Bootstrapping Data Envelopment Analysis of Efficiency and Productivity of County Public Hospitals in Eastern, Central, and Western China after the Public Hospital Reform

China implemented the public hospital reform in 2012. This study utilized bootstrapping data envelopment analysis（DEA） to evaluate the technical efficiency（TE） and productivity of county public hospitals in Eastern, Central, and Western China after the 2012 public hospital reform. Data from 127 county public hospitals（39, 45, and 43 in Eastern, Central, and Western China, respectively） were collected during 2012–2015. Changes of TE and productivity over time were estimated by bootstrapping DEA and bootstrapping Malmquist. The disparities in TE and productivity among public hospitals in the three regions of China were compared by Kruskal–Wallis H test and Mann–Whitney U test. The average bias-corrected TE values for the four-year period were 0.6442, 0.5785, 0.6099, and 0.6094 in Eastern, Central, and Western China, and the entire country respectively, with average non-technical efficiency, low pure technical efficiency（PTE）, and high scale efficiency found. Productivity increased by 8.12%, 0.25%, 12.11%, and 11.58% in China and its three regions during 2012–2015, and such increase in productivity resulted from progressive technological changes by 16.42%, 6.32%, 21.08%, and 21.42%, respectively. The TE and PTE of the county hospitals significantly differed among the three regions of China. Eastern and Western China showed significantly higher TE and PTE than Central China. More than 60% of county public hospitals in China and its three areas operated at decreasing return scales. There was a considerable space for TE improvement in county hospitals in China and its three regions. During 2012–2015, the hospitals experienced progressive productivity; however, the PTE changed adversely. Moreover, Central China continuously achieved a significantly lower efficiency score than Eastern and Western China. Decision makers and administrators in China should identify the causes of the observed inefficiencies and take appropriate measures to increase the efficiency of county public hospitals in the three areas of China, especially in Central China.

Data Envelopment Analysis on Evaluating the Efficiency of Public Hospitals in Tianjin,China

Public hospitals are the most important components of health systems and account for a large proportion of health resources in China. However, few researches on the efficiency assessment of public hospitals have been conducted in Tianjin, China. On the basis of the data of annual health service report in 2013 from the Ministry of Health, we measured the relative efficiency of the tertiary general public hospitals in Tianjin and estimated the magnitudes of output increase and/or input reduction by using data envelopment analysis to improve hospital efficiency. The main findings of this study indicate that more than half of the sample hospitals operate at a technical and scale efficiency, and the prevalent scale inefficiency is increasing returns to scale. Moreover, it is a prominent issue that health resource constraint and resource waste coexist. Health policy-makers and hospital administrators would need to address these problems by taking comprehensive measures such as optimizing the allocation of health resources, implementing hierarchical diagnosis and treatment, as well as innovating medical-service operating mechanism of public hospital to improve the people's wellbeing.

Efficiency and Productivity of County-level Public Hospitals Based on the Data Envelopment Analysis Model and Malmquist Index in Anhui, China

Background： China began to implement the national medical and health system and public hospital reforms in 2009 and 2012, respectively. Anhui Province is one of the four pilot provinces, and the medical reform measures received wide attention nationwide. The effectiveness of the above reform needs to get attention. This study aimed to master the efficiency and productivity of county-level public hospitals based on the data envelopment analysis （DEA） model and Malmquist index in Anhui, China, and then provide improvement measures for the future hospital development. Methods： We chose 12 country-level hospitals based on geographical distribution and the economic development level inAnhui Province. Relevant data that were collected in the field and then sorted were provided by the administrative departments of the hospitals. DEA models were used to calculate the dynamic efficiency and Malmquist index factors for the 12 institutions. Results： During 2010-2015, the overall average relative service efficiency of 12 county-level public hospitals was 0.926, and the number of hospitals achieved an effective DEA for each year from 2010 to 2015 was 4, 6, 7, 7, 6, and 8, respectively, as measured using DEA. During this same period, the average overall production efficiency was 0.983, and the total productivity factor had declined. The overall production efficiency of five hospitals was 〉1, and the rest are 〈1 between 2010 and 2015. Conclusions： In 2010-2015, the relative service efficiency of 12 county-level public hospitals in Anhui Province showed a decreasing trend, and the service efficiency of each hospital changed. In the past 6 years, although some hospitals have been effective, the efficiency of the county-level public hospitals in Anhui Province has not improved significantly, and the total factor productivity has not been effectively improved. County-level public hospitals need to combine their own reality to find their own deficiencies.

