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Prioritization of healthcare systems during pandemics using Cronbach's measure based fuzzy WASPAS approach
Muhammet Deveci1,2, Raghunathan Krishankumar3, Ilgin Gokasar4
1Department of Industrial Engineering, Turkish Naval Academy, National Defence University, 34940 Tuzla, Istanbul, Turkey.
Abstract:
Pandemics are well-known as epidemics that spread globally and cause many illnesses and mortality. Because of globalization, the accelerated occurrence and circulation of new microbes, the infection has emerged and the incidence and movement of new microbes have sped up. Using technological devices to minimize the visit durations, specifying days for handling chronic diseases, subsidy for the staff are the alternatives that can help prevent healthcare systems from collapsing during pandemics. The study aims to define the efficient usage of optimization tools during pandemics to prevent healthcare systems from collapsing. In this study, a new integrated framework with fuzzy information is developed, which attempts to prioritize these alternatives for policymakers. First, rating data are assigned respective fuzzy values using the standard singleton grades. Later, criteria weights are determined by extending Cronbach´s measure to fuzzy context. The measure not only understands data consistency comprehensively, but also takes into consideration the attitudinal characteristics of experts. By this approach, a rational weight vector is obtained for decision-making. Further, an improved Weighted Aggregated Sum Product Assessment (WASPAS) algorithm is put forward for ranking alternatives, which is flexibly considering criteria along with personalized ordering and holistic ordering alternatives. The usefulness of the developed framework is tested with the help of a real case study. Rank values of alternatives when unbiased weights are used is given by 0.741, 0.582, 0.640 with ordering as . The sensitivity/comparative analysis reveals the impact of the proposed model as useful in selecting the best alternative for the healthcare systems during pandemics.
Insights
This study introduces a fuzzy optimization framework to prioritize healthcare system resilience strategies during pandemics. The developed model effectively ranks interventions, aiding policymakers in preventing healthcare collapse.
Area of Science:
- Healthcare Management
- Operations Research
- Public Health
Background:
- Pandemics pose significant global health risks, accelerating the emergence and spread of novel microbes.
- Globalization has increased the frequency and impact of infectious disease outbreaks, straining healthcare systems.
- Effective strategies are crucial to prevent healthcare system collapse during global health crises.
Purpose of the Study:
- To develop and validate an optimization framework for prioritizing interventions aimed at preventing healthcare system collapse during pandemics.
- To integrate fuzzy logic and decision-making tools for robust policy recommendations.
- To provide a systematic approach for policymakers to manage healthcare resources effectively during health emergencies.
Main Methods:
- Development of an integrated fuzzy information framework to assign fuzzy values to rating data.
- Extension of Cronbach's measure to a fuzzy context for determining criteria weights, considering expert characteristics.
- Implementation of an improved Weighted Aggregated Sum Product Assessment (WASPAS) algorithm for ranking alternatives.
- Validation of the framework using a real-world case study and sensitivity analysis.
Main Results:
- The fuzzy framework successfully prioritized healthcare system resilience alternatives.
- The improved WASPAS algorithm provided a rational weight vector for decision-making.
- Sensitivity analysis confirmed the model's utility in selecting optimal strategies for healthcare systems during pandemics.
- Rank values for alternatives with unbiased weights were 0.741, 0.582, and 0.640.
Conclusions:
- The proposed fuzzy optimization framework offers an efficient method for policymakers to prioritize interventions during pandemics.
- The integrated approach enhances decision-making by incorporating expert judgment and uncertainty.
- This study provides a valuable tool for strengthening healthcare system resilience against global health threats.
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