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

Abstract

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.

Discrete-Event Simulation Model for Monitoring Elderly and Patient’s Smart Beds

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Application of fuzzy TOPSIS for prioritization of patients on elective surgeries waiting list - A novel multi-criteria decision-making approach

“…In the recent literature, TOPSIS and Fuzzy TOPSIS have been used in numerous fields such as assessment of energy systems (Taylan et al, 2020), maintenance management (Olugu et al, 2021), occupational accident (Abbasinia & Mohammadfam, 2022), petrochemical industry (Abbassinia et al, 2020), noise control (Mousavi et al, 2019), outsourcing (Kiani et al, 2022), reverse logistics (Naseem et al, 2021), manufacturing systems (Mathew et al, 2020) and renewable energy (Solangi et al, 2019). Usage of TOPSIS can be found in healthcare literature for analysis of dose planning (Malekpoor et al, 2022), hospital waste management (Baghapour et al, 2018), medical device risk factors (Kirkire et al, 2018), triage in intensive care unit (Davodabadi et al, 2021), human errors factors in the emergency departments (Hsieh et al, 2018), mobile health (Rajak & Shaw, 2019), medical diagnosis (Baccour, 2018), and nano material selection (K. Zhang et al, 2019).…”

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