A study on the efficiency and spatial correlation of health resource allocation in Chinese hospitals

BACKGROUND: This study quantitatively evaluated the efficiency of hospital healthcare resource allocation across 31 provinces in China from 2019 to 2023, with the aim of providing evidence-based decision support for improving resource utilization efficiency and promoting the sustainable development of medical institutions. METHODS: A three-stage Data Envelopment Analysis (DEA)-Malmquist model was employed to estimate both static and dynamic efficiency in hospital healthcare resource allocation. Spatial autocorrelation of efficiency was examined using Moran's I to identify regional spatial dependence patterns. RESULTS: The average comprehensive efficiency of healthcare resource allocation in Chinese hospitals was below 1, indicating substantial room for improvement in overall efficiency, though an overall upward trend was observed during the study period. After controlling for environmental factors, the mean comprehensive efficiency declined from 0.858 to 0.827, suggesting that external environmental conditions influenced actual efficiency to some extent. Dynamic analysis indicated that technical efficiency was the primary constraint on total factor productivity growth. In regional comparisons, after accounting for environmental factors, the efficiency ranking shifted from the original pattern of eastern > central > western to a temporary order of central > eastern > western. Spatial analysis indicated a significant positive spatial correlation in resource allocation efficiency. A stable high-efficiency cluster persisted in the region south of the Yangtze River, while low-efficiency clusters had largely dissipated by 2023, reflecting a convergence trend of provincial efficiency levels toward the efficiency frontier. CONCLUSIONS: Hospital efficiency in China exhibits a distinct east-to-west gradient. However, after adjusting for environmental heterogeneity, the central region temporarily outperformed the eastern region, highlighting the confounding effects of external factors. Robust spatial spillover effects were observed. Policy interventions should therefore prioritize targeted efficiency improvements in low-efficiency cold-spot provinces over mere input expansion. The bias-corrected efficiency scores and spatial clustering patterns provide a validated benchmark for national and regional health resource planning.