Using data envelopment analysis to measure the extent of technical efficiency of public health centres in Ghana

Akazili, James; Adjuik, Martin; Jehu-Appiah, Caroline; Zere, Eyob

doi:10.1186/1472-698x-8-11

Cited by 93 publications

(103 citation statements)

References 20 publications

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“…The curves were denominated "frontiers of observed quality" and considered as excellent the quality observed in municipalities represented by points on the frontier and considered other municipalities as ineffi cient. The algorithm calculated the distance from each point to the frontier of observed quality, and associated a measure that was inversely proportional to the distance for each point, in order to obtain a monotonic and increasing measure for quality over the interval [0,1]. The same principal was assumed in the aggregation of measures of relevance and effectiveness to generate the measure of value, as well as in the aggregation of measures of effi cacy and effi ciency to generate the measure of merit.…”

Section: Methodsmentioning

confidence: 99%

Indicador sintético para avaliar a qualidade da gestão municipal da atenção básica à saúde

Scaratti¹,

Calvo²

2012

Rev. Saúde Pública

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OBJECTIVE:To develop a composite indicator to evaluate the quality of municipal management of primary health care. METHODS:The evaluation model focuses on aspects of health system management. Fifty-fi ve performance indicators were used and classifi ed according to the criteria of relevance, effectiveness, effi cacy and effi ciency. The measures were aggregated through an additive data envelopment analysis model for measures of value, merit and quality. Data was utilized from 36 municipalities in Santa Catarina State (Southern Brazil), with populations between 10 thousand and 50 thousand residents in 2006. RESULTS:The results are presented as monotonic measures over the interval [0, 1] (score = 1: effi cient; other values: ineffi cient). Five municipalities had a score of 1 in the quality of management for actions promoting access, while eight municipalities received a score of 1 in the quality of management of actions for service provision; the other municipalities were classifi ed as ineffi cient (score < 1) for both dimensions. CONCLUSIONS:The quality of municipal management in primary health care can be evaluated with a composite indicator, constructed through linear programming techniques, which simultaneously considers the criteria of relevance, effectiveness, effi cacy and effi ciency and expresses them as measures of value, merit and quality.

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Section: Methodsmentioning

confidence: 99%

Indicador sintético para avaliar a qualidade da gestão municipal da atenção básica à saúde

Scaratti¹,

Calvo²

2012

Rev. Saúde Pública

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“…According to Akazili, et al (2008), DEA is an essential method for evaluating the efficiency of health systems. The strategic and operational aspects of resource management can be evaluated by DEA (Akazili, et al, 2008).…”

Section: Application Of Dea In Healthcarementioning

confidence: 99%

“…The strategic and operational aspects of resource management can be evaluated by DEA (Akazili, et al, 2008). Kirigia and Boussofiane said that DEA enables to measure the efficiency of operational strategies in the health sector.…”

Section: Application Of Dea In Healthcarementioning

confidence: 99%

The Application of Data Envelopment Analysis in Healthcare Performance Evaluation of Rehabilitation Departments in Hungary

Dénes

Kecskés²,

Koltai

et al. 2017

QIP Journal

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Purpose: Performance evaluation is a general problem both in production and service systems. Generally, operation performance is determined based on input resource utilization and on outputs related data. Performance evaluation is especially complicated when both financial and nonfinancial indicators must be considered in the evaluation of the efficiency of healthcare system. The purpose of this paper is to apply data envelopment analysis (DEA) in order to measure the efficiency of rehabilitation departments curing musculoskeletal diseases. Methodology/Approach:The evaluation of the efficiency of rehabilitation departments includes several parameters. Performance evaluation becomes complicated when several evaluation criteria must be taken into consideration at the same time. In these cases, scoring methods are generally used, which transform performance data into a common scale and an aggregate score is calculated with subjective weights. Using DEA the subjective element of evaluation is eliminated when the weights of inputs and outputs are determined.Findings: The applied DEA model evaluates the performance of rehabilitation departments. The presented analysis highlights the differences between the efficiency of the studied departments, and explores inefficiencies related to economies of scale. The slack values directly show the operational shortcomings in specific areas, and indicate the exact amount of the required changes.Research Limitation/implication: The applied DEA model evaluates the performance of rehabilitation departments. The presented analysis highlights the differences between the efficiency of the studied departments, and explores inefficiencies related to economies of scale. The slack values directly show the operational shortcomings in specific areas, and indicate the exact amount of the required changes. 128 Originality/Value of paper: The originality of the paper lies on the identification of inputs and outputs for the applied DEA model as only nonfinancial indicators were taken into consideration. The analysis involves all rehabilitation departments of the Hungarian healthcare system; consequently, conclusions related to the general state of this area can be drawn.

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“…Liu et al (2013) provide a detailed survey of DEA applications in various fields. Among various healthcare applications, DEA has been mostly applied to the efficiency comparison of hospitals (Nunamaker 1983;Parkin and Hollingsworth, 1997;Ouellette and Vierstraete, 2004;Akazili et al, 2008;Flokou et al, 2011;Kawaguchi et al, 2014).…”

Section: Main Aim and Objectives Of The Current Studymentioning

confidence: 99%

“…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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Using data envelopment analysis to measure the extent of technical efficiency of public health centres in Ghana

Cited by 93 publications

References 20 publications

Indicador sintético para avaliar a qualidade da gestão municipal da atenção básica à saúde

Indicador sintético para avaliar a qualidade da gestão municipal da atenção básica à saúde

The Application of Data Envelopment Analysis in Healthcare Performance Evaluation of Rehabilitation Departments in Hungary

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

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