Evaluating hospital performance with case-mix-adjusted outputs

Applications of data envelopment analysis in acute care hospitals: a systematic literature review, 1984-2022

This study reviews scholarly publications on data envelopment analysis (DEA) studies on acute care hospital (ACH) efficiency published between 1984 and 2022 in scholarly peer-reviewed journals. We employ systematic literature review (SLR) method to identify and analyze pertinent past research using predetermined steps. The SLR offers a comprehensive resource that meticulously analyzes DEA methodology for practitioners and researchers focusing on ACH efficiency measurement. The articles reviewed in the SLR are analyzed and synthesized based on the nature of the DEA modelling process and the key findings from the DEA models. The key findings from the DEA models are presented under the following sections: effects of different ownership structures; impacts of specific healthcare reforms or other policy interventions; international and multi-state comparisons; effects of changes in competitive environment; impacts of new technology implementations; effects of hospital location; impacts of quality management interventions; impact of COVID-19 on hospital performance; impact of teaching status, and impact of merger. Furthermore, the nature of DEA modelling process focuses on use of sensitivity analysis; choice of inputs and outputs; comparison with Stochastic Frontier Analysis; use of congestion analysis; use of bootstrapping; imposition of weight restrictions; use of DEA window analysis; and exogenous factors. The findings demonstrate that, despite several innovative DEA extensions and hospital applications, over half of the research used the conventional DEA models. The findings also show that the most often used inputs in the DEA models were labor-oriented inputs and hospital beds, whereas the most frequently used outputs were outpatient visits, followed by surgeries, admissions, and inpatient days. Further research on the impact of healthcare reforms and health information technology (HIT) on hospital performance is required, given the number of reforms being implemented in many countries and the role HIT plays in enhancing care quality and lowering costs. We conclude by offering several new research directions for future studies.

Do adjustment costs constrain public healthcare providers' technical efficiency? Evidence from the New Zealand Public Healthcare System

Efficiency analysis is crucial in healthcare to optimise resource allocation and enhance patient outcomes. However, the prompt adaptation of inputs can be hindered by adjustment costs, which impact Long-Run Technical Efficiency (LRTE). To bridge this gap in healthcare literature, this research employs a Bayesian Dynamic Stochastic Frontier Model to estimate parameters and explore healthcare efficiency dynamics over time. The study reveals the LRTE for New Zealand District Health Boards (DHBs) as 0.76, indicating around 32% more input utilisation due to adjustment costs. Most DHBs exhibit consistent short-run operational efficiency, with the national Short-Run Technical Efficiency (SRTE) very close to the LRTE. Among the tertiary providers, Auckland and Capital & Coast DHBs operate below the LRTE level, setting them apart from other tertiary providers. Similarly, Tairawhiti and West Coast DHBs also fall below the LRTE level, as indicated by their SRTE scores, potentially influenced by their unique healthcare settings and resource challenges. This research brings a new perspective to policy discussions by incorporating the temporal dynamics of decision-making and considering adjustment costs. It underscores the need to balance short-term and long-term technical efficiency, underlining their collective significance in fostering a sustainable and efficient healthcare system in New Zealand.

Efficiency analysis in the management of COVID-19 pandemic in India based on data envelopment analysis

Purpose: This article measured the performance of 32 states and union territories (UTs) of India against COVID-19 disease using efficiency score which was calculated by data envelopment analysis (DEA) and compared the efficiency score with the different models which are used in many articles to evaluate the efficiency of healthcare system. Here the input parameters are taken as public health expenditure in a million, number of hospitals, number of hospital beds, percentage of health workers, population density, and number of infected, and output parameters divided into good and bad categories such as the number of recovered are taken as good output. The number of death is taken as bad outputs. The modified undesirable output model is used to calculate efficiency score and compared the efficiency score with Charnes, Cooper, and Rhodes (CCR) and Banker, Charnes, and Cooper (BCC) models. Finally, the states & UTs are completely ranked with the help of efficiency score and Maximal Balance Index, and evaluated benchmarking for each states & UTs. Data Source: Secondary data were collected from Census 2011 and the Ministry of health & family welfare, Government of India on 32 stats & UTs (NHAC, 2018; NHP, 2019; COVID19India, 2021). Results: According to Undesirable model results, 16 (50%) of 32 Indian states & UTs s were found to be efficient. Among the efficient DMUs, Chandigarh is the most efficient unit and Meghalaya is the most inefficient unit. Rajasthan was the most referenced state for inefficient states. Limitation: The efficiency score is affected by changing the number of inputs and outputs. The lack of more effective parameters are used to evaluate performance and enable qualitative variable comparison.

