Measuring hospital efficiency with frontier cost functions

Ownership and Changes in Hospital Inefficiency, 1986–1991

“…For these hospitals, assuming an objective of maximizing the utility associated with a certain set of services or activities, subject to a profit constraint, is more appropriate than assuming an objective of maximizing profit (Hoerger 1991). And, as noted previously, empirical studies generally have found that levels of hospital inefficiency differ according to ownership status (Ozcan and Luke 1993;Zuckerman, Hadley, and Iezzoni 1994).…”

“…Ozcan and Luke (1993) concluded that government hospitals were more technically efficient than private not-for-profit hospitals; they also found that for-profit hospitals were less technically efficient than private not-forprofit hospitals. Zuckerman, Hadley, and Iezzoni (1994) found that for-profit hospitals had the highest mean inefficiency, with government hospitals having the next highest and not-forprofit hospitals having the lowest mean inefficiency. The studies thus agree that the level of inefficiency of for-profit hospitals has been higher than that of other hospital types, but their conclusions vary about differences in the level of inefficiency between government and private not-for-profit hospitals.…”

“…Previous studies of hospital inefficiency in a given year have found that, on average, hospitals have not used the best-practice combination of inputs to produce a given level of output, with mean hospital inefficiency typically falling in the 12% to 15% range (Grosskopf and Valdmanis 1987;Ozcan and Luke 1993;Zuckerman, Hadley, and Iezzoni 1994).…”

“…For example, Grosskopf and Valdmanis (1987) and Ozcan and Luke (1993) used data envelopment analysis, a linear programming approach that assumes a deterministic production function. Other studies of hospital efficiency, including Zuckerman, Hadley, and Iezzoni (1994), Hadley, Zuckerman, and Iezzoni (1996), Chirikos (1998/99), and Rosko (2001), used the stochastic frontier approach, which assumes that the cost function for each hospital is affected both by stochastic factors, over which the hospital has no control, and by errors in the hospital's choices that lead to inefficiency. The cost function thus includes two error termsone to measure random error and one to measure inefficiency.…”

Assessing the Queuing Process Using Data Envelopment Analysis: an Application in Health Centres

“…Table 1 shows the most commonly used inputs and outputs in previous DEA studies when comparing hospitals. Number of Outpatient visits (Bwana 2015 ;Flokou et al, 2011;Masiye et al, 2006 ;Ramanathan 2005;Zuckerman et al, 1994) Number of beds (Bwana 2015;Kose et al, 2014, Al-Shammari 1999Akazili et al, 2008;Harrison et al, 2004;Puig-Junoy 2000;Weng et al, 2009;Magnussen 1996) Number of Inpatient visits (Chuang et al, 2011;Butler and Li 2005;Tsai and Molinero 2002;Zere et al, 2001;Banker et al, 1986 ;Kawaguchi et al, 2014) Number of doctors (Grosskopf and Valdmanis 1987;Kirigia et al, 2008;Chang et al, 2004;Huang et al, 1989;Prior 2006;Kose et al, 2014;Dotoli et al, 2015) Number of major and minor surgeries (Al-Shammari 1999;Chang et al, 2004 ;Puig-Junoy 2000 ;Gerdtham et al, 1999 ;Dotoli et al, 2015) Number of nurses (Chuang et al, 2011;Masiye et al, 2006;Hollingsworth and Parkin 1997;Byrnes and Valdmanis 1993;Kawaguchi et al, 2014) Number of emergency visits (Butler andLi 2005 Grosskopf andValdmanis 1987;<...>…”