Smart medical device selection based on intuitionistic fuzzy Choquet integral

Abstract

This paper presents a novel approach for evaluating the smart medical device selection process in a group decision-making setting in an uncertain decision environment. Intuitionistic fuzzy Choquet integral (IFCI) approach is applied to treat the uncertainty and vagueness in the decision-making process. IFCI also considers the interactions among the decision criteria in the data provided by the decision makers. In this paper, the emphasis is placed upon the selection of wearable monitoring devices for cardiac patients. The goal is to present the complexity of the problem, raise interest among specialists in the healthcare industry and assess smart medical devices under different evaluation criteria. The problem is formulated as a multi-criteria decision model with ten criteria and eight alternatives. The results of the IFCI model are analyzed using 9 sensitivity analysis scenarios, which prove the adequacy of the obtained results. The result of the proposed method is also compared with the IF extensions of the VIKOR, TOPSIS, COPRAS, MOORA and MULTIMOORA models in order to validate and verify the obtained outcome. The Spearman coefficient of correlation is applied to check the stability of the variations in the rankings. The results indicate that the model and the rankings it generates are sufficiently stable.