Intuitionistic Fuzzy Multi-Criteria Hybrid Approach for Prioritizing Seasonal Respiratory Diseases Patients Within the Public Emergency Departments

When several patients with Seasonal Respiratory Diseases (SRDs) arrive at Emergency Departments (EDs) and healthcare resources are scarce, physicians need to decide which patients to hospitalize. Several conflicting criteria can be used for this decision. Moreover, medical judgments may vary significantly from one doctor to another, based on their perceptions and backgrounds. Considering the above-mentioned context, this study aimed to develop a Multi-criteria Decision-Making (MCDM) model for measuring the risk of unfavorable health evolution —Risk Priority Index (RPI) in each SRD patient and determine the best discharge/treatment option accordingly. Our model is composed of three methods: Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP), Intuitionistic Fuzzy Decision-Making Trial and Evaluation Laboratory (IF-DEMATEL), and Combined Compromise Solution (CoCoSo). A case study of Covid-19 patients in a public Mexican hospital was presented to validate the proposed approach. This investigation has proposed a hybrid MCDM framework that is advantageous over the others proposed in the literature as it incorporates 1) uncertainty, 2) vagueness, 3) experts’ hesitancy, 4) interdependence assessment, 5) short- and long-term interventions, 6) RPI and risk levels, and 7) specific intervention pathways for patients. The results demonstrated that Covid-19 symptoms (global weight = 20.9%) and comorbidities (global weight = 20.7%) were the most important factors in prioritizing infected patients within the EDs, while managing symptomatology played a key role in defining the patient pathway in the healthcare system (D+RT = 15.792).