Background Traditional Chinese medicine (TCM) hospitals are vital to China's healthcare system, yet concerns persist about the efficiency and equity of resource allocation. Variations in economic development across cities within a province lead to disparities in allocation efficiency, with many TCM hospitals facing challenges like low technical efficiency and uneven resource distribution. These issues hinder quality healthcare delivery and compromise fairness. Methods Using health statistics data (2018–2024) from China's Gansu Provincial Bureau of Statistics, this study employed a three-stage Data Envelopment Analysis (DEA) model, the Malmquist index, and Health Resources Agglomeration Degree (HRAD) to evaluate the efficiency and equity of TCM hospital resource allocation across 14 cities in the province. Results In 2024, the comprehensive technical efficiency of healthcare services at Gansu Provincial TCM Hospital was 0.961, with 10 regions being DEA-effective, 1 showing weak effectiveness, and 3 deemed ineffective. After adjusting environmental variables and random disturbances in the third-stage analysis, the recalculated efficiency metric stands at 0.962, showing minimal variation. This indicates that environmental factors exert a negligible influence on efficiency. From 2018 to 2024, total factor productivity declined annually, indicating significant room for efficiency improvement. Resource allocation equity varied widely across regions, with notable disparities in both geographical concentration and population-based distribution observed during the study period. Conclusions The efficiency and equity of resource allocation of TCM hospitals require substantial improvement. Insufficient resources limit hospital performance, and while technical efficiency surpasses allocation efficiency, overall technical standards remain inadequate. Geographic inequities in resource distribution are particularly pronounced. To address these challenges, establishing a provincial resource allocation mechanism, enhancing infrastructure in low-efficiency areas, and coordinating resource distribution across economically diverse cities are essential to optimize both efficiency and fairness.
Ba et al. (2025) studied this question.