42,946 research outputs found
Advancing efficiency analysis using data envelopment analysis: the case of German health care and higher education sectors
The main goal of this dissertation is to investigate the advancement of efficiency analysis through DEA. This is practically followed by the case of German health care and higher education organizations. Towards achieving the goal, this dissertation is driven by the following research questions:
1.How the quality of the different DEA models can be evaluated?
2.How can hospitalsâ efficiency be reliably measured in light of the pitfalls of DEA applications?
3.In measuring teaching hospital efficiency, what should be considered?
4.At the crossroads of internationalization, how can we analyze university efficiency?
Both the higher education and the health care industries are characterized by similar missions, organizational structures, and resource requirements. There has been increasing pressure on universities and health care delivery systems around the world to improve their performance during the past decade. That is, to bring costs under control while ensuring high-quality services and better public accessibility. Achieving superior performance in higher education and health care is a challenging and intractable issue. Although many statistical methods have been used, DEA is increasingly used by researchers to find best practices and evaluate inefficiencies in productivity. By comparing DMU behavior to actual behavior, DEA produces best practices frontier rather than central tendencies, that is, the best attainable results in practice. The dissertation primarily focuses on the advancement of DEA models primarily for use in hospitals and universities. In Section 1 of this dissertation, the significance of hospital and university efficiency measurement, as well as the fundamentals of DEA models, are thoroughly described. The main research questions that drive this dissertation are then outlined after a brief review of the considerations that must be taken into account when employing DEA. Section 2 consists of a summary of the four contributions. Each contribution is presented in its entirety in the appendices. According to these contributions, Section 3 answers and critically discusses the research questions posed.
Using the Translog production function, a sophisticated data generation process is developed in the first contribution based on a Monte Carlo simulation. Thus, we can generate a wide range of diverse scenarios that behave under VRS. Using the artificially generated DMUs, different DEA models are used to calculate the DEA efficiency scores. The quality of efficiency estimates derived from DEA models is measured based on five performance indicators, which are then aggregated into two benchmark-value and benchmark-rank indicators. Several hypothesis tests are also conducted to analyze the distributions of the efficiency scores of each scenario. In this way, it is possible to make a general statement regarding the parameters that negatively or positively affect the quality of DEA estimations. In comparison with the most commonly used BCC model, AR and SBM DEA models perform much better under VRS. All DEA applications will be affected by this finding. In fact, the relevance of these results for university and health care DEA applications is evident in the answers to research questions 2 and 4, where the importance of using sophisticated models is stressed.
To be able to handle violations of the assumptions in DEA, we need some complementary approaches when units operate in different environments. By combining complementary modeling techniques, Contribution 2 aims to develop and evaluate a framework for analyzing hospital performance. Machin learning techniques are developed to perform cluster analysis, heterogeneity, and best practice analyses. A large dataset consisting of more than 1,100 hospitals in Germany illustrates the applicability of the integrated framework. In addition to predicting the best performance, the framework can be used to determine whether differences in relative efficiency scores are due to heterogeneity in inputs and outputs. In this contribution, an approach to enhancing the reliability of DEA performance analyses of hospital markets is presented as part of the answer to research question 2. In real-world situations, integer-valued amounts and flexible measures pose two principal challenges. The traditional DEA models do not address either challenge. Contribution 3 proposes an extended SBM DEA model that accommodates such data irregularities and complexity. Further, an alternative DEA model is presented that calculates efficiency by directly addressing slacks. The proposed models are further applied to 28 universities hospitals in Germany. The majority of inefficiencies can be attributed to âthird-party funding incomeâ received by university hospitals from research-granting agencies. In light of the fact that most research-granting organizations prefer to support university hospitals with the greatest impact, it seems reasonable to conclude that targeting research missions may enhance the efficiency of German university hospitals. This finding contributes to answering research question 3.
University missions are heavily influenced by internationalization, but the efficacy of this strategy and its relationship to overall university efficiency are largely unknown. Contribution 4 fills this gap by implementing a three-stage mathematical method to explore university internationalization and university business models. The approach is based on SBM DEA methods and regression/correlation analyses and is designed to determine the relative internationalization and relative efficiency of German universities and analyze the influence of environmental factors on them. The key question 4 posed can now be answered. It has been found that German universities are relatively efficient at both levels of analysis, but there is no direct correlation between them. In addition, the results show that certain locational factors do not significantly affect the universityâs efficiency.
