To measure China’s medical resources mismatch index, to analyze the differences in the spatial distribution of medical resources mismatch, and to clarify the specific path to improve the mismatch of medical resources.

Based on the 2009-2021 data, China’s medical capital and labor mismatch indices were measured, the spatial and temporal evolution characteristics and sources of differences were analyzed using Dagum’s Gini coefficient and its decomposition method, and the fsQCA method was used to analyze the conditional groupings of high or low medical resource mismatches.

There were different degrees of capital mismatch or labor mismatch in each region. The overall Gini coefficient showed an "inverted V" evolution trend, the overall Gini coefficient within the region showed a fluctuating downward trend, and the overall Gini coefficient between regions was more complicated. Inter-region differences were the most important factor in the differences in the spatial allocation of medical resources. There were two types of pathways that lead to a high medical resource mismatch, i.e., labor-labor mismatch index and labor-labor mismatch index. There were 2 types of paths, i.e., labor force-hospital structure dual-driven (H1) and service level auxiliary-driven (H2), and 2 types of paths leading to low medical resource mismatch, i.e., urbanization-hospital structure-service level linkage-restricted (L1, L2) and internal and external linkage-restricted (L3, L4).

It’s supposed to play themacro-controlrole for the government to promote the rational allocation of regional medical resources, take the medical association as an important hand to play the leading role of tertiary hospitals, and fully implement the development strategy of new type of urbanization and lower the threshold of population settlement.