The Development and Evaluation of Hospital Performance Measures for Policy Analysis

Ehreth, Jenifer

doi:10.1097/00005650-199406000-00003

Cited by 48 publications

(23 citation statements)

References 16 publications

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“…number of treated cases, number of nurses and/or doctors taught) requires a decrease in at least one other output, or an increase in at least one input. The relevance of ef®ciency measurement in the hospital sector was highlighted in a recent empirical study, where it was found that ef®ciency was the most dominant dimension of hospital performance (Ehreth, 1994;p. 584).…”

Section: General Frameworkmentioning

confidence: 99%

On the efficiency of public, welfare and private hospitals in Germany over time: a sectoral data envelopment analysis study

Helmig

Lapsley

2001

Health Serv Manage Res

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This paper examines the efficiency of the German hospital sector over time and the relative efficiency of public, welfare (both nonprofit) and private (for-profit) hospital sectors using data from the Federal Statistics Office of German hospitals. Efficiency scores were computed using data envelopment analysis. The absolute efficiency of the hospital sector as a whole was found to have improved between 1991 and 1996. In this comparison, the empirical results showed that the hospitals in the public and welfare sector are relatively more efficient than private hospitals. Our results suggest that public, welfare and private hospital sectors have different best-practice frontiers; and that public and welfare hospital sectors appear to use relatively fewer resources than private hospitals. These results suggest differences in quality of care arising from ownership.

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Section: General Frameworkmentioning

confidence: 99%

On the efficiency of public, welfare and private hospitals in Germany over time: a sectoral data envelopment analysis study

Helmig

Lapsley

2001

Health Serv Manage Res

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“…Putting an increased emphasis on targeted investments in health, it is essential to ensure complementarity of efficient activities of hospital clinics and also other health care settings. With this particular view, DEA methodology has been used to measure efficiency in hospitals [4,8,30,34,[36][37][38][39][42][43][44][45][46][47][48][49][50][53][54][55][56][57][58][59][60]64,65,[75][76][77][78][79][80][81][82][83][84][85][86], in health care systems [5,6,32,33,35,41,63,66,68], in primary care [7], in clinical...…”

Section: Discussionmentioning

confidence: 99%

Efficiency Assessment across Homogeneous Specialty Clinics in the Region of Thessaly, Greece

Geitona¹

2013

TOPHJ

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Abstract:Background: Hospital care expenditure is the most significant cost driver in the health care sector. Reductions in public hospitals' expenses are among the principal austerity measures included in the memorandum recommendations. However, health policy decision-making seems to be a political rather than a technical issue.Objective: The aim of this paper is to assess performance by using Data Envelopment Analysis(DEA) among homogeneous specialties in the General Medicine(GM) and surgical clinics, across all hospitals operating in the Regional Health Authority of Thessaly(RHAT), over the period of [2002][2003][2004][2005][2006].Methods: Two output-oriented DEA models have been adapted, separated in homogeneous GM and surgical clinics, for both constant(CRS) and variable returns to scale(VRS). The unit of analysis is the clinic. A total of 175 decision-making units(DMUs) have been composed. The number of inpatients and inpatient days are considered as outputs whereas the number of the personnel employed and beds as labour and capital inputs respectively.Results: Highest efficiency scores overtime were achieved by the GM clinics of the University District Hospital of Larissa. In surgical specialties, the ophthalmology clinic of the general hospital(GH) of Larissa and the urology of GH of Karditsa achieved the highest efficiency scores. Inefficiencies among GM and surgical clinics per year were also found. Both homogeneous groups followed similar trends in the curves. Five GM and ten surgical DMUs under both VRS and CRS remained fully efficient. Conclusions:The economic crisis Greece is facing, necessitates the assessment of National Health System(NHS) hospitals' performance in order to support health policy decision-making and resources allocation.

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“…In health care literature, Dea has been used to analyse efficiency in hospitals and nursing home industries. among previous applications of Dea with hospital data are studies by Banker et al (1986), Chang (1998), Chattopadhy and Ray (1996), ehreth (1994), ersoy et al (1997, giuffrida and gravelle (2001), grosskoff and Valdmanis (1987), Hollingsworth and Parkin (2001), Jacobs (2001), Kirigia et al (2002), Linna et al (2002), Morey et al (1992), Salinas-Jimenez and Smith (1996), Sherman (1984), Shroff et al 1998,Wan et al (2002, White et al (1996) and Zavras et al (2002). The original Dea model, proposed by Charnes et al (1978) and referred to as the CCR model in literature, assumes a production technology with constant returns to scales.…”

Section: Data Envelopment Analysismentioning

confidence: 99%

Technical Efficiency and Scale Efficiency of District Hospitals

Dash

Vaishnavi

Muraleedharan

2010

Journal of Health Management

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The Government of Tamil Nadu state in India has been implementing various health sector reforms (for example, expansion and upgradation of public health facilities, provision of round the clock services in selected primary health centres and continuous availability of quality medicines decentralisation) in a bid to improve efficiency in health care. However, few attempts have been made to make an estimate of the efficiency of hospitals in Tamil Nadu as well as in India till date. The objectives of this study are: (i) to estimate the relative technical efficiency (TE) and scale efficiency (SE) of a sample of public hospitals in Tamil Nadu; and (ii) to demonstrate policy implications for health sector policy makers. The Data Envelopment Analysis (DEA) approach, a well-known operations research (OR) technique for evaluating the relative efficiency of a set of similar decision making units (DMU), was used to estimate the efficiency of these hospitals. To do so we made use of the data collected from the Directorate of Medical and Rural Health Services (DMRHS) for 29 districts of TamilNadu in 2004-05. The output data included are outpatient visits, number of inpatients, number of surgeries undertaken, number of deliveries and number of emergency cases. The numbers of staff members and bed strength were used as input. Of the 29 hospitals, it was found that 52 per cent were technically efficient as they had relative efficiency score 1.00 and lie on the efficiency frontier, while the remaining 48 per cent were technically inefficient and can use some of the efficient hospitals as their peers to improve their efficiency. Further, the average scale efficiency among the inefficient hospitals was 81 per cent, which implies that the scale inefficient hospitals could reduce their size by 19 per cent without reducing their current output levels.

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The Development and Evaluation of Hospital Performance Measures for Policy Analysis

Cited by 48 publications

References 16 publications

On the efficiency of public, welfare and private hospitals in Germany over time: a sectoral data envelopment analysis study

On the efficiency of public, welfare and private hospitals in Germany over time: a sectoral data envelopment analysis study

Efficiency Assessment across Homogeneous Specialty Clinics in the Region of Thessaly, Greece

Technical Efficiency and Scale Efficiency of District Hospitals

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