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

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.

Financial Performance and Profile of Brazilian Hospitals

The literature on data envelopment analysis (DEA) of hospital efficiency has used absolute data to approach financial and operating indicators, either separate or combined. This study stratifies a sample of Brazilian hospitals using financial and operating indicators to investigate their performance, based on financial liquidity ratios and levels of indebtedness against their profitability and return on investments. The models obtained in the analysis show that the level of indebtedness and the operating margin are determinants of efficiency, but they may be overrun by debt capital and return on investments, depending on installed capacity.

Key Indicators Affecting Hospital Efficiency: A Systematic Review

Background

Measuring hospital efficiency is a systematic process to optimizing performance and resource allocation. The current review study has investigated the key input, process, and output indicators that are commonly used in measuring the technical efficiency of the hospital to promote the accuracy of the results.

Methods

To conduct this systematic review, the electronic resources and databases MEDLINE (via PubMed), Scopus, Ovid, Proquest, Google Scholar, and reference lists of the selected articles were used for searching articles between 2010 and 2019. After in-depth reviews based on the inclusion and exclusion criteria, among 1,537 studies, 144 articles were selected for the final assessment. Critical Appraisal Skills Programme (CASP) Checklist was used for evaluating the quality of the articles. The main findings of studies have been extracted using content analysis.

Results

After the final analysis, the Context/Input indicators that were commonly considered by studies in analyzing hospital technical efficiency include different variables related to Hospital Capacity, Structure, Characteristics, Market concentration, and Costs. The Process/Throughput indicators include different variables related to Hospital Activity or services-oriented process Indicators, Hospital Quality-oriented process indicators, and Hospital Educational processes. Finally, the Output/Outcome indicators include different variables related to Hospital Activity-related output variables and Quality-related output/outcomes variables.

Conclusion

This study has identified that it is necessary to mix and assess a set of input, process, and output indicators of the hospital with both quantitative and qualitative indicators for measuring the technical efficiency of hospitals comprehensively.

Technical Efficiency of Public and Private Hospitals in Beijing, China: A Comparative Study

Objective: With the participation of private hospitals in the health system, improving hospital efficiency becomes more important. This study aimed to evaluate the technical efficiency of public and private hospitals in Beijing, China, and analyze the influencing factors of hospitals’ technical efficiency, and thus provide policy implications to improve the efficiency of public and private hospitals. Method: This study used a data set of 154–232 hospitals from “Beijing’s Health and Family Planning Statistical Yearbooks” in 2012–2017. The data envelopment analysis (DEA) model was employed to measure technical efficiency. The propensity score matching (PSM) method was used for matching “post-randomization” to directly compare the efficiency of public and private hospitals, and the Tobit regression was conducted to analyze the influencing factors of technical efficiency in public and private hospitals. Results: The technical efficiency, pure technical efficiency and scale efficiency of public hospitals were higher than those of private hospitals during 2012–2017. After matching propensity scores, although the scale efficiency of public hospitals remained higher than that of their private counterparts, the pure technical efficiency of public hospitals was lower than that of private hospitals. Panel Tobit regression indicated that many hospital characteristics such as service type, level, and governance body affected public hospitals’ efficiency, while only the geographical location had an impact on private hospitals’ efficiency. For public hospitals in Beijing, those with lower average outpatient and inpatient costs per capita had better performance in technical efficiency, and bed occupancy rate, annual visits per doctor, and the ratio of doctors to nurses also showed a positive sign with technical efficiency. For private hospitals, the average length of stay was negatively associated with technical efficiency, but the bed occupancy rate, annual visits per doctor, and average outpatient cost were positively associated with technical efficiency. Conclusions: To improve technical efficiency, public hospitals should focus on improving the management standards, including the rational structure of doctors and nurses as well as appropriate reduction of hospitalization expenses. Private hospitals should expand their scale with proper restructuring, mergers, and acquisitions, and pay special attention to shortening the average length of stay and increasing the bed occupancy rate.

The economic efficiency of clinical laboratories in public hospitals: A case study in Iran

Introduction

Clinical laboratories are identified as one of the most important and expensive units of the health system. Therefore, it is essential to pay attention to these units' cost efficiency. This study purpose was to evaluate the economic efficiency of hospitals' laboratory units affiliated to Urmia University of Medical Sciences (UMSU), in order to assess their performance.

Methods

This research was a descriptive‐analytic study that was accomplished in 2017. The statistical population of the study included all of the hospitals' clinical laboratories affiliated to UMSU. Moreover, DEA method and Deap_2.1 software were used to analyze data. In this study, technical and allocative efficiencies of the studied laboratory units were also calculated in addition to the determination of the economic efficiency of the laboratories.

