目的 通过应用数据包络分析（DEA）方法对医院科室运营效率进行评价，分析DEA方法在医院临床科室相对效率评价中的价值。 方法 采用聚类分析等确定投入产出指标，采用DEA方法中C2R和BC2模型对2004年1月－2008年12月各科室相对效率进行评价和分析。 结果 70个被评价单元中有41个被评价单元的总体有效值为1，属于相对有效单元；29个被评价单元的C2R模型总体有效值＜1，属于相对无效单元。 结论 DEA方法适用临床科室相对效率评价多投入、多产出的特点，能够有效识别被评价单位中的无效单元，并且对于投入产出值能够指明导致无效的方向和需调整的程度，指导相关管理部门对科室的调整和资源投入方向。
ObjectiveTo measure the operational efficiency and explore the phenomenon of the economy of scale in secondary public general hospitals of China for improving the health service efficiency.MethodsFrom February to August 2019, the data set of two input indicators (the number of employees and actual open beds) and two output indicators (the numbers of outpatients and discharges) in 511 secondary general hospitals of Shandong, Anhui, Shanxi, Hubei and Hainan provinces in 2018 were collected for data envelopment analysis. The analysis processes were three folds: First, the technical efficiency, pure technical efficiency, scale efficiency and scale compensation status of the sample hospitals were calculated respectively. Second, the comparative analysis of efficiency value and scale compensation status was carried out in 5 groups according to the bed scale. Finally, the input and output projection analysis was carried out on the ineffective decision making units.ResultsThe medians of technical efficiencies, pure technical efficiencies, and scale efficiencies of the 511 secondary general hospitals were 0.472, 0.531, and 0.909, respectively. In the 511 hospitals, 493 hospitals (96.5%) were in ineffective state, of which 321 hospitals (62.8%) were in the state of decreasing return to scale. The staff redundancy of the group with beds >100 and ≤300 was 23.86%, and its service quantity could be increased by 39.37%.ConclusionsThe overall operating efficiencies are inefficiency in secondary general hospitals of China and the optimal scale of actual open beds is between 300 and 500 beds from the perspective of scale efficiency.
ObjectiveTo measure the total factor productivity and its component changes of public secondary general hospitals in China from 2012 to 2018.MethodsFrom February to September in 2019, stratified systematic sampling method was used to collect the panel data of input and output indicators from 2012 to 2018 of 511 public secondary general hospitals in 5 provinces of China (Shandong, Hubei, Hainan, Anhui, and Shanxi), and Bootstrap-Malmquist-data envelopment analysis was used to calculate the total factor productivity and its component changes of the hospitals.ResultsFrom 2012 to 2018, the total factor productivity of the 511 public secondary general hospitals decreased by 0.22%, technical efficiency decreased by 5.24%, technical changes increased by 5.29%, pure technical efficiency decreased by 1.40%, and scale efficiency decreased by 3.89%, respectively.ConclusionsIn the past 7 years, the total factor productivity of public secondary general hospitals in China has declined slightly, mainly due to the decline of scale efficiency and pure technical efficiency, and the technological progress is the main reason for its improvement. The implications for the public secondary general hospitals are three folds: avoiding blind expansion and exploring optimum scale of beds, strengthening the internal fine management to improve the management practice and technical efficiency, and promoting technological progress by healthcare cooperating organizations.
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.
Objective To explore the present situation of the efficiency about public tertiary general hospitals in Shandong province, measure and compare the efficiency and the state of returns to scale of hospitals under different bed scales. Methods Based on the input and output data of 137 public tertiary general hospitals in Shandong province in 2017, two input indicators (the number of employees and the number of actual beds) and two output indicators (the total number of outpatients and emergent patients, and the number of discharges) were selected. The technical efficiency, pure technical efficiency and scale efficiency of sample hospitals were calculated by using data envelopment analysis, and a comparative analysis was carried out under different bed scales. Results Of the 137 public tertiary general hospitals, the mean of technical efficiency value was 0.666, the medians of pure technical efficiency value and scale efficiency value in 2017 were 0.817 and 0.919, respectively. In the 137 sample hospitals, there were 132 hospitals (96.4%) in ineffective status; there were 90 hospitals (65.7%) exhibiting increasing returns to scale, 11 hospitals (8.0%) exhibiting constant returns to scale, and 36 hospitals (26.3%) exhibiting decreasing returns to scale. There were significant differences in hospital efficiency and returns to scale under different bed sizes (P<0.001), and the scale efficiency was the highest when the bed size was 1001-2000. Conclusions The overall operating efficiency of the public tertiary general hospitals in the province was not high yet. Most hospitals were in ineffective status and most of them were in the state of increasing returns to scale. The optimal scale of actual beds is between 1001 and 2000 beds from the perspective of scale efficiency.
Objective To establish a cooperative decision-making model of county-level public hospitals, so as to freely select the best partner in different decision-making units and promote the optimal allocation of medical resources. Methods The input and output data of 10 adjacent county-level public hospitals in Henan province from 2017 to 2019 was selected. Based on the traditional data envelopment analysis (DEA) model, a generalized fuzzy DEA cooperative decision-making model with better applicability to fuzzy indicators and optional decision-making units was constructed. By inputting index information such as total number of employees, number of beds, annual outpatient and emergency volume, number of discharged patients, total income and hospital grade evaluation, the cooperation efficiency intervals of different hospitals were calculated to scientifically select the best partner in different decision-making units.Results After substituting the data of 10 county-level public hospitals in H1-H10 into the model, taking H2 hospital as an example to make cooperative decision, among the four hospitals in H1, H2, H7 and H10 of the same scale, under optimistic circumstances, the best partner of H2 hospital was H7 hospital, and the cooperation efficiency value was 1.97; in a pessimistic situation, the best partner of H2 hospital was H10 hospital, and the cooperation efficiency value was 0.98. The model had good applicability in the cooperative decision-making of county-level public hospitals. Conclusion The generalized fuzzy DEA model can better evaluate the cooperative decision-making analysis between county-level public hospitals.