Evaluating the Effectiveness of Healthcare Services by Using the Method of Data Envelopment Analysis

Author(s):  
Vitalina Babenko
2021 ◽  
Vol 13 (3) ◽  
pp. 1337
Author(s):  
Silvia González-de-Julián ◽  
Isabel Barrachina-Martínez ◽  
David Vivas-Consuelo ◽  
Álvaro Bonet-Pla ◽  
Ruth Usó-Talamantes

A data envelopment analysis was used to evaluate the efficiency of 18 primary healthcare centres in a health district of the Valencian Community, Spain. Factor analysis was used as a first step in order to identify the most explanatory variables to be incorporated in the models. Included as variable inputs were the ratios of general practitioners, nurses, and costs; as output variables, those included were consultations, emergencies, avoidable hospitalisations, and prescription efficiency; as exogenous variables, those included were the percentage of population over 65 and a multimorbidity index. Confidence intervals were calculated using bootstrapping to correct possible biases. Efficient organisations within the set were identified, although the results depend on the models used and the introduction of exogenous variables. Pharmaceutical expenditure showed the greatest slack and room for improvement in its management. Data envelopment analysis allows an evaluation of efficiency that is focussed on achieving better results and a proper distribution and use of healthcare resources, although it needs the desired goals of the healthcare managers to be clearly identified, as the perspective of the analysis influences the results, as does including variables that measure the achievements and outcomes of the healthcare services.


2016 ◽  
Vol 33 (2) ◽  
pp. 284-294 ◽  
Author(s):  
Çağlar Sezgin Aksezer

Purpose – Reliability evaluation of healthcare services has been a challenging task for both operations managers and system engineers working in the respective field. The purpose of this paper is to develop a data envelopment analysis-based reliability allocation model. Design/methodology/approach – A two-phase optimization scheme for the reliability evaluation and allocation of homogeneous system entities, namely, hospitals, operating in a healthcare network is proposed. First, reliability evaluation is performed nonparametrically through the frontier estimation technique data envelopment analysis by considering several failure modes and failure free discharged patients as the inputs and output of the service system. Subsequently, optimal reliability allocation that maximizes the overall network reliability subject to a budget constraint is carried out by utilizing weights of the inputs and output calculated on the Pareto optimal frontier, which is constructed from the most reliable hospitals operating in the network. Findings – The popular performance assessment methodology DEA is found to be an invaluable reliability assessment and allocation tool, where optimal weights of the associated envelopment model, under certain budget restrictions, are used to maximize overall network reliability. Originality/value – An empirical illustration of the proposed model is presented on a set of hospital network data from Turkey. Modeling implications can be carried out on similar service operations where identification of the critical performance indicator costs is possible.


2019 ◽  
Vol 21 (2) ◽  
pp. 279-293
Author(s):  
Asmita Chitnis ◽  
Dharmesh K. Mishra

India is expected to be ranked among the top three healthcare markets in terms of growth by 2020. The scale and scope for delivery of quality healthcare services demand high levels of service performance to provide effective and efficient services to patients. The purpose of this study is to assess the performance efficiency of Indian private hospitals using data envelopment analysis (DEA) and super-efficiency DEA. The analysis uses an output-oriented approach with a mix of four inputs and one output variables to identify the most efficient hospitals. In the first stage, a sample of 25 private hospitals is evaluated using DEA, and in the second stage, the same sample is analysed using super-efficiency DEA for discriminating the performance of the efficient hospitals. The results show seven hospitals as the most efficient ones using DEA in the first stage. Fortis Hospital Ltd emerges as the super-efficient hospital using super-efficiency DEA analysis in the second stage. The results obtained have managerial implications and provide the decision maker (DM) the requisite guidance for corrective actions.


1997 ◽  
Vol 48 (3) ◽  
pp. 332-333 ◽  
Author(s):  
A Charnes ◽  
W Cooper ◽  
A Y Lewin ◽  
L M Seiford

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