For policymakers, it is important to point out that efficiency modeling methodology is highly contested and in its infancy. DEA efficiency results are affected by many technical judgments for which there is little guidance on best practices. In many cases, these judgments have more to do with political than technical aspects (such as output choices). This suggests a need for a discussion between analysts and policymakers. In a nutshell, there is no doubt that DEA models can contribute to any health care or university mission. Despite the limitations we have discussed previously to ensure that they are used appropriately, these methods still offer powerful insights into organizational performance. Even though these techniques are widely popular, they are seldom used in real clinical (rather than academic) settings. The only purpose of analytical tools such as DEA is to inform rather than determine regulatory judgments. They, therefore, have to be an essential part of any competent regulatorâs analytical arsenal
Changes in Hospital Efficiency after Privatization
We investigated the effects of privatization on hospital efficiency in Germany. To do so, we obtained bootstrapped DEA efficiency scores in the first stage of our analysis and subsequently employed a difference-in-difference matching approach within a panel regression framework. Our findings show that conversions from public to private for-profit status were associated with an increase in efficiency of between 3.2 and 5.4%. We defined four alternative post- privatization periods and found that the increase in efficiency after a conversion to private for- profit status appeared to be permanent. We also observed an increase in efficiency one year after hospitals were converted to private non-profit status, but our estimations suggest that this effect was transitory. Our findings also show that the efficiency gains after a conversion to private for-profit status were achieved through substantial decreases in staffing ratios in all analyzed staff categories with the exception of physicians. It was also striking that the efficiency gains of hospitals converted to for-profit status were significantly lower in the DRG era than in the pre-DRG era. Altogether, our results suggest that converting hospitals to private for-profit status may be an effective way to ensure the scarce resources in the hospital sector are used more efficiently.Privatization, Performance measurement, Data envelopment analysis, Propensity score matching, Germany
Measuring and comparing the (in)efficiency of German and Swiss hospitals
A nonparametric Data Envelopment Analysis (DEA) is performed on hospitals in the federal state of Saxony (Germany) and in Switzerland. This study is of interest from three points of view. First, contrary to most existing work, patient days are not treated as an output but as an input. Second, the usual DEA assumption of a homogeneous sample is tested and rejected for a large part of the observations. The proposed solution is to restrict DEA to comparable observations in the two countries. Finally, hospital beds are treated as a discretionary input in one DEA and as a fixed input in the other, and the effect on efficiency is related to differences in hospital planning in Germany and Switzerland. Based on the comparable observations, hospitals of Saxony have higher efficiency scores than their Swiss counterparts. --International efficiency comparison,Hospitals,Data Envelopment Analysis
Cost and Technical Efficiency of German Hospitals â A Stochastic Frontier Analysis
Using a newly available and multifaceted dataset provided by the German Federal Statistical Office, this paper is the first to investigate both technical and cost efficiency of more than 1500 German general hospitals conducting a stochastic frontier analysis. The empirical results for the years from 2000 to 2003 indicate that private and non-profit hospitals are on average less cost and technical efficient than publicly owned hospitals. One explanation for this result may be that German private and non-profit hospitals produce at a longer average length of stay and, thereby, a higher cost per case than public institutions due to the incentives provided by reimbursement schemes until 2004. Furthermore, the paper reveals that non-subsidised hospitals are less efficient than their respective counterparts. Controlling for patientsâ characteristics (in addition to the constructed case-mix weights), it can be shown that a high ratio of old patients decreases efficiency whereas a high ratio of female patients and a high surgery rate increase it.Hospital efficiency, ownership, privatisation
Harnessing Health Care Markets for the Public Interest: Insights for U.S. Health Reform From the German and Dutch Multipayer Systems
Outlines how the German and Dutch systems offer universal coverage via competing insurance plans and promote effective and efficient care. Highlights insurance exchanges, multipayer policies and group purchasing, information systems, and public reporting
Effects of ownership, subsidization and teaching activities on hospital costs in Switzerland