Adding a Social Risk Adjustment Into the Estimation of Efficiency: The Case of Chilean Hospitals

BACKGROUND AND OBJECTIVES

There is much interest in adding social variables to hospital performance assessments. Many of the existing analyses, however, already include patients' diagnosis data, and it is not clear that adding a social adjustment variable would improve the quality of the results: the growing literature on this issue provides mixed results. The purpose in this study was to add evidence from a developing country into this discussion.

METHODS

We estimate the efficiency of hospitals controlling for casemix, with and without adjusting the hospital's casemix for the patients' sociodemographic variables. The magnitude of the adjustment is based on the observed impact of age, sex, and income on length of stay, conditional on the diagnosis related group (DRG). We use a data envelopment analysis (DEA) to assess the efficiency of 50 Chilean hospitals' discharges, including 780 DRGs and covering about 60% of total discharges in Chile from 2013 to 2015.

RESULTS

We found that the sociodemographic adjustment introduces very small changes in the DEA estimation of efficiency. The underlying reason is the relatively low influence of sociodemographics on hospital costs, conditional on DRG, and the changing pattern of sociodemographics across DRGs for any given hospital.

CONCLUSION

We conclude that the casemix-adjusted estimation of hospital efficiency is robust to the heterogeneity of patients' sociodemographic heterogeneity across hospitals. These results confirm, in a developing country, what has been observed in developed countries. For management purposes, then, the processing costs of adding social variables into hospitals' performance assessments might not be justified.

An application of PCA-DEA with the double-bootstrap approach to estimate the technical efficiency of New Zealand District Health Boards

Using yearly panel data from 2011 to 2017 on New Zealand District Health Boards (DHBs), this study combines principal component analysis and data envelopment intertemporal analysis with the double-bootstrap approach to estimate the technical efficiency of health care providers along with the trend of efficiency performances. The results show that although most large DHBs have improved their level of technical efficiency between 2011 and 2017, the majority of medium- and small-sized DHBs have not seen any noticeable improvement in their level of technical efficiency. The results also show that large and tertiary DHBs operate at a high level of technical efficiency. In contrast, most of the medium- and small-sized DHBs posted some of the lowest technical efficiency scores. Furthermore, the results show that medium- and small-sized DHBs have a higher average length of hospital stays which is found to be associated with decreasing levels of technical efficiency scores.

Hospital Policy and Productivity - Evidence from German States

Total factor productivity (TFP) growth allows for additional healthcare services under restricted resources. We examine whether hospital policy can stimulate hospital TFP growth. We exploit variation across German federal states in the period 1993-2013. State governments decide on hospital capacity planning (number of hospitals, departments, and beds), ownership, medical students, and hospital investment funding. We show that TFP growth in German hospital care reflects quality improvements rather than increases in output volumes. Second-stage regression results indicate that reducing the length of stay is generally a proper way to foster TFP growth. The effects of other hospital policies depend on the reimbursement scheme: Under activity-based (German Diagnosis-related Group) hospital funding, scope-related policies (privatization and specialization) come with TFP growth. Under fixed daily rate funding, scale matters to TFP (hospital size and occupancy rates). Differences in capitalization in East and West Germany allow to show that deepening capital may enhance TFP growth if capital is scarce. We also show that there is less scope for hospital policies after large-scale restructurings of the hospital sector. Copyright © 2016 John Wiley & Sons, Ltd.

