Prioritization of Patients in ICU: Composite Approach of Multiple-Criteria Decision-Making and Discrete Event Simulation

• Published in: Brazilian journal of operations & production management Vol. 18; no. 1; pp. 1 - 21
• Main Authors: Davodabadi, Afsaneh, Daneshian, Behrooz, Saati, Saber, Razavyan, Shabnam
• Format: Journal Article
• Language: English
• Published: Associação Brasileira de Engenharia de Produção (ABEPRO) 01.01.2021
• Subjects: Discrete Event Simulation; Fuzzy ANP; Fuzzy set theory; Fuzzy TOPSIS; Hospital equipment allocation
• DOI: 10.14488/BJOPM.2021.008
• ISSN: 2237-8960

Goal: This article aims to present a systematic approach to improve the resource allocation and human queues prioritization patterns. Design / Methodology / Approach: To achieve such a purpose, effective criteria using a fuzzy-Delphi method, and subject-related researchers’ views were obtained. Utilizing the Analytic Network Process method, the weights of each criterion was measured. Then, considering the established weights and using a fuzzy-TOPSIS method, a prioritization system via Discrete Event Simulation was developed. Results: Results indicate that the established approach properly improved the performance of the prioritization system in terms of resources and facilities allocation in neurology’s ICUs. Limitations of the investigation: A drawback of this research can be in states of emergency which limits the options at hand and the criteria proposed may set a drawback on the aim of the study. Practical implications: The results show that the proposed model can modify patient entry based on multiple criteria in terms of productivity and social justice in the patient queuing strategy. Originality / Value: The contribution of this research is threefold: the literature has been reviewed to conclude the criteria concerning decisions around ICUs, the concluded criteria filtered through an expert panel which can be relied based on the method, a real application of the steps proposed is presented which allows comparing the accuracy and efficiency of the decisions made in the hospitals.