A Performance Assessment Method for Hospitals: The Case of Municipal Hospitals in Angola

Kirigia, Joses Muthuri; Emrouznejad, Ali; Cassoma, Basilio; Asbu, Eyob Zere; Barry, Saidou

doi:10.1007/s10916-008-9157-5

Cited by 87 publications

(65 citation statements)

References 21 publications

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“…Studies conducted by Ismail on 15 health service providers in Sudan in 2007, 13 Zere on 86 hospitals in South Africa in 2000, 10 Kirigia et al on 28 public hospitals in Angola in 2002, 14 Akazili et al on 89 health care centers in Ghana in 2008, 15 Marschall and Flessa on 20 health service providers in rural areas in Burkina Faso in 2011, 16 Moga et al on 50 private hospitals in India in 2014, 17 and Barouni et al 18 on 8 hospitals affiliated with the Qom University of Medical Sciences in 2015 used DEA to evaluate the efficiency of hospitals and health service providers. DEA is a non-parametric method based on linear programming that estimates the frontier production function, which is the maximum possible production obtained from specific production factors.…”

Section: Do Hospitals Affiliated With the Kurdistan University Of Medmentioning

confidence: 99%

Do Hospitals Affiliated With the Kurdistan University of Medical Sciences Perform Efficiently? Non-parametric Data Envelopment Analysis

et al. 2016

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Background: One way to improve the performance of hospitals, the largest resource-consuming units in the healthcare sector, is to continuously evaluate their performance. Objective: The current study assessed the performance of hospitals affiliated with the Kurdistan University of Medical Sciences using data envelopment analysis (DEA). Methods: This retrospective descriptive-analytic study used DEA to assess efficiency types (technical, managerial, and scale) in hospitals of the Kurdistan University of Medical Sciences (n = 12) in the years 2007 to 2011. The number of active beds, nurses, physicians (general and specialist), and other staff were inputs; inpatient admission and occupied bed days were outputs. Stata version 12 was used for data analysis. Results: The mean technical, scale, and managerial efficiency values were 0.85, 0.89, and 0.95, respectively. The highest and lowest slack inputs were nurses and active beds, respectively. Conclusion:The findings indicate that Kurdistan hospitals were less than appropriately efficient during the studied period. They also suggest that there is a capacity of about 15% for enhancing output in hospitals (compared with the most efficient studied hospitals) without increasing costs or inputs.

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Section: Do Hospitals Affiliated With the Kurdistan University Of Medmentioning

confidence: 99%

Do Hospitals Affiliated With the Kurdistan University of Medical Sciences Perform Efficiently? Non-parametric Data Envelopment Analysis

et al. 2016

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“…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;<...>…”

Section: Selection Of Input and Output Variables In The Dea Modelmentioning

confidence: 99%

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

2015

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Queuing is one of the very important criteria for assessing the performance and efficiency of any service industry, including healthcare. Data Envelopment Analysis (DEA) is one of the most widelyused techniques for performance measurement in healthcare. However, no queue management application has been reported in the health-related DEA literature. Most of the studies regarding patient flow systems had the objective of improving an already existing Appointment System. The current study presents a novel application of DEA for assessing the queuing process at an Outpatients' department of a large public hospital in a developing country where appointment systems do not exist.The main aim of the current study is to demonstrate the usefulness of DEA modelling in the evaluation of a queue system. The patient flow pathway considered for this study consists of two stages; consultation with a doctor and pharmacy. The DEA results indicated that waiting times and other related queuing variables included need considerable minimisation at both stages.

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“…In Asia, DEA was used to examined hospital's efficiency by Pharm (2010) measuring the efficiency of hospitals in Vietnam. In Africa DEA was also used to examine hospitals efficiency, among few hospitals studies conducted include; Kirigia et al (2008) measured the efficiency of hospitals in Angola; Osei et al (2005) examined efficiency of district hospitals in Ghana; Zere et al (2001) assessed the efficiency of hospitals in South Africa; Bwana (2015) measured technical efficiency of faith based hospitals in Tanzania; Yawe (2010) examined the efficiency of district hospitals in Uganda.…”

Section: Background Of Studies On Hospital Efficiencymentioning

confidence: 99%

Technical Efficiency of Tanzania Teaching Hospitals: The Case of Private not for-profit Hospitals

Bwana

Raphael²

2015

BMS

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In this study, we examined the technical efficiency of private teaching hospitals in Tanzania. We employed a widely used non-parametric approach (Data Envelopment Analysis) in a sample of 18 teaching hospitals. The study period covered 2009 -2013. The result from this study is expected to be useful to the owners and administrators of teaching hospitals, giving them justification for effective planning and implementation of the strategies that will avoid abuse of the available scarce health resources. Government and policy makers may also reap some inputs (from result of this study) for health policies, particularly pertaining to research and the training of future medical experts.Findings revealed that out of 18 teaching hospitals, only 4 (22.3%) are operating close to technical efficiency with average level of technical efficiency ranging between 92% and 98%. The remaining 14 hospitals are operating far from efficiency frontier. Overall mean scale efficiency were found to be 82.4%. With support of DEA this study has revealed inefficiency in the use of scarce health care resources in teaching hospitals in Tanzania. This requires the hospitals administrators and managers to consider steps to be taken to improve inefficiency.

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A Performance Assessment Method for Hospitals: The Case of Municipal Hospitals in Angola

Cited by 87 publications

References 21 publications

Do Hospitals Affiliated With the Kurdistan University of Medical Sciences Perform Efficiently? Non-parametric Data Envelopment Analysis

Do Hospitals Affiliated With the Kurdistan University of Medical Sciences Perform Efficiently? Non-parametric Data Envelopment Analysis

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

Technical Efficiency of Tanzania Teaching Hospitals: The Case of Private not for-profit Hospitals

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