Integrated Analysis of Healthcare Efficiency: A Systematic Review

Data Envelopment Analysis (DEA) has been used as a performance measurement tool in efficiency assessment of healthcare systems. However, over the years, researchers and health practitioners presented the theoretical and methodological limitations of DEA that limits the full view of healthcare efficiency. To address these limitations, a commonly used strategy is to integrate other statistical methods and techniques with DEA to provide better efficiency evaluation. This paper reviews 57 studies with DEA applications in the healthcare industry to illustrate the integrated analysis of healthcare efficiency. With DEA as the central method, regression models in conjunction with statistical tests are commonly used. Input-oriented radial DEA models using predominantly capacity-related inputs and activity-related outputs and following either constant return to scale or variable return to scale assumptions are mostly applied to measure healthcare efficiency.

Efficiency and productivity measurement of rural township hospitals in China: a bootstrapping data envelopment analysis

OBJECTIVE

Township hospitals (THs) are important components of the three-tier rural healthcare system of China. However, the efficiency and productivity of THs have been questioned since the healthcare reform was implemented in 2009. The objective of this study is to analyse the efficiency and productivity changes in THs before and after the reform process.

SETTING AND PARTICIPANTS

A total of 48 sample THs were selected from the Xiaogan Prefecture in Hubei Province from 2008 to 2014.

OUTCOME MEASURES

First, bootstrapping data envelopment analysis (DEA) was performed to estimate the technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of the sample THs during the period. Second, the bootstrapping Malmquist productivity index was used to calculate the productivity changes over time.

RESULTS

The average TE, PTE and SE of the sample THs over the 7-year period were 0.5147, 0.6373 and 0.7080, respectively. The average TE and PTE increased from 2008 to 2012 but declined considerably after 2012. In general, the sample THs experienced a negative shift in productivity from 2008 to 2014. The negative change was 2.14%, which was attributed to a 23.89% decrease in technological changes (TC). The sample THs experienced a positive productivity shift from 2008 to 2012 but experienced deterioration from 2012 to 2014.

CONCLUSIONS

There was considerable space for TE improvement in the sample THs since the average TE was relatively low. From 2008 to 2014, the sample THs experienced a decrease in productivity, and the adverse alteration in TC should be emphasised. In the context of healthcare reform, the factors that influence TE and productivity of THs are complex. Results suggest that numerous quantitative and qualitative studies are necessary to explore the reasons for the changes in TE and productivity.

Market Structure and Technical Efficiency in the Hospital Services Industry: A DEA Approach

This article uses data envelopment analysis and multiple regression analysis to examine empirically the impact of various market-structure elements on the technical efficiency of the hospital services industry in various metropolitan areas of the United States. Market-structure elements include the degree of rivalry among hospitals, extent of HMO activity, and health insurer concentration. The DEA results show the typical hospital services industry experienced 11 percent inefficiency in 1999. Moreover, multiple regression analysis indicates the level of technical efficiency varied directly across metropolitan hospital services industries in response to greater HMO activity and private health insurer concentration in the state. The analysis suggests the degree of rivalry among hospitals had no marginal effect on technical efficiency at the industry level. Evidence also implies that the presence of a state Certificate of Need law was not associated with a greater degree of inefficiency in the typical metropolitan hospital services industry.

Output congestion leads to compromised care in Peruvian public hospital neonatal units

Peru is moving toward a universal health insurance system, and it is facing important challenges in the provision of public health services. As more citizens gain access to health insurance, the flow of patients exceeds the capacity of public hospitals to provide care with quality. In this study we explore the relationship between technical efficiency and patient safety events in neonatal care units of Peru's public hospitals. We use Data Envelope Analysis (DEA) with output congestion to assess the association between technical efficiency and patient safety events. We study 35 neonatal care units of public hospitals in Peru's Social Security Health System, and identify two undesirable (risk-adjusted) safety outcomes: neonatal mortality and near-miss neonatal mortality. We found that for about half of hospital's neonatal care units, technical efficiency is affected by output congestion. For those hospitals, patient safety is being compromised by receiving too many patients. Our results are consistent with public reports indicating that hospitals in the Peru's Social Security Health System are overcrowded, affecting efficiency and jeopardizing quality of care. We found that most congested hospitals are located in the capital city and suburban areas, and are more likely to be hospitals with the lowest and the highest level of care. Our results call for improvements in the patient referral system and capacity expansion.

