Developing a Novel Integrated Generalised Data Envelopment Analysis (DEA) to Evaluate Hospitals Providing Stroke Care Services

Stroke is the biggest cause of adult disability and the third biggest cause of death in the US. Stroke is a medical emergency, and the treatment given in the early hours is important in shaping the patient’s long-term recovery and prognosis. Despite the fact that substantial attention has been dedic...

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Vydáno v:Bioengineering (Basel) Ročník 8; číslo 12; s. 207
Hlavní autoři: Mirmozaffari, Mirpouya, Shadkam, Elham, Khalili, Seyed Mohammad, Yazdani, Maziar
Médium: Journal Article
Jazyk:angličtina
Vydáno: Switzerland MDPI AG 10.12.2021
MDPI
Témata:
Bioengineering
Case studies
Costs
Data analysis
Data envelopment analysis
Decision making
Efficiency
Emergency medical services
generalised data envelopment analysis
health
Hospitals
interactive approach
Linear programming
Methods
Multiple objective analysis
multiple objective linear programming
Performance evaluation
Preferences
Simulation
stem method
Stroke
United States > US
interactive approach
multiple objective linear programming
stem method
health
hospital
generalised data envelopment analysis
stroke
ISSN:2306-5354, 2306-5354
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Shrnutí:Stroke is the biggest cause of adult disability and the third biggest cause of death in the US. Stroke is a medical emergency, and the treatment given in the early hours is important in shaping the patient’s long-term recovery and prognosis. Despite the fact that substantial attention has been dedicated to this complex and difficult issue in healthcare, novel strategies such as operation research-based approaches have hardly been used to deal with the difficult challenges associated with stroke. This study proposes a novel approach with data envelopment analysis (DEA) and multi-objective linear programming (MOLP) in hospitals that provide stroke care services to select the most efficient approach, which will be a new experiment in literature perception. DEA and MOLP are widely used for performance evaluation and efficiency measurement. Despite their similarities and common concepts, the two disciplines have evolved separately. The generalised DEA (GDEA) cannot incorporate the preferences of decision-makers (DMs) preferences and historical efficiency data. In contrast, MOLP can incorporate the DM’s preferences into the decision-making process. We transform the GDEA model into MOLP through the max-ordering approach to (i) solve the problem interactively; (ii) use the step method (STEM) and consider DM’s preferences; (iii) eliminate the need for predetermined preference information; and (iv) apply the most preferred solution (MPS) to identify the most efficient approach. A case study of hospitals that provide stroke care services is taken as an example to illustrate the potential application of the proposed approach method.
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ISSN:2306-5354
2306-5354
DOI:10.3390/bioengineering8120207