RESUMO
Objective:To analyze the operation efficiency of hospitals in 31 provinces in China from 2009 to 2019 based on the three-stage data envelopmeni analysis(DEA) model, for references to improve the operation efficiency of hospitals in China and promote the high-quality development of public hospitals.Methods:The data came from such sources as China health statistics yearbook and China general hospital ranking list of Fudan university.The number of hospitals, health technicians and beds in 31 provinces of China from 2009 to 2019 were used as input indicators, while that of hospital patients, discharged patients, hospitalized patients, reputational scoring of superior specialties and academic scoring of scientific research were used as output indicators.Government health expenditure, per capita GDP, population density and the proportion of tertiary hospitals were used as environmental variables.The three-stage DEA model was used to calculate the hospital operation efficiency and scale reward.Results:The environmental variables affected the operation efficiency of hospitals in China( P<0.05). After removing the impact, the average of comprehensive efficiency, pure technical efficiency and scale efficiency of hospitals in 31 provinces from 2009 to 2019 were 0.703, 0.961 and 0.726, respectively.Among them, the scale benefit of hospitals in 4 provinces remained unchanged, while those in 26 provinces increased progressively and 1 province decreased progressively. Conclusions:Pure technical efficiency could be the main factor to improve the operation efficiency of hospitals in China, while the low scale efficiency will affect the improvement of the operation efficiency of hospitals.The scale efficiency of hospitals in most provinces had great room for improvement.In order to improve the overall hospital operation efficiency in China, the authors suggested to expand hospital scale based on the precondition of quality, promote balanced distribution of high-quality medical resources, and play the positive role of the social, economic and environment variables.