Slack based measure of efficiencies of public sector hospitals in Uttarakhand (India)

Purpose

– The purpose of this paper is to determine the relative efficiencies of public sector hospitals in Uttarakhand, India.

Design/methodology/approach

– The study use data of public hospitals collected from Directorate of Medical Health and Family Welfare, Government of Uttarakhand, Dehradun, India for the year 2011. The cross-sectional data analyses are carried out by applying data envelopment analysis (DEA) based slack based model.

Findings

– The analysis found that out of total 36 hospitals only ten hospitals are relatively overall technical efficient. The average overall technical efficiency 54.10 per cent indicates that an average hospital has the scope of producing the outputs with the inputs 45.90 per cent lesser than their existing levels. The slack analysis results show that on average 12.57 per cent of beds, 13.16 per cent of doctors, 14.04 per cent of paramedical staff can be reduced and 17.53 per cent of out-door patients, 66.55 per cent of in-door patients, 208.23 per cent of major surgeries, 110.73 per cent of minor surgeries can be expanded if all the inefficient hospitals operate at the level of efficient hospitals.

Originality/value

– The present study is undertaken to measure the relative efficiencies of public sector hospitals in Uttarakhand. There is dearth of studies being done on Indian healthcare sector and this study will help to utilize healthcare resources efficiently for formulating policy implications for public hospitals in Uttarakhand. For the robustness of DEA results, Jackknifing analysis is also conducted.

A data envelopment analysis approach for measuring the efficiency of Canadian acute care hospitals

Data envelopment analysis is a methodology particularly well-suited to measuring the efficiency of hospitals because it is able to accommodate multiple heterogeneous inputs and outputs in order to model the complex relationships that exist within them. This research uses data envelopment analysis to develop a model of Canadian hospital production efficiency in collaboration with the Canadian Institute for Health Information. The model is intended to illustrate the utility of data envelopment analysis as a hospital performance measurement tool for Canadian Institute for Health Information and to augment their current hospital performance indicators. The model measures the overall production efficiency of acute care hospitals using labour and capital inputs together with outputs measuring inpatient and outpatient activity. The model also includes non-discretionary variables adjusting for case-mix variations among the hospitals. The model is extensively validated and identifies a set of highly referenced, efficient hospitals ideal for the establishment of best practices.

Improving the effectiveness of service delivery in the public healthcare sector: the case of ophthalmology services in Malaysia

Background

Rising demand of ophthalmology care is increasingly straining Malaysia’s public healthcare sector due to its limited human and financial resources. Improving the effectiveness of ophthalmology service delivery can promote national policy goals of population health improvement and system sustainability. This study examined the performance variation of public ophthalmology service in Malaysia, estimated the potential output gain and investigated several factors that might explain the differential performance.

Methods

Data for 2011 and 2012 on 36 ophthalmology centres operating in the Ministry of Health hospitals were used in this analysis. We first consulted a panel of ophthalmology service managers to understand the production of ophthalmology services and to verify the production model. We then assessed the relative performance of these centres using Data Envelopment Analysis (DEA). Efficiency scores (ES) were decomposed into technical, scale, and congestion component. Potential increase in service output was estimated. Sensitivity analysis of model changes was performed and stability of the result was assessed using bootstrap approach. Second stage Tobit regression was conducted to determine if hospital type, availability of day services and population characteristics were related to the DEA scores.

