Assessment for hierarchical medical policy proposals using hesitant fuzzy linguistic analytic network process

Abstract The aim of assessing the hierarchical medical policy proposals is to select the optimal one from possible alternatives so that it can better strengthen the policy development. After clarifying the research objectives, issues and method of this study, a new evaluation indicator system for HMP proposals is established from the perspective of stakeholders in the medical system by taking the length of observation time into consideration. Then, three HMP proposals are determined by analyzing the existing studies, which play the role of possible alternatives. Furthermore, we derive the initial weights of control criteria and sub-criteria based on multiplicative consistency of the hesitant fuzzy linguistic preference relation, and develop the decision matrix by combining the subjective and objective information together. In order to derive the comprehensive weights of control criteria, we construct a supermatrix and develop the hesitant fuzzy linguistic analytic network process. A numerical example is presented to illustrate the application of the evaluation indicator system and the HFL-ANP method. Some discussions of results and a comparative analysis are provided.

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