ObjectiveTo compare and evaluate the discrimination, validity, and reliability of different data envelopment analysis (DEA) models for measuring the effectiveness of models by selecting different input and output indicators of the model.MethodsData from health statistical reports and pilot program of diagnosis-related groups of tertiary hospitals in Hubei Province from 2017 to 2018 were used to analyze the discrimination, content and structure validity, and reliability of the models. Six DEA models were established by enriching the details of input and output on the basis of the input and output indicators of the conventional DEA model of hospitals.ResultsFrom the view of discrimination, the results of all models were left-skewed, the cost-efficiency model had the lowest left-skewed degree (skewness coefficient: -0.14) and was the flattest (kurtosis coefficient: -1.02). From the view of structure validity, the results of the cost-efficiency model were positively correlated with total weights, outpatient visits, and inpatient visits (r=0.328, 0.329, 0.315; P<0.05). From the perspective of content validity, the interpretation of model was more consistent with theory of production after revision of input and output indicators. From the view of reliability, the cost efficiency model had the largest correlation coefficient between the data of 2017 and 2018 (r=0.880, P<0.05).ConclusionsAfter refining the input and output indicators of the DEA model, the discrimination, validity, and reliability of the model are higher, and the results are more reasonable. Using indicators such as discrimination, validity, and reliability can measure the effectiveness of the DEA model, and then optimize the model by selecting different input and output indicators.
ObjectiveTo investigate the distribution, service volume, and medical efficiency of private general hospitals in Sichuan Province to provide references for optimizing the allocation of health resources in Sichuan Province. MethodsUsing the 2020 data from private general hospitals above the second level in 18 cities and states in Sichuan Province, this study calculated the market concentration and competitiveness with the Herfindahl-Hirschman index (HHI). A three-stage data envelopment analysis (DEA) model was employed to eliminate environmental variables and random errors for hospital efficiency analysis. Influencing factors were conducted using a Tobit regression model. ResultsThe HHI indices for the number of licensed (assistant) physicians, beds, and total consultations in each city and state were below 1 000, indicating a low concentration market. The comprehensive technical efficiency, pure technical efficiency, and scale efficiency of private general hospitals above the second level in Sichuan Province were 0.534, 0.661, and 0.806, respectively, after the three-stage DEA analysis. The number of practicing (assistant) physicians was negatively correlated with scale efficiency. the number of beds was negatively correlated with pure technical efficiency. The total number of consultations showed a positive correlation with overall technical efficiency, pure technical efficiency, and scale efficiency. ConclusionThe provincial private hospital market exhibits low concentration competition. Differences in efficiency exist among various regions, grades, and hospital types. Market competition in resource allocation promotes the improvement of pure technological efficiency and scale efficiency. Market share competition hinders the improvement of comprehensive technical efficiency, pure technical efficiency, and scale efficiency.