%, which is the dominant factor. The largest regional differences are found within the central region, while the gaps between the eastern and central regions continue to widen, and those between the western and northeastern regions tend to become more balanced. The most significant interregional differences are observed between the central and western regions. The efficiency of resource allocation for TCM hospitals is on the rise, with the kernel density curve shifting to the right. The main peak height first decreases and then increases, while the width first expands and then contracts. The absolute difference first increases and then decreases. The rightward convergence of the tail indicates that there are efficient hospitals, but the gaps are narrowing. The multi-peak distribution reveals a multi-level differentiation pattern with the coexistence of low-efficiency and high-efficiency clusters. Per capita GDP, urbanization level, aging rate, population density, and the number of graduates from higher medical colleges can promote efficiency improvement. Population density and the proportion of TCM physicians have a positive spatial spillover effect on efficiency, while per capita GDP has a negative spatial spillover effect. CONCLUSION: The efficiency of medical resource allocation in traditional Chinese medicine (TCM) hospitals is steadily improving, and the regional differences are continuously narrowing. The degree of efficiency multi-polarization is becoming more moderate, and the development of regional equilibrium is being achieved. Both internal and external environmental factors jointly influence the improvement of medical resource allocation efficiency in TCM hospitals. It is recommended to take measures such as technological empowerment, institutional constraints, financial support, and talent absorption to enhance the efficiency of medical resource allocation in TCM hospitals and bridge the regional gaps.