Results

In 2011, 33 % of the ophthalmology centres were found to have ES > 1 (mean ES = 1.10). Potential output gains were 10 % (SE ± 2.92), 7.4 % (SE ± 2.06), 6.9 % (SE ± 1.97) if the centres could overcome their technical, scale and congestion inefficiencies. More centres moved to the performance frontier in 2012 (mean ES = 1.07), with lower potential output gain. The model used has good stability. Robustness checks show that the DEA correctly identified low performing centres. Being in state hospital was significantly associated with better performance.

Conclusions

Using DEA to benchmarking service performance of ophthalmology care could provide insights for policy makers and service managers to intuitively visualise the overall performance of resource use in an otherwise difficult to assess scenario. The considerable potential output gain estimated indicates that effort should be invested to understand what drove the performance variation and optimise them. Similar performance assessment should be undertaken for other healthcare services in the country in order to work towards a sustainable health system.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-015-1011-0) contains supplementary material, which is available to authorized users.

Should inpatients be adjusted by their complexity and severity for efficiency assessment? Evidence from Portugal

Hospital efficiency analysis depends largely on the model specifications. This study discusses the importance of the case-mix index (CMI) to homogenize the sample of inpatient discharges. It proposes a new index where they are classified by service, since it is usual to have lack of data to compute the CMI and this can influence the credibility of results. Data from the Portuguese national diagnosis-related group (DRG) database was utilized. Three different approaches are developed in this paper, based on locally convex order-m method as well as on translog functions. The first one correlates the efficiency with different inpatients weighting schemes, by using the Nadaraya-Watson method. The second approach compares different frontiers that have been computed using the different weighting schemes. Finally, by using bootstrap, the paper investigates whether the inclusion of severity/ complexity-related variables in the model statistically modifies the results. It has been shown that, under the Portuguese healthcare framework, if the model is environment corrected (which should include epidemiological and main political/ structural health reforms variables), then the severity adjustment of inpatients is pointless. The employment of an inpatient-weighting scheme, such as the CMI, may introduce significant frontier shift, thus its absence is not recommended in productivity evolution analyzes. The CMI shifts the efficiency frontier, but not the relative position of units against it (the last scenario if exogenous variables are present).

Mapping and modeling of physician collaboration network

Effective provisioning of healthcare services during patient hospitalization requires collaboration involving a set of interdependent complex tasks, which needs to be carried out in a synergistic manner. Improved patients' outcome during and after hospitalization has been attributed to how effective different health services provisioning groups carry out their tasks in a coordinated manner. Previous studies have documented the underlying relationships between collaboration among physicians on the effective outcome in delivering health services for improved patient outcomes. However, there are very few systematic empirical studies with a focus on the effect of collaboration networks among healthcare professionals and patients' medical condition. On the basis of the fact that collaboration evolves among physicians when they visit a common hospitalized patient, in this study, we first propose an approach to map collaboration network among physicians from their visiting information to patients. We termed this network as physician collaboration network (PCN). Then, we use exponential random graph (ERG) models to explore the microlevel network structures of PCNs and their impact on hospitalization cost and hospital readmission rate. ERG models are probabilistic models that are presented by locally determined explanatory variables and can effectively identify structural properties of networks such as PCN. It simplifies a complex structure down to a combination of basic parameters such as 2-star, 3-star, and triangle. By applying our proposed mapping approach and ERG modeling technique to the electronic health insurance claims dataset of a very large Australian health insurance organization, we construct and model PCNs. We notice that the 2-star (subset of 3 nodes in which 1 node is connected to each of the other 2 nodes) parameter of ERG has significant impact on hospitalization cost. Further, we identify that triangle (subset of 3 nodes in which each node is connected to the rest 2 nodes), alternative k-star (subset of k nodes in which 1 node is connected to each of other k - 1 nodes), and alternative k - 2 path (subset of k nodes in which, between a specific pair of nodes, there exists k - 2 paths of length 2) parameters of ERG have impact on the hospital readmission rate. Our findings can have implications for healthcare administrators or managers who could potentially improve the practice cultures in their organizations by following these outcomes.