This paper explores the cost structure of Swiss hospitals, focusing on differences due to teaching activities and those across different ownership and subsidization types. A stochastic total cost frontier with a Cobb-Douglas functional form has been estimated for a panel of 150 general hospitals over the six-year period from 1998 and 2003. Inpatient cases adjusted by DRG cost weights and ambulatory revenues are considered as two separate outputs. The adopted econometric specification allows for unobserved heterogeneity across hospitals. The results indicate that the time-invariant unobserved factors could account for considerable cost differences that could be only partly due to inefficiency. The results suggest that teaching activities are an important cost driving factor and hospitals that have a broader range of specialization are relatively more costly. The excess costs of university hospitals can be explained by more extensive teaching activities as well as the relatively high quality of medical units. However, even after controlling for such differences university hospitals have shown a relatively low cost-efficiency especially in the first two or three years of the sample period. The analysis does not provide any evidence of significant efficiency differences across ownership and subsidization categories.general hospitals, teaching hospitals, stochastic frontier, cost efficiency
Benchmarking the Health Sector in Germany â An Application of Data Envelopment Analysis
At present, a first round of hospital benchmarking as required by German law on health care reform takes place. After extensive discussions between hospitals and insurance companies, which are jointly responsible to deliver benchmarking results, a method with some peculiar characteristics was chosen. In this paper it is argued that the deficiencies of said method could be overcome by using Data Envelopment Analysis (DEA). The reasons that make DEA an advisable tool for policy decisions within the context of relative performance evaluation in the health care sector are discussed. In order to illustrate the potential of nonparametric frontier estimation for hospital benchmarking in Germany, a comparison of hospitals, which provide the same basic clinical care, is carried out. Controlling for differences in the case mix and for possible heterogeneity of the services which hospitals provide, substantial productivity differences can be detected. Beyond simply identifying inefficient providers DEA leads to additional insight about the reasons of inefficiency and to useful management implications.Health care reform benchmarking relative performance evaluation Data Envelopment Analysis
The welfare state and new challenge from the back door
1980s in Germany, Britain, France and Italy suggests a convergent and consistent process of homogenisation driven chiefly by institutional mimetic isomorphism. This new 'organisational settlement' is increasingly shaped by the structural autonomisation of individual service delivery units. This paper argues that, when organisational autonomy becomes normatively sanctioned, that this increases the likelihood of its adoption, even in the face of different institutional conditions and welfare regimes. Hence, the paper is foremost concerned with explaining similarities and decreasing variance across countries and across sectors, and with accounting for the main driver of this homogenisation process. Why would different organisational fields across countries and welfare regimes adopt similar structures, in light of inconclusive evidence of economic efficiency gains? The convergence of the organisational settlement of the welfare delivery state is not only driven by economic globalisation or efficiency linked to performance, but primarily by the political demand to find new sources of legitimation in an age of increasing displacement of political authority to managers. The paper is structured in three main parts. First, it revisits the theory of organisational isomorphism by its application to the new patterns of change of welfare delivery. Secondly, it discusses the reform trajectories of autonomisation in schooling and hospital care in Britain, in comparative terms with France and Italy. Thirdly, it concentrates on Germany and it establishes empirically how this case does no longer fit the characterisation of 'immobilisme', especially in the health care sector. Lastly, the wider implications of organisational homogenisation for the TRUDI constellation are discussed. --
Does Higher Cost Inefficiency Imply Higher Profit Inefficiency? - Evidence on Inefficiency and Ownership of German Hospitals
This paper investigates cost and profit efficiency of German hospitals. More specifically, it deals with the question how hospital efficiency varies with ownership, patient structure and other exogenous factors, which are neither inputs nor outputs of the production process. We conduct a Stochastic Frontier Analysis (SFA) on a multifaceted administrative German dataset combined with the balance sheets of 374 hospitals for the years 2002 to 2005.The results indicate that private (for-profit) and (private) non-profit hospitals are on average less cost efficient but more profit efficient than publicly owned hospitals.Hospital efficiency, ownership, stochastic frontier analysis, profit function
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A parallel approach to analysis of costs/benefits and efficiency changes resulting from privatisation of health services
The marketisation of public health care systems is part of a long process, which is not necessarily clearly set out or understood at the beginning. Public policy plays an important role in creating internal markets and changing public health care systems. The findings of this review show that there are now recognisable steps in the process of moving from a state/ government run health care system to a marketised and privatised system but this can take place over many years
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