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Application of a Gray-Based Decision Support Framework for Location Selection of a Temporary Hospital during COVID-19 Pandemic

Authors

Hashemkhani Zolfani, Sarfaraz , YAZDANI, MORTEZA, Ebadi Torkayesh, Ali , Derakhti, Arman

External publication

No

Means

Symmetry

Scope

Article

Nature

Científica

JCR Quartile

SJR Quartile

JCR Impact

2.713

SJR Impact

0.385

Publication date

01/06/2020

ISI

000550810700001

Scopus Id

2-s2.0-85087441470

Abstract

The hospital location selection problem is one of the most important decisions in the healthcare sector in big cities due to population growth and the possibility of a high number of daily referred patients. A poor location selection process can lead to many issues for the health workforce and patients, and it can result in many unnecessary costs for the healthcare systems. The COVID-19 outbreak had a noticeable effect on people's lives and the service quality of hospitals during recent months. The hospital location selection problem for infected patients with COVID-19 turned out to be one of the most significant and complicated decisions with many uncertain involved parameters for healthcare sectors in countries with high cases. In this study, a gray-based decision support framework using criteria importance through inter-criteria correlation (CRITIC) and combined compromise solution (CoCoSo) methods is proposed for location selection of a temporary hospital for COVID-19 patients. A case study is performed for Istanbul using the proposed decision-making framework.

Keywords

COVID-19; criteria importance through inter-criteria correlation (CRITIC); combined compromise solution (CoCoSo); gray values; temporary hospital; location selection