Performance evaluation in home and community care

Our research objective was to estimate the technical efficiency of regions in Ontario, Canada delivering home care relative to the 'best performance' frontier. Data Envelopment Analysis (DEA), an efficiency frontier technique, measured the technical efficiency of each geographically-defined Community Care Access Centre (CCAC) controlling for case-mix and service quality. Differences in case-mix and service quality did not fully explain the variation in efficiency scores across CCACs. Most CCACs in our sample were scale inefficient (i.e., not operating at an optimal size). The inability of home care providers to select patients or to adjust the service area is a potential explanation for the observed patterns in inefficiency. Efficiency analysis appears to represent an additional tool for use in assessing the performance of providers in the home and community care sector.

Social Efficiency of Hospital Care Delivery: Frontier Analysis From the Consumer’s Perspective

The efficiency of hospital services and patients’ access to hospitals are both important health care policy issues. In the past, research has relied on studying these topics separately. In this article, we measure both efficiency and access at the same time using data envelopment analysis (DEA). By including both the technically efficient use of resources, as well as the patients’ travel distances, we found increases in social efficiency when patients’ travel distances were taken into account. When compared with patients with nonurgent conditions, we found that patients suffering from conditions requiring urgent attention were treated at closer hospitals, increasing the social efficiency. Insurance coverage and hospital ownership were also examined. Our findings corroborated past literature in the hospital and travel distance literature and set out a framework for future research. Perhaps most important, we demonstrate the techniques needed to incorporate broader measures of social costs into studies of hospital efficiency.

Do hospitals practice cream skimming?

‘Cream skimming’ refers to choosing patients for some characteristic(s) other than their need for care, which enhances the profitability or reputation of the provider. Under capitation or other fixed payment schemes, this often means choosing less ill patients. We present a new methodology to measure cream skimming by hospitals. Our approach also provides a measure of a hospital's gain in productive efficiency by caring for patients with lower illness severity. Using a panel of Washington state hospitals, we find evidence that hospitals do practice cream skimming. However, we find little evidence to suggest that cream skimming varies by hospital size, profit status or time.

The short-term effect on technical and scale efficiency of establishing regional health systems and general management in Greek NHS hospitals

OBJECTIVES

The Greek National Health System has been subjected to a reform initiative in 2001. The new legislation required hospitals to operate as administrative and economic decentralized units, under the control of newly established Regional Health Systems. In addition, Professional Managers have been appointed and signed "efficiency contracts", which supposedly committed them to run the hospitals effectively and efficiently. The present study aims at estimating the efficiency impact of this reform.

METHODS

Data Envelopment Analysis was employed with included inputs being the number of medical staff employees, other hospital employees and staffed beds, whereas outputs were the case-mix adjusted inpatient cases, outpatient visits and surgical operations performed. The technical and scale efficiencies of a sample of 51 general acute National Health System hospitals have been comparatively examined before and after the reform.

RESULTS

The analysis surprisingly indicates that technical and scale efficiency has been reduced following the policy changes.

CONCLUSIONS

It appears that the expected benefits from the reform have not in general been achieved, at least in the short-run. This result is examined in light of coexisting administrative and organizational factors, which are impeding the reform process.

Investigating health system performance: an application of data envelopment analysis to Zambian hospitals

BACKGROUND

Zambia has recently articulated an ambitious national health program designed to meeting health-related MDGs. Public expectations are high and Zambia continues to receive significant resources from global and bilateral donors to support its health agenda. Although the lack of adequate resources presents the most important constraint, the efficiency with which available resources are being utilised is another challenge that cannot be overlooked. Inefficiency in producing health care undermines the service coverage potential of the health system. This paper estimates the technical efficiency of a sample of hospitals in Zambia.

METHODS

Efficiency is measured using a DEA model. Vectors of hospital inputs and outputs, representing hospital expended resources and output profiles respectively, were specified and measured. The data were gathered from a sample of 30 hospitals throughout Zambia. The model estimates an efficiency score for each hospital. A decomposition of technical efficiency into scale and congestion is also provided.

