2024 : 6 : 13
Hamidreza Talaie

Hamidreza Talaie

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0002-2532-8702
Education: PhD.
ScopusId: 57200392829
Faculty: Economic and Administrative Sciences
Address: Arak University


A healthcare service quality assessment model using a fuzzy best–worst method with application to hospitals with in-patient services
Multi-Criteria Decision-MakingFuzzy environmentHealthcare service qualityBest–Worst MethodPandemic crisis
Journal Healthcare Analytics
Researchers Ehsan Khanmohammadi ، Hamidreza Talaie ، Maryam Azizi


Hospitals and healthcare centers face many service problems during the pandemic. Problems that may arise in providing high-quality services lead to increased dissatisfaction. The Covid-19 crisis saw an unprecedented rise in the number of visits and hospitalizations in healthcare centers, which led to drastic fluctuations in the quality of services provided by these centers. This study aims to assess the quality of services in hospitals through a fuzzy Best–Worst Method (BWM). This method makes fewer computations and more consistent comparisons than Analytic Hierarchy Process (AHP), the most common method used among Multi-Criteria Decision Making (MCDM) methods. Our proposed fuzzy BWM is an efficient, reliable, easy-to-apply quality assessment technique. To show the applicability of the proposed method, we have investigated the service quality of four hospitals. Accordingly, the factors and sub-factors of the quality of health and medical services were obtained through an in-depth review of the literature. The matrices of pairwise comparisons were then completed based on experts’ opinions, and the weights were extracted from the fuzzy pairwise comparison matrices after solving the model. The results show even the hospitals with the highest score are far from what patients and experts perceive as the quality of service. Based on our results, caring, accuracy, skill, and timeliness are the most important criteria in evaluating healthcare service quality in Iran during the pandemic.