Performance Assessment of European Football Teams： Using Stochastic Data Envelopment Analysis Model

Data Envelopment Analysis （DEA） is a powerful mathematical optimization method widely used for measuring, evaluating and improving the performance of Decision Making Units （DMUs）. These used in the various forms, such as hospitals, government agencies, educational institutions, air force, bank branches, business finns, sport teams and even people including the performance of countries, regions, etc. Recently DEA has been extended to examine the performance through the different sport types. In this paper, a Stochastic Input Oriented Data Envelopment Analysis （SIODEA） Model is conducted for measuring and evaluating the relative efficiency scores of football teams selected from different European countries during 2014/2015 season each with some of inputs are stochastic with normally distributed and recent inputs are deterministic and outputs, to shed light on the professional football teams performance.

A New Approach for Ranking Efficient Units in Data Envelopment Analysis and Application to a Sample of Vietnamese Agricultural Bank Branches

This paper proposes a new approach for ranking efficiency units in data envelopment analysis as a modification of the super-efficiency models developed by Tone [1]. The new approach based on slacks-based measure of efficiency (SBM) for dealing with objective function used to classify all of the decision-making units allows the ranking of all inefficient DMUs and overcomes the disadvantages of infeasibility. This method also is applied to rank super-efficient scores for the sample of 145 agricultural bank branches in Viet Nam during 2007-2010. We then compare the estimated results from the new SCI model and the exsisting SBM model by using some statistical tests.

Efficiency measurement of fertilizer-manufacturing organizations usingFuzzy data envelopment analysis

The aim of the paper is to benchmark the performance of the Indian fertilizermanufacturing organizations based on the ranking of efficiencies using a fuzzy data envelopment analysis(FDEA).FDEA has been used to find the relative efficiency and ranking of the fertilizer-manufacturing organizations.The last few years’data have been converted into the fuzzy inputs and outputs as minimum,mean,and maximum values,respectively.The performance of the fertilizer manufacturing organizations is based on the output maximization model of DEA.The frontier organizations set the benchmark for the lagging organizations for further improvement in the performance.This method can also be used to incorporate the data of the several years for multiple inputs and outputs instead of consideration of data of only one year.The proposed approach in this study may help organizations to improve its efficiency to fulfill its goal.

The Correlation of Hospital Operational Efficiency and Average Length of Stay in China: A Study Based on Provincial Level Data

Objective: To measure the hospital operation efficiency, study the correlation between average length of stay and hospital operation efficiency, analyze the importance of shortening average length of stay to the improvement of the hospital operation efficiency and put forward relevant policy suggestion. Methods: Based on China provincial panel data from 2003 to 2012, the hospital operation efficiencies are calculated using Super Efficiency Data Envelopment Analysis model, and the correlation between average length of stay and hospital operation efficiency is tested using Spearman rank correlation coefficient test. Results: From 2003 to 2012, the average of national hospital operation efficiency was increasing slowly and the hospital operations were inefficient in most of the areas. The national hospital operation efficiency is negatively correlated to the average length of stay. Conclusion: Measures should be taken to set average length of stay in a scientific and reasonable way, improve social and economic benefits based on the improvement of efficiency.

A point-wise minimization model for data envelopment analysis considering environmental variables

Environmental variables are widely recognized as a cause of differences in efficiency measurement.However,the existing literature on data envelopment analysis(DEA)in environmental factors ignores the impact of demand on output.To address this gap,we propose the Point-wise Minimization DEA model(PWMDEA),which considers contextual variables that affect demand and lead to differences in efficiency.The model obtains efficiency value by considering the minimum of virtual inputs and virtual demand.Then,efficiency is evaluated by minimizing the ratio of above minimum to virtual output.This one-step model avoids issues of multi-stage assumptions and requires less data,making it more applicable.Moreover,we demonstrate the accuracy of our new model by conducting simulations with given true efficiency values.The simulation results demonstrate that our model has the lowest ranking error when the output is affected by multiple inputs or when demand has a significant impact.In addition,we evaluate the efficiency of healthcare in 31 Chinese provinces by considering two environmental factors.The results suggest that provinces with lower financial investments or population loss received higher rankings from our proposed model.These findings provide plausible explanations and demonstrate the practical usefulness of our model.

