| Objective: The study used a three-stage DEA model to calculate the efficiency of China's 2003-2017 annual health efficiency and the regional health efficiency of 31 provinces and cities in 2013-2015.Evaluate and analyze the dynamic changes of time and space in China's health efficiency.Taking per capita health expenditure as input index,perinatal survival rate,maternal survival rate and life expectancy as output indicators,two three-stage DEA models were constructed under different index combinations to study the dynamic development and regional development of health input and output in China.difference.The specific objectives are:(1)Summarize the operation mechanism of common model for efficiency measurement,introduce the advantages and limitations of single model for health efficiency measurement,and explore the advantages of efficiency measurement under combined model.(2)Construct a three-stage model,construct a three-stage DEA model with different index combinations from time series and provincial space.(3)Use SFA model to control environmental variables,eliminate management efficiency and random interference factors.To explore the changes in health efficiency after the model is improved;(4)to provide targeted policy recommendations for the input and utilization of health resources according to the dynamic changes of time and space in China's health efficiency.Content: Firstly,the index system of the three-stage DEA is constructed.The per capita health expenditure is taken as the input index,the perinatal mortality,maternal mortality and life expectancy are used as the original output indicators,and multiple models under different indicator combinations are constructed.The health efficiency of China is measured from the perspective of time series and provincial space.The calculation results include technical efficiency values,pure technical efficiency values,scale efficiency values,and slack variables of inputs in various provinces and cities in China in 2003-2017 and 2013-2017.The next step is to use the input slack variable in the first stage as the explanatory variable,the environmental factor,the random factor and the management efficiency as the regression model constructed by the explanatory variable for SFA analysis.Therefore,the efficiency error caused bythe elimination management inefficiency and random interference is calculated,and the adjusted input is calculated.Finally,the health efficiency is re-measured with adjusted input,and the efficiency before and after the adjustment is compared and analyzed.The advantages of the three-stage DEA are empirically tested to provide a model basis for real efficiency measurement.Methods:(1)Adopt the VRS&CRS model in the input-oriented DEA model.According to the particularity of the output indicators of healthy production efficiency,the health output indicators are selected to analyze the technical efficiency,pure technical efficiency,scale efficiency,and input slack variables.(2)The SFA model performs regression analysis on the input variable slack value measured by the DEA model and the environmental variables that cannot be determined by the decision unit,and then separates the management inefficiency from the random interference factor.(3)Standardization of data,certain processing of the original variables,in addition to the impact of different indicators on different attributes,making the results more comparable.(4)According to the dynamic changes of time and space of China's health efficiency,provide targeted policy recommendations for the input and utilization of health resources.Results: The results of the first-stage DEA calculation: In the first-stage DEA time series analysis,the health efficiency calculations of China's Model 1 and Model2 are both inefficient,and the technical efficiency,pure technical efficiency and scale efficiency are decreasing year by year.Inefficiency in technical efficiency is mainly caused by ineffective scale.Mainly due to the inefficiency of scale,the proportion of output growth is much lower than the proportion of input growth.The province with the highest overall comprehensive health efficiency in provincial efficiency is Guizhou,with an average technical efficiency of 0.987;the lowest province is Beijing,and the average technical efficiency is only 0.250.The average annual health expenditure in Beijing has to be reduced by 6012.37 yuan,far exceeding other provinces and cities.Guizhou,Jiangxi,and Guangxi provinces have lower improvement values,and the five-year per capita health expenditure investment improvement is less than 100 yuan.Two-stage SFA regression analysis unilateral likelihood ratio test(LR)passed the significance test,In the time series analysis,thecorrelation coefficient between per capita GDP,household consumption level,illiteracy rate and total dependency ratio is positive,and the correlation coefficient of environmental factors is negative,The correlation coefficient between per capita GDP and environmental factors in the provincial panel regression model passed the significance test,and the correlation coefficient between GDP per capita and environmental factors was positive.The results of the three-stage DEA model show that the health efficiency of time series is improved to different extents,and the technical efficiency of model 2 is improved more than that of model 1,and the improvement effect is remarkable.After the adjustment of the average health efficiency of all provinces and cities in 2013-2017,the rankings of several provinces and cities have decreased,and the northeast region has improved.The central region has a small fluctuation,and most provinces and cities in the western region have made great progress.The mean value of pure technical efficiency changes greatly and scale efficiency.Conclusion:(1)The health efficiency estimates for 2003-2017 are all inefficient,mainly due to the inefficiency of scale efficiency,and the proportion of output growth is much lower than the proportion of input growth.(2)Technical efficiency There is a big difference between provinces.“ High input-high output”and“low input-low output”will lead to high efficiency.(3)The slack variables of input factors are affected by environmental factors.The increase in per capita GDP,household consumption level,illiteracy rate and total dependency ratio exacerbates the waste of input factors and has a negative impact on health.The increase of environmental factors will be conducive to the reduction of input redundancy,which is conducive to the improvement of health efficiency;the increase of environmental pollution in the panel regression will increase the waste of input factors and have a negative impact on health efficiency.(4)After the efficiency adjustment of various provinces and cities,technical efficiency,pure technical efficiency and scale efficiency have been improved to varying degrees.It shows that the confounding of external factors will measure the efficiency of various provinces and cities in China.Due to the large regionaldifferences between provinces and cities,different regions need to be placed under the same environmental level for comparative efficiency analysis.(5)The efficiency of a single model will underestimate the level of health efficiency in China.The three-stage DEA model is better than the traditional DEA model.The efficiency values calculated by the three-stage DEA model is more accurate and effective. |
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