A multi-criteria framework for addressing digitalization solutions of medical system under interval-valued T-spherical fuzzy information

Abstract

With the help of Internet technology, digital reform of the medical system has gradually sprung up and begun to reconstruct the medical and health industry chain and service model, which has brought great change to the medical industry. At present, there are many digitalization solutions of medical system on the market. However, there are many differences in the technical standards, functions, prices and service objects of these solutions, and the objective environment is uncertain. At the same time, decision-makers often have subjective uncertainty when making choices. Therefore, it is difficult for decision-makers to choose the most satisfactory one from many digitalization solutions. To solve these problems, this study proposes the IVT-SFS weighted Muirhead mean (IVTSFWMM) operator, and establishes the evaluation and decision-making method of digitalization solutions of medical system based on this operator. Then we apply this method to cases and select the best performing solution from the four existing digitalization solutions of medical system in the market to prove the effectiveness of the method. The advantage of the method proposed in this study is that it can express subjective uncertainty when the decision-maker gives the evaluation information in the form of interval-valued fuzzy numbers, and the interaction between any number of indicators can be considered when aggregating indicators. The results show that the method proposed in this paper can effectively express the fuzzy evaluation information in complex environments, and provide suggestions for system designers to provide decision support for the evaluation and selection of intelligent medical solutions.