RESULTS

Results show that overall Zambian hospitals are operating at 67% level of efficiency, implying that significant resources are being wasted. Only 40% of hospitals were efficient in relative terms. The study further reveals that the size of hospitals is a major source of inefficiency. Input congestion is also found to be a source of hospital inefficiency.

CONCLUSION

This study has demonstrated that inefficiency of resource use in hospitals is significant. Policy attention is drawn to unsuitable hospital scale of operation and low productivity of some inputs as factors that reinforce each other to make Zambian hospitals technically inefficient at producing and delivering services. It is argued that such evidence of substantial inefficiency would undermine Zambia's prospects of achieving its health goals.

Non-parametric and parametric applications measuring efficiency in health care

This paper reviews 188 published papers on frontier efficiency measurement. The techniques used are mainly based on non-parametric data envelopment analysis, but there is increasing use of parametric techniques, such as stochastic frontier analysis. Applications both to hospitals and wider health care areas are reviewed and summarised, and some meta-type analysis undertaken. Results appear to confirm earlier findings that public provision demonstrates less variability than private. The paper is meant as a resource in itself, but also points to the future in terms of possible directions for research in efficiency measurement in health care and health.

On the efficiency of public, welfare and private hospitals in Germany over time: a sectoral data envelopment analysis study

This paper examines the efficiency of the German hospital sector over time and the relative efficiency of public, welfare (both nonprofit) and private (for-profit) hospital sectors using data from the Federal Statistics Office of German hospitals. Efficiency scores were computed using data envelopment analysis. The absolute efficiency of the hospital sector as a whole was found to have improved between 1991 and 1996. In this comparison, the empirical results showed that the hospitals in the public and welfare sector are relatively more efficient than private hospitals. Our results suggest that public, welfare and private hospital sectors have different best-practice frontiers; and that public and welfare hospital sectors appear to use relatively fewer resources than private hospitals. These results suggest differences in quality of care arising from ownership.

Comparing teaching and non-teaching hospitals: a frontier approach (teaching vs. non-teaching hospitals)

This paper compares teaching and non-teaching hospitals in terms of their provision of patient services. We proceed by comparing the frontiers of the teaching and non-teaching hospitals using a data envelopment (DEA) type approach, which we apply to a sample of 236 teaching hospitals and 556 non-teaching hospitals operating in the US in 1994. Our results suggest that only about 10% of the teaching hospitals can effectively "compete" with non-teaching hospitals based on the provision of patient services.

The technical efficiency of hospitals under a single payer system: the case of Ontario community hospitals

Using DEA, we investigated the impact of ownership, size, and location on the relative technical efficiency of community hospitals in Ontario, which has a single payer system. Consistent with Hansmann's theory of non-profit organizations and contrary to US-based research, we find no significant differences in efficiency across ownership types (government, religious or secular non-profit). Nor do we find significant differences in efficiency by size or location. Our findings suggest that model formulation and differences in payer mix across types of hospitals in the US have a strong influence on the measurement of the hospital ownership-efficiency relationship.

Alternative methods to examine hospital efficiency: data envelopment analysis and stochastic frontier analysis

There has been increasing interest in the ability of different methods to rank efficient hospitals over their inefficient counterparts. The UK Department of Health has used three cost indices to benchmark NHS hospitals (Trusts). This study uses the same dataset and compares the efficiency rankings from the cost indices with those obtained using Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA). The paper concludes that the methods each have particular strengths and weaknesses and potentially measure different aspects of efficiency. Several specifications should be used to develop ranges of inefficiency to act as signalling devices rather than point estimates. It is argued that differences in efficiency scores across different methods may be due to random "noise" and reflect data deficiencies. The conclusions concur with previous findings that there are not truly large efficiency differences between Trusts and savings from bringing up poorer performers would in fact be quite modest.

Efficiency measurement of health care: a review of non-parametric methods and applications

There has been increasing interest in measuring the productive performance of health care services, since the mid-1980s. This paper reviews this literature and, in particular, the concept and measurement of efficiency and productivity. Concerning measurement, we focus on the use of Data Envelopment Analysis (DEA), a technique particularly appropriate when multiple outputs are produced from multiple inputs. Applications to hospitals and to the wider context of general health care are reviewed and the empirical evidence from both the USA and Europe (EU) is that public rather than private provision is more efficient.