Empirical Study on the Measurement of the High-Tech Industry Efficiency in China--Based on the Data of China＇s 31 Provinces （Including Municipalities and Autonomous Regions）

To evaluate the relative effectiveness of the input and output of the high-tech industry in China＇s 31 provinces （including municipalities and autonomous regions）, DEA evaluation model was constructed using data envelopment analysis （DEA）, and DEA evaluation model was solved using Deap2.1 software, for the purpose of obtaining the DEA efficiency and the non-DEA efficiency in all the provinces （including municipalities and autonomous regions）. Then, the comprehensive efficiency, technical efficiency, scale efficiency, scale return, and projection analysis were analyzed. Finally, the provinces of the non-DEA efficiency are sorted according to three efficiencies, and also a goal of improvement is proposed for the purpose of expanding technology investment in the provinces of the DEA efficiency.

Comparative Study of Three Commonly Used Methods for Hospital Efficiency Analysis in Beijing Tertiary Public Hospitals, China

Background： Tertiary hospitals serve as the medical service center within the region and play an important role in the medical and health service system. They are also the key targets of public hospital reform in the new era in China. Through the reform of health system, the public hospital efficiency has changed remarkably. Therefore, this study aimed to provide some advice for efficiency assessment of public hospitals in China by comparing and analyzing the consistency of results obtained by three commonly used methods for examining hospital efficiency, that is, ratio analysis （RA）, stochastic frontier analysis （SFA）, and data envelopment analysis （DEA）. Methods： The theoretical basis, operational processes, and the application status of RA, SFA, and DEA were learned through literature analysis. Then, the empirical analysis was conducted based on measured data from 51 tertiary public hospitals in Beijing from 2009 to 2011. Results： The average values of hospital efficiency calculated by SFA with index screening and principal component analysis （PCA） results and those calculated by DEA with index screening results were relatively stable. The efficiency of specialized hospitals was higher than that of general hospitals and that of traditional Chinese medicine hospitals. The results obtained by SFA with index screening results and the results obtained by S FA with PCA results showed a relatively high correlation （r-value in 2009, 2010, and 2011 were 0.869, 0.753, and 0.842, respectively, P 〈 0.01）. The correlation between results obtained by DEA with index screening results and PCA results and results obtained by other methods showed statistical significance, but the correlation between results obtained by DEA with index screening results and PCA results was lower than that between results obtained by SFA with index screening results and PCA results. Conclusions： RA is not suitable for multi-index evaluation of hospital efficiency. In the given conditions, SFA is a stable efficiency analysis method. In the evaluation of hospital efficiency, DEA combined with PCA should be adopted with caution due to its poor stability.

基于波士顿矩阵分析法的区域医院科技创新效率研究

目的通过客观评价了解区域医院科技创新效率,推动医院医学学科建设,为医院争创国家区域医疗中心的建设目标提供助力。方法基于医院科技量值指标体系,选取深圳市67家三级医院作为研究对象,分析医院科技创新发展情况,利用波士顿矩阵分析法反映医院科技创新效率。结果深圳市医院间科技创新效率有较大差距:6家医院以相对低的科技投入产生了较高的科技产出,科技创新效率最好;13家医院以较高的科技投入产生了较高的科技产出,具有较好的科技创新效率,科技产出仍可再提升;1家医院科技投入高而科技产出较低,具有较低的科技创新效率,在科技产出方面仍有较大提升空间;47家医院科技投入较低且科技产出也较低,在科技投入及科技产出两个维度仍需发力。结论应依据城市经济高质量发展水平,加强医院科技创新投入水平,引导产出高质量医学科技成果,提升医院科技创新效率。

