Hospital Performance Evaluation in COVID-19 Pandemic by Using Hesitant Fuzzy MABAC

Abstract

Healthcare service demand during the COVID-19 pandemic has significantly increased compared to the pre-pandemic period. In some cases, it is known that the hospitals are insufficient and the health system were at the point of collapse. In order to provide a better service to patients, it is very important to measure and improve current performance. In this study, intensive care unit’s performance of hospitals under the COVID-19 pandemic was evaluated by using Hesitant Fuzzy MABAC (Multi-Attributive Border Approximation Area Comparison) method. There are different criteria sets in the literature for the evaluation of hospitals. Within the scope of this study; technical competence of the COVID-19 emergency service, patient satisfaction, sufficiency of health personnel, and patient follow-up process criteria were used. Since the comparison was made from the perspective of experts, the ambiguities and hesitations in the evaluations were reflected in ambiguous and fuzzy linguistic terms. In the application section, performance measurement of three hospitals were made. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.