The impact of the internal market on hospital efficiency, productivity and service quality

In this paper we use non-parametric mathematical programming models to compute and decompose Malmquist indices of productivity and quality change, which are used to evaluate the reforms in the UK National Health Service in the early nineties. We focus on acute hospitals and we study them over the first five years of the reforms. The findings of the study indicate that there was a productivity slowdown in the first year after the reforms but productivity progress in the subsequent years and thus, overall there was a net gain in productivity over the entire period considered. Productivity trends were dominated by technical change rather than hospital relative efficiency changes, as hospitals were already largely relatively efficient at the time of the introduction of the reforms. In fact, over the last four years in the period studied there was small relative efficiency regress and this does not bear out the argument that the reforms would increase hospital efficiency. The productivity changes are similar when service quality is incorporated in the analysis but the magnitude of these changes diminishes. Quality of service followed different trends to productivity change and this may have been the price for the productivity gains achieved.

A descriptive assessment of the production and cost efficiency of general hospitals in Greece

This paper focuses on the assessment of alternative aspects of the efficiency of 98 out of 126 hospitals of the Greek national health system. The analysis is directly concerned with the degree of utilisation of resources and the production efficiency of the general hospitals selected. For the measurement of the indices of efficiency, the internationally known method of Data Envelopment Analysis (modified to the particular characteristics of the Greek NHS) was used. The efficiency of Greek hospitals was assessed utilising two alternative conceptual models: one focusing on production and the other on cost efficiency. The results, in both cases, indicated the scope for substantial efficiency improvements. The analysis has sought to discuss the policy implications resulting from the current efficiency status of the hospitals with reference to issues of resource re-allocation and optimal scale size.

A review of organizational performance assessment in health care

As health care organizations look for ways to ensure cost-effective, high quality service delivery while still meeting patient needs, organizational performance assessment (OPA) is useful in focusing improvement efforts. In addition, organizational performance assessment is essential for ongoing management decision-making, operational effectiveness and strategy formulation. In this paper, the roles and impact of OPA models in use in health care are reviewed, and areas of potential abuse, such as myopia, tunnel vision and gaming, are identified. The review shows that most existing OPA models were developed primarily as sources of information for purchasers or consumers, or to enable providers to identify areas for improvement. However, there was little conclusive evidence evaluating their impact. This review of existing OPA models enabled the establishment of principles for the development, implementation and prevention of abuse of OPA specific to health care. The OPA models currently in use in health care may provide managers with false confidence in their ability to monitor organizational performance. To further enhance the field of OPA, areas for future research are identified.

Financial performance of safety-net hospitals in a changing health care environment

Safety-net hospitals serving the poor and indigent in inner-cities have received inadequate research attention regarding the determinants of their financial performance in the changing health care environment. We analyze how the 1990-92 financial performance of 275 such hospitals is related to exogenous and endogenous factors such as payer mix, service mix, staffing and ownership. Models of hospital financial performance are developed using operating margin, cost per discharge and revenue per discharge as measures of performance. Stepwise regression is used to test the model with data from the American Hospital Association (AHA) and Health Care Investment Analysts (HCIA). Results suggest that: 1) The profitability of inner-city hospitals appears positively related with technical complexity of care; 2) High interest and low operating surplus may constrain the addition of technically sophisticated services to enhance profitability; 3) There is some evidence that new governmental programs, e.g. Medicaid managed care and Medicaid Diagnosis Related Groups (DRGs), may not have improved operating margins, though Medicaid DRGs appear to have contained costs. Follow-up research is needed on this issue; 4) Given external fiscal realities, internal management strategies for inner-city hospitals require research, e.g. developing appropriate managed care systems and timely expansion of sub-acute services and; 5) Services such as AIDS treatment and community health education represent opportunities to respond to community needs, especially since unit cost of such services will decline with high volume.