基于改进三阶段松弛测量-数据包络模型的火电上市公司碳排放效率评估研究

【目的】计算火电上市公司的碳排放效率,对比分析效率排名居后的原因及排名前列的驱动因素,根据差异性条件对火电公司进行分组,探讨造成效率差异的影响因素。【方法】基于非期望产出的改进三阶段松弛值测量(slackbasedmeasure, SBM)-数据包络分析(data envelopment analysis,DEA)模型评估中国火电上市公司2016—2022年全要素碳排放效率。【结果】火电上市公司的碳排放效率逐年递增,并在剔除外部环境影响后整体下降。增加政府环保补贴可能会引发火电公司资本、人员和煤炭过度投入;增加地区研发投入对公司资产、人员和煤耗量具有积极作用;区域经济水平的提高会促进企业资产优化配置和人员有效管理,但会导致发电煤耗量的浪费。【结论】中央实控、低煤耗率和有碳排放交易的火电上市公司技术差距率更高,整体碳排放效率水平更优。

Stock Efficiency Evaluation Based on Multiple Risk Measures:A DEA-Like Envelopment Approach

This paper proposes a new approach for stock efficiency evaluation based on multiple risk measures. A derived programming model with quadratic constraints is developed based on the envelopment form of data envelopment analysis(DEA). The derived model serves as an input-oriented DEA model by minimizing inputs such as multiple risk measures. In addition, the Russell input measure is introduced and the corresponding efficiency results are evaluated. The findings show that stock efficiency evaluation under the new framework is also effective. The efficiency values indicate that the portfolio frontier under the new framework is more externally enveloped than the DEA efficient surface under the standard DEA framework.

基于DEA的三级公立医院手术科室效率研究

目的中国公立医院进入高质量发展的新时代,各医院手术数量不断攀升,管理部门亟需引进一套科学评价手术科室资源效率的工具,促使医院充分利用现有手术资源。方法数据包络分析法(data envelopment analysis,DEA)对投入产出效率进行评价。以中国首批高质量发展试点单位北京市某三甲医院为例,投入量为手术科室的医护人数、床位数量、专用设备原值,产出量为经过CMI校正的手术量和出院人数。结果通过DEA模型分析,发现该医院只有K7、K9两个科室实现DEA有效,K1、K2纯技术效率过低,说明未充分利用现有手术资源。从规模效益上看,K3、K6处于递减状态,K7、K9不变,其余科室递增。通过Malmquist指数对技术效率和规模效率进行动态评价,结果显示,除新冠疫情影响期间外,其余期间均处于全要素增长率递增状态。文章也计算了各投入产出的松弛变量,精确得出应调整的生产资料投入值和产出工作量的数值。结论案例医院各手术科室效率参差不齐,决策层应对未充分利用手术资源的科室给予指导;对实现DEA有效的科室,在手术资源分配上给予适当倾斜。

基于DEA模型的多院区医院临床科室运行效率分析

目的:分析多院区医院临床科室运行效率,为完善多院区协同发展机制提供参考。方法:运用数据包络分析中的BCC模型和Malmquist生产率指数模型,分析多院区医院临床科室运行效率。结果:不同院区同一临床科室综合效率存在差异;效率相对较低的科室主要在于规模不合理或组织管理水平不高;分院区相关科室技术进步明显,而组织管理和规模经济短期受到影响。结论:多院区医院要发挥优势学科辐射带动作用,提升“非有效”科室的组织管理水平,探索适宜发展的规模;结合不同院区功能定位和科室发展特征,合理规划和布局各项医疗资源,推动医院高质量发展。

基于数据包络分析的中国污染地块治理绩效评价研究

中国高速的城市化进程产生了大量工业企业搬迁,造成众多污染地块需要治理。中国为治理污染地块耗资巨大,但缺乏相关的绩效评价。筛选了40个典型污染地块治理工程(涉及全国33个区县)进行绩效评价并探究了污染地块治理绩效的影响因素。结果表明:(1)山东省、河北省及湖南省中南部地区的污染地块治理绩效较高,重庆市、湖南省等华中地区及东南沿海地区零星有一些污染地块治理绩效相对较低。(2)地块尺度,资金投入不足、时间投入过短、人员投入过少是影响污染地块治理绩效的重要因素,期望产出方面也仍有很大提升空间,非期望产出方面需要进一步控制污染排放。(3)区县尺度,污染地块治理绩效主要与工业增加值占国内生产总值比例和年末总人口呈显著(p<0.05)正相关,说明经济和人口是主要影响因素。

