Technical efficiency and economies of diversification in health care

Economies of scope in the Norwegian public hospital sector

This study investigates the potential economies of scope in the Norwegian public hospital sector after a major structural and organizational reform. Economies of scope refers to potential cost savings occurring from the scope of production rather than the scale. We use a data driven approach to distinguish between relatively specialized and differentiated hospitals. Using registry data spanning the period 2013-2019, we use non-parametric data envelopment analysis with bootstrapping procedures to investigate the potential presence of economies of scope. This is done separately for three different dimensions of which hospital production can be either specialized or differentiated. The findings suggest that economies of scope are present in the Norwegian hospital sector, meaning that there are cost savings related to the optimal differentiation of the activity. It is difficult to conclude on how these findings relate to the reform.

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.

Technical efficiency of Portuguese public hospitals: A comparative analysis across the five regions of Portugal

The present study aims to analyse the efficiency scores of hospital units, with reference to the five Portuguese health administrative regions (North, Centre, Lisbon and Tagus Valley, Alentejo, and Algarve). This paper contextualizes the process of decentralization of health in Portugal (started 1993) as well as the hospitals' corporatization and merging reforms (started 2002). These reforms aimed to meet health care needs by optimizing costs, improving efficiency, and broadening both access and quality in health services. Data envelopment analysis was used to quantify and compare the efficiencies of 27 hospitals heterogeneously distributed by five administrative regions. The results show a large average performance across the country. However, there are regions with scores larger than the national average and others with inferior results. This interregional diversity points towards disparities that deserve special attention from the policymakers and hospital managers.

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.

Exploring the relationship between costs and quality: does the joint evaluation of costs and quality alter the ranking of Danish hospital departments?

OBJECTIVE

The purpose is to evaluate the relationship between costs and quality and to assess whether the joint evaluation of costs and quality affects the ranking of hospital departments relative to comparison based on costs alone.

METHODS

Using patient level data for 3,754 patients in six vascular departments, we estimate fixed effect models for costs (linear) and quality (logistic). We consider two quality measures; mortality and wound complications. To assess whether the joint evaluation of costs and quality affects the ranking of departments, we construct joint confidence regions for each pair of departmental effects for costs and quality using a bootstrap method and rank departments according to their cost-effectiveness ratio. The findings are used to evaluate a theory of a U-shaped cost/quality relationship.

RESULTS

The association between cost and quality differs depending on how quality is measured. Lower costs are associated with higher mortality, implying a cost/quality trade-off. In contrast, there is no clear association between costs and wound complications among vascular departments.

CONCLUSIONS

Compared to benchmarking of departments based solely on their costs, we show that the ranking of departments may be altered considerably when quality is taken into account. Consequently, it is important to have a well-rounded view of departmental objectives when undertaking performance evaluation. The results for mortality may lend some support to the theory of a U-shaped cost/quality relationship. However, the results for wound complications do not support the theory of a U-shaped cost/quality relationship.

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.