The Impact of Autonomy Reform on the Efficiency of Public Hospitals in China: A DEA-ITSA Combination Analysis.

Purpose: Since 2014, China has been rolling out a new autonomy reform for public hospitals, aiming to enhance their efficiency and better utilize the health budgets. The purpose of this research is to assess the reform's success and explore its effects on hospital outcome efficiency, laying a foundation based on empirical evidence for future policy decisions.

Methods: The data envelopment analysis(DEA) and interrupted time-series analysis (ITSA) approaches were combined to analyze the reform impacts on the 16 samples of Shenzhen municipal public hospitals in China, using data extracted from the Shenzhen Health Statistics Yearbook from 2002 to 2023.

Results: The results revealed that from 2002 to 2023, 15 out of 16 sample hospitals achieved total factor productivity improvement in Shenzhen city of China, with the average growth rate of Malmquist total factor productivity index(MI) was 3.05% and the highest growth rate was 6.93%, yet only one hospital showing a growth rate of -0.02%. The results of ITSA show a significant intervention in 2014. After the policy intervention, the fixed reference Malmquist total factor productivity index(FRMI) for the general and the specialty hospital group increased at rates of 0.04680(P<0.000) and 0.1746(p<0.000) per year by the Newey-West model, similarly, the rates of 0.04689(P<0.000) and 0.1762(p<0.000) per year by the Prais-Winsten model.

Conclusion: The reform has positively impacted public hospitals' total factor productivity(TFP). The TFP of the general hospitals was increasing before the policy intervention of autonomy hospitals, but the time of its implementation was associated with a more significant rise. Meanwhile, the TFP of specialty hospitals decreased before the intervention; however, its trend shifted to growth after the intervention. This research further emphasizes the applicability of the DEA-ITSA combination method as an effective tool for health policies evaluation using public data within China's healthcare framework.