珠海市慢性疾病预防控制能力建设现状分析

目的 了解珠海市基本公共卫生服务慢性疾病项目管理现状、管理能力及基础资源配置等,分析评估基础资源配置效率和慢性疾病防控能力建设制约因素与需求等,为制定慢性疾病预防控制相关政策和防控策略提供依据。方法 在调查的7家疾控中心和29家基层医疗卫生机构中,共有卫生技术在岗人员590人,结合定性访谈进行现场问卷调查,应用数据包络分析技术(DEA模型)分析珠海市各镇街基层医疗卫生机构基本公共卫生服务慢性疾病管理资源配置投入产出效率。结果 珠海市开展慢性疾病预防控制服务项目的基层医疗卫生技术人员的平均年龄为(38.34±10.34)岁,大专及以下学历人员占48.1%,初级职称或无职称人员占59.5%,公共卫生专业人员仅占29.5%,非在编人员占55.1%。2021年珠海市25个镇街综合效率(TE)平均值为0.785,6个镇街TE达到DEA有效,其他均存在不同程度产出不足的情况。结论 强化珠海市政府慢性疾病管理职责,可通过完善慢性疾病管理基础配置、加快推进慢性疾病管理信息化建设、采取形式多样的督导与培训等方式提升慢性疾病预防控制能力建设。

基于DEA-Malmquist指数模型的我国中医医院服务效率评价研究

目的评价2017—2023年全国30个省(区、市)中医医院的服务效率,为促进中医医院高质量发展提供参考。方法运用数据包络分析法中的BCC模型和Malmquist指数模型测算全国中医医院服务效率的静态和动态变化,利用时间序列预测法预测2022—2023年的指标变化并进行动态评价。结果2021年全国中医医院的综合效率均值为0.852,50%的省(区、市)处于DEA无效状态,2017—2021年全国中医医院的总体服务效率呈现下降态势,全要素生产率指数均值为0.958,平均下降4.2%,东、中、西部地区的指数均值分别为0.978、0.946和0.951,3大地区均出现不同程度的下降,经预测分析后的2017—2023年整体效率变化趋势不大。结论全国中医医院的总体服务效率处于较低水平,且区域发展差异明显,其中技术进步指数是一项重要影响因素。各省(区、市)应合理控制中医医院的发展规模,不断推动技术进步,提高资源利用率,逐步缩小地区差异,进而提升中医医院的服务效率。

基于两阶段中立型交叉效率和Shannon熵的公交服务效益评价:利益相关者视角

为了获得高区分度、更准确的公交服务效益评价结果,提出了一种基于两阶段中立型交叉效率和Shannon熵集结模型的组合评价方法。基于网络数据包络分析模型得到两阶段中立型交叉效率模型中的自评结果,在此基础上测算出互评结果,利用Shannon熵集结模型将自评与互评结果集结得出最终交叉效率值。从公交企业、公众和政府三方利益相关者的角度构建了公交服务效益评价指标体系,对2011~2016年间“长三角”地区案例进行研究。结果表明:大多数公交企业的运营状况均不佳,但综合效益总体上在缓慢提升;服务过程评价结果显著优于生产过程评价结果;小型规模公交企业综合效益最高,其次是中型规模企业,而大型规模企业最低;政府大量的补贴和公交企业过量的资源投入会对效益产生负面影响。

排污权交易对福建绿色发展效率的影响研究

绿色发展是一种基于传统发展模式的可持续发展的创新模式,提高绿色发展的关键是提高绿色发展效率。为进一步检验排污权交易政策对福建省绿色发展效率的影响,该文首先采用数据包络分析方法的超效率模型测算绿色发展效率,其次将2011-2020年未实际开展排污权交易的省份作为控制组,通过合成控制法分析排污权交易对福建省绿色发展效率的影响情况,并进行了稳健性检验。结果表明:(1)资源配置效率是导致绿色发展效率不均衡的关键因素。(2)福建省排污权交易政策的实施对绿色发展效率呈促进作用,从拟合的结果来看,2015年若未实施排污权交易,其绿色发展效率均值将比实际值有所下降。