Translating Frontiers Into Practice: Taking the Next Steps Toward Improving           Hospital Efficiency

Mutter, Ryan; Rosko, Michael D.; Greene, William H.; Wilson, Paul W.

doi:10.1177/1077558710384878

Cited by 27 publications

(17 citation statements)

References 52 publications

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“…Thereby, in the efficiency analysis literature there has been considerable interest in reconciling SFA and DEA [6]. Two studies that compared SFA and DEA are Chirikos and Sear [7] for US hospitals and Jacobs [2] for hospitals in the UK where both studies found divergent estimations between the results from the two approaches.…”

Section: Introductionmentioning

confidence: 99%

An empirical study of comparing DEA and SFA methods to measure hospital units' efficiency

Katharakis

Katharaki

Katostaras

2014

IJOR

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Frontier techniques have been used to measure healthcare provider efficiency in hundreds of published studies. Although these methods have the potential to be useful to decision makers, their utility is limited by both methodological questions concerning their application. The aim of this paper is to examine the data envelopment analysis (DEA) and stochastic frontier analysis (SFA) results in order to facilitate a common understanding about the adequacy of these methods, defining any differences in healthcare efficiency estimation. A two-stage bootstrap DEA method and the Translog formula of the SFA were performed. Multi-inputs and multi-outputs were used in both of the approaches assuming two scenarios either including environmental variables or not. The introduced environmental variables were regressed with the bias corrected estimations derived from the first step of the two-stage bootstrap DEA model. In the Translog SFA functional form, these variables were introduced as shifted. Thirty-two Greek public hospital units constitute the sample. The main output of the analysis was that the efficiency scores increased with the incorporation of environmental variables in the SFA model, with the average efficiency score to become from 0.85 to 0.89. However, DEA and SFA were found to yield divergent efficiency estimates due to many factors such as the nature of the environmental variables, the measurement error and other random factors. Environmental variables being hospital status and geographical position were found significantly correlating with inefficiency, while patient mobility was not found strongly correlating. The analysis concludes that there is a need for careful attention by stakeholders since the nature of the data and its availability influence the measurement of the efficiency and thus it is necessary to be specific when choosing the appropriate mathematical form in order to test the behavior which generates the data.

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Section: Introductionmentioning

confidence: 99%

An empirical study of comparing DEA and SFA methods to measure hospital units' efficiency

Katharakis

Katharaki

Katostaras

2014

IJOR

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“…In the absence of clinical outcome measures, patient satisfaction is often used as a proxy for both care quality and operational effectivenessVin addition to being an important measure in its own right (Salinas-Jiménez & Smith, 1996). Furthermore, empirical work has shown a positive relationship between hospital efficiency and performance measures (Mutter, Rosko, Greene, & Wilson, 2011;Nayar, Ozcan, Yu, & Nguyen, 2013;. However, it is unclear if managers have the wherewithal to influence care processes that link patient satisfaction and efficiency vis-(-vis other direct care professionals.…”

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confidence: 99%

Measuring Patient Satisfaction’s Relationship to Hospital Cost Efficiency

Huerta

Harle

Ford

et al. 2016

Health Care Management Review

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“…Sherman () provides an early application to hospital productivity and Mutter et al . (), a recent example, but there have been applications to physician practices as well (Andes et al ., ).…”

Section: Data Envelopment Analysismentioning

confidence: 99%

Can Data Envelopment Analysis Provide a Scalar Index of ‘Value’?

et al. 2013

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The concept of 'value' typically includes a combination of cost and quality measures. Some approaches to incorporating value into payment systems treat cost and quality as separate dimensions, but policymakers have expressed interest in a single scalar index that combines cost and quality. Treating risk-adjusted cost as an input and multiple measures of quality as outputs, we examine whether data envelopment analysis input efficiency is associated with higher quality and lower cost in a sample of physician practices using 2008 US Medicare claims data from Colorado. The findings suggest that input efficiency might provide a useful scalar measure of value for a value-based payment system for physician services.

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Translating Frontiers Into Practice: Taking the Next Steps Toward Improving Hospital Efficiency

Cited by 27 publications

References 52 publications

An empirical study of comparing DEA and SFA methods to measure hospital units' efficiency

An empirical study of comparing DEA and SFA methods to measure hospital units' efficiency

Measuring Patient Satisfaction’s Relationship to Hospital Cost Efficiency

Can Data Envelopment Analysis Provide a Scalar Index of ‘Value’?

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