A Systematic Review of Hospital Efficiency and Productivity Studies: Lessons from Australia, UK and Canada.

Abstract

BackgroundAgeing populations, more expensive technology, growing rates of chronic disease and increasing consumer expectations are expected to lead to increased demand for health services and a rise in health expenditure within Australia. Productivity and efficiency analysis of Australia’s health system could provide valuable insight into the performance of the health system and assist stakeholders to reduce unnecessary growth in public hospital expenditure. This review describes efficiency and productivity analyses of hospitals in Australia, Canada and the United Kingdom. Methods We conducted a systematic literature review of efficiency and productivity analyses of hospitals in Australia, Canada and the United Kingdom. The search was conducted in two stages; (1) a search of the grey literature using a Google search engine; and (2) a traditional systematic review method search of academic databases. It is uncommon for grey literature to have abstracts, therefore, executive summaries, table of contents or subheadings were screened. Titles and Abstracts of journal articles were screened. DiscussionWithin Australia and key comparator nations, the number of efficiency and analysis studies is small. There is no clear consensus on the most suitable analysis technique to measure efficiency and productivity of hospitals. However, selection of inputs is similar across all studies identified in this review, consisting of measures of labour (most commonly relating to full time equivalent employees), goods and services (e.g. purchased consumables, such as drugs), and capital. Similarly, the majority of studies struggled to identify output measures that could capture improvements in patient outcomes, a key performance measure for any hospital. Instead, most studies utilised proxy measures relating to hospital throughputs (number of separations) or population health measurements. Of note, only one study demonstrated active engagement with the health sector in study development. Conclusion There is considerable scope for the further development of efficiency and productivity analysis techniques that can adequately capture relevant production factors, allow for robust comparisons across hospitals and time periods and which meaningfully engage with the health sector to inform improvements in efficiency and productivity.

Approach in Inputs & Outputs Selection of Data Envelopment Analysis (DEA) Efficiency Measurement in Hospital: A Systematic Review

“…The selection of appropriate inputs and outputs is essential for the analysis of DEA to be useful, and we cannot emphasise this point enough. As many previous reviews stated, the quality and quantity of these indicators play a major role in the DEA efficiency analysis [15–18,20,21,30,33]. We observed in term of inputs, majority of the studies (52.76%) used staff-related input as part of the variables in efficiency measurement.…”

“…Numerous studies have been published to demonstrate the usefulness and potential of DEA in evaluating hospital efficiency [28][29][30][31]. Although creating hypotheses by comparing DEA ratings across several hospital studies is helpful, there are significant drawbacks.…”

“…The methodology of DEA has been the subject of dozens of review studies on hospital application. General applications of DEA to health care performance measurement [15,16,18], categorization or clustering of DEA technique [20,33], comparing DEA analysis between other methods, between countries or between two periods [28,30,34,35], or new knowledge and new approach on the assessment of DEA [17,21]. A systematic literature review (SLR) uses organized, transparent, and replicable techniques at each stage of the process to completely discover and synthesize literature that is relevant to a certain subject.…”

“…The methodology of DEA has been the subject of dozens of review studies on hospital application. General applications of DEA to health care performance measurement[15,16,18], categorization or clustering of DEA technique [20,33], comparing DEA analysis between other methods, between countries or between two periods [28,30,34,35], or new knowledge and new approach on the assessment of DEA [17,21].…”