The efficiency evaluation of traditional Chinese medicine hospitals by data envelopment analysis in Zhengzhou, China - Wang, Jingjing; Lv, Hui; Jiang, Hui; Ren, Wenjie (Frontiers in Public Health, 2024)
Aim This study aimed to evaluate the operational efficiency of traditional Chinese medicine (TCM) hospitals in China. Methods Pearson’s analysis was used to test the correlation between the input and output variables. Data envelopment analysis (DEA) was utilized to analyze the input and output variables of 16 TCM hospitals, and each hospital efficiency score was computed by Deap 2.1, assuming variable return to scale (VRS), which is an input-oriented model. t tests were conducted to confirm the significant difference of efficiency scores at the hospital level and by hospital type, and ANOVA was used to test for significant differences in efficiency scores according to hospitals’ size. Results The correlation coefficient of the input and output indicators was between 0.613 and 0.956 (p < 0.05). The difference in number of doctors (ND) and numbers of pharmacists (NP) were statistically significant (p < 0.05) at the hospital level. The mean efficiency scores for technical efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) in secondary TCM hospitals were 0.766, 0.919, and 0.838, respectively. Additionally, the lowest TE, PTE, and SE were 0.380, 0.426, and 0.380, respectively. Eight TCM hospitals in this study were DEA efficient, with an efficiency score of 1. There were no statistically significant differences in TE, PTE, and SE among hospital levels, hospital types or hospital sizes groups (p > 0.05). Conclusion This study revealed that tertiary TCM hospitals had a greater level of efficiency than secondary TCM hospitals. In our study, 50% of TCM hospitals had inefficient management. Therefore, to activate the new development power of TCM hospitals, it is necessary to reform and improve the management system and mechanism of TCM hospitals, optimize the development environment of TCM hospitals and formulate development plans and measures based on local conditions.