Results

The average economic efficiency of clinical laboratories calculated by DEA in 2017 was 0.676. This value was lower than the allocative and technical efficiency scores, which indicates that these units could attain full efficiency by reducing their costs without having any effect on output values. Moreover, about 14 percent of the clinical laboratory units were economically efficient. In addition, it is noteworthy to state that, from total of university hospital laboratories, only three hospitals had no economic excess or deficiency values of inputs.

Conclusion

Considering that 76% of laboratory units have not been economically efficient, it is necessary for the laboratory managers to consider optimum allocating of resources, with respect to the cost of laboratory equipment and inputs in order to increase their units' economic efficiency.

The Determinants of the Technical Efficiency of Acute Inpatient Care in Canada

OBJECTIVE

To evaluate the technical efficiency of acute inpatient care at the pan-Canadian level and to explore the factors associated with inefficiency-why hospitals are not on their production frontier.

DATA SOURCES/STUDY SETTING

Canadian Management Information System (MIS) database (CMDB) and Discharge Abstract Database (DAD) for the fiscal year of 2012-2013.

STUDY DESIGN

We use a nonparametric approach (data envelopment analysis) applied to three peer groups (teaching, large, and medium hospitals, focusing on their acute inpatient care only). The double bootstrap procedure (Simar and Wilson 2007) is adopted in the regression.

DATA COLLECTION/EXTRACTION METHODS

Information on inpatient episodes of care (number and quality of outcomes) was extracted from the DAD. The cost of the inpatient care was extracted from the CMDB.

PRINCIPAL FINDINGS

On average, acute hospitals in Canada are operating at about 75 percent efficiency, and this could thus potentially increase their level of outcomes (quantity and quality) by addressing inefficiencies. In some cases, such as for teaching hospitals, the factors significantly correlated with efficiency scores were not related to management but to the social composition of the caseload. In contrast, for large and medium nonteaching hospitals, efficiency related more to the ability to discharge patients to postacute care facilities. The efficiency of medium hospitals is also positively related to treating more clinically noncomplex patients.

CONCLUSIONS

The main drivers of efficiency of acute inpatient care vary by hospital peer groups. Thus, the results provide different policy and managerial implications for teaching, large, and medium hospitals to achieve efficiency gains.

Efficiency and optimal size of hospitals: Results of a systematic search

Background

National Health Systems managers have been subject in recent years to considerable pressure to increase concentration and allow mergers. This pressure has been justified by a belief that larger hospitals lead to lower average costs and better clinical outcomes through the exploitation of economies of scale. In this context, the opportunity to measure scale efficiency is crucial to address the question of optimal productive size and to manage a fair allocation of resources.

Methods and findings

This paper analyses the stance of existing research on scale efficiency and optimal size of the hospital sector. We performed a systematic search of 45 past years (1969–2014) of research published in peer-reviewed scientific journals recorded by the Social Sciences Citation Index concerning this topic. We classified articles by the journal’s category, research topic, hospital setting, method and primary data analysis technique. Results showed that most of the studies were focussed on the analysis of technical and scale efficiency or on input / output ratio using Data Envelopment Analysis. We also find increasing interest concerning the effect of possible changes in hospital size on quality of care.

Conclusions

Studies analysed in this review showed that economies of scale are present for merging hospitals. Results supported the current policy of expanding larger hospitals and restructuring/closing smaller hospitals. In terms of beds, studies reported consistent evidence of economies of scale for hospitals with 200–300 beds. Diseconomies of scale can be expected to occur below 200 beds and above 600 beds.

Assessing the relationships between hospital resources and activities: a systematic review

Face the challenge of minimizing their resource utilization without reducing the quality of healthcare. Achieving this aim requires precise analysis and optimization of various inputs and outputs. This paper presents a systematic review of the relationships between hospital resources (considered productivity inputs) and financial and activity outcomes (considered productivity outputs). Several electronic bibliographic databases and the Internet were searched for articles published between January 1990 and December 2013 that examined the relationships between hospital resources and financial and activity outcomes. We assessed the quality of the study design, the nature of the sample, input and output indicators, and the statistical methods used for each selected study. Thirty-eight original papers were selected. Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) were the most statistical methods used. Based on our analysis, we retained 18 input and 19 output indicators that could constitute the basis for hospital productivity benchmarking. Selecting a small set of shared economic and activity indicators is relevant for assessing the productivity of a hospital, measuring trends and performing national or international benchmarking. Such indicators should be combined with quality measures for a comprehensive evaluation approach.

Efficiency, ownership, and financing of hospitals: the case of Austria

While standard economic theory posits that privately owned hospitals are more efficient than their public counterparts, no clear conclusion can yet be drawn for Austria in this regard. As previous Austrian efficiency studies rely on data from the 1990s only and are based on small hospital samples, the generalizability of these results is questionable. To examine the impact of ownership type on efficiency, we apply a Data Envelopment Analysis which extends the existing literature in two respects: first, it evaluates the efficiency of the Austrian acute care sector, using data on 128 public and private non-profit hospitals from the year 2010; second, it additionally focusses on the inpatient sector alone, thus increasing the comparability between hospitals. Overall, the results show that in Austria, private non-profit hospitals outperform public hospitals in terms of technical efficiency. A multiple regression analysis confirms the significant association between efficiency and ownership type. This conclusive result contrasts some international evidence and can most likely be attributed to differences in financial incentives for public and private non-profit hospitals in Austria. Therefore, by drawing on the example of the Austrian acute care hospital sector and existing literature on the German acute care hospital sector, we also discuss the impact of hospital financing systems and their incentives on efficiency. This paper thus also aims at providing a proof of principle, pointing out the importance of the respective market conditions when internationally comparing hospital efficiency by ownership type.

Cost-efficiency in Medicaid long-term support services: the role of home and community based services

Growth in home and community based services (HCBS) has been implicated in rising long-term care expenditure in the Medicaid program. Its efficiency impact has not been tested. Using Stochastic Frontier Analysis (SFA) and panel data methods, we evaluated the cost efficiency of long-term support services (LTSS) provided by state Medicaid agencies and examined its association with intensity of HCBS use. We compared the efficiency of state funded HCBS programs with federal waiver programs. We found substantial variation in cost efficiency of LTSS programs by states, but all showed improvement over time related to increased HCBS use. Higher participation in federal waivers programs yielded additional improvements in cost-efficiency. Results indicate that increasing HCBS services targeted at “high need” population and developmentally disabled individuals would improve efficiency in LTSS delivery. These results reveal the importance of measuring and comparing efficiencies across Medicaid funded LTSS programs, as we introduce reforms in the LTSS delivery system. We recommend that Medicaid agencies invest in the development of improved data sources for the estimation of cost efficiencies of their programs.

Efficiency improvements of public hospitals under a capitation payment scheme

In a context of cost containment and demands for better quality in public health care, payment systems are used as an instrument to promote efficiency improvements in service providers. Andalusia has adopted an original type of risk-adjusted capitation payment mechanism to reimburse public hospitals. This paper presents the main characteristics of the reimbursement mechanism of the Andalusian Health Service highlighting some differences with the mechanisms adopted in other parts of Europe. The paper also explores the evolution of the efficiency and quality of the hospitals after its implementation using the Malmquist index. Results indicate that hospitals have slightly improved their efficiency, particularly urban hospitals, and these improvements are not significantly related to a negative evolution of quality. However, it is not possible to assert to what extent, improvements are the consequence of the new payment system. The organisation of the Servicio Andaluz de Salud and the limited competition between hospitals reduce the effectiveness of the reform.

Productive innovations in hospitals: an empirical research on the relation between technology and productivity in the Dutch hospital industry

This paper studies the relationship between technology and productivity in Dutch hospitals. In most studies technical change is measured by a proxy, namely a time trend. In practice however, innovations slowly spread over all hospitals and so different hospitals are operating under different technologies at the same point in time. In this study we explicitly inventory specific and well-known innovations in the Dutch hospital industry in the past ten years. These innovations are aggregated into a limited number of homogenous innovation clusters, which are measured by a set of technology index numbers. The index numbers are included in the cost function specification and estimation. The results indicate that technical change is non-neutral and output- biased and that some technologies affect cost in beneficial ways.

The decomposition of cost efficiency: an empirical application of the shadow cost function model to Dutch general hospitals

This paper investigates the performance of the Dutch general hospital industry by a parametric method. In general, the parametric approaches find more difficulties in distinguishing between technical and allocative efficiencies than DEA. Only recently a class of models is developed based on shadow prices which have possibilities to distinguish between technical and allocative efficiency. However, these models cause some serious computational problems. This paper recommends an approach to overcome these problems by using an iterative two-stage estimation procedure. The estimation is conducted on a panel data set of Dutch general hospitals. Estimation shows that this method is effective. The parameter estimates are plausible, reliable and satisfy all theoretical requirements. In particular we find some reliable estimates for the individual hospitals' shadow prices. According to these shadow prices hospitals should reallocate their resources in favor of material supplies at the cost of other personnel and nursing personnel. The mean technical efficiency is about 86%, whereas the allocative efficiency is about 92%. The outcomes also show that technical progress is very small. Economies of scale are present only for small hospitals.

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.