Performance evaluation for medical alliance in China based on a novel multi-attribute group decision-making technique with Archimedean copulas-based Hamy operators and extended best-worst method

Abstract

Background: Medical alliance plays an important role in promoting resource sharing, optimizing the allocation of medical resources, establishing a hierarchical diagnosis and treatment system featuring primary diagnosis at the grassