Abstract
BACKGROUND: Against the backdrop of the coordinated advancement of the “Healthy China” and “Digital China” initiatives, enhancing the utilization efficiency of healthcare resources has become a core issue in achieving universal health coverage. Currently, provinces across China face significant challenges in allocating medical resources. Conducting in-depth research into the current state of resource utilization efficiency and its underlying mechanisms holds critical practical significance for optimizing resource allocation and driving high-quality development of the healthcare system. METHODS: This study employs a data envelopment analysis model to measure the efficiency of healthcare resource utilization at the provincial level in China. Utilizing a fuzzy set qualitative comparative analysis method, it systematically examines the synergistic effects of different antecedent conditions to reveal the diverse pathways driving high resource utilization efficiency. RESULTS: Data analysis reveals a complex picture of healthcare resource utilization efficiency in China: (1) In 2021, China’s average comprehensive healthcare resource utilization efficiency stood at 0.918. However, only 35.5% of provinces achieved DEA efficiency, indicating that nearly two-thirds of provinces still face resource misallocation issues. (2) Among these, 14 provinces exhibited increasing returns to scale (under-investment in resources), while 6 provinces showed decreasing returns to scale (over-investment in resources), reflecting structural imbalances between resource allocation and actual demand. (3) fsQCA configuration analysis identified five efficient driving pathways: H1(Digital-Economic-Spatial Constraint Type) reflects cumulative disadvantages across multiple dimensions; H2 (Economy-Digital Synergy) and H4 (Urbanization-Driven) demonstrate how different factor combinations achieve functional equivalence through divergent pathways; H3 (Comprehensive Factor Balance) and H5 (Full Factor Empowerment) collectively outline the evolutionary path from “factor-driven” to “innovation-driven” development. CONCLUSION: Achieving high-level efficiency in healthcare resource utilization does not rely on a single optimization approach, but rather results from the coordinated allocation of economic capital, digital technology, and spatial structures. Research reveals the existence of a “multiple concurrent” equivalent driving model, offering diverse pathways for regions with varying developmental conditions. Policy formulation should abandon a one-size-fits-all approach and instead adopt differentiated strategies aligned with local resource endowments and developmental stages. This systematic thinking will drive comprehensive improvements in healthcare resource utilization efficiency. CLINICAL TRIAL NUMBER: Not applicable.