The efficiency of residency training and health outcomes in China: Based on two-stage DEA and cluster analysis

Abstract

To address the residency training performance and further explore its determinants, with the help of a unique dataset, our study calculated the efficiency of residency training and health outcomes in 18 Chinese tertiary hospitals from 2020 to 2021 using a two-stage data envelopment analysis (DEA) model given the two-stage characteristics of vocational training and clinical practice of residents. The results showed that the efficiency of the sample hospitals in both residency training and medical service provision was high, there are approximately 1/3 hospitals of sub-efficient in each stage, but the number of efficient units for assessing the residency training performance was slightly less than that for assessing the health outcome performance. All the decision-making units (DMUs) were clustered into four groups through K-means cluster analysis according to efficiency results. The results showed that there was an obvious inconsistency between the teaching goals and the health outcome goals of Chinese public hospitals. In some hospitals, the low residency pass rate resulted in the low efficiency in stage 1, while the redundant inputs in beds resulted in the low efficiency in stage 2. Residency training hospitals should strengthen their synergistic management in programs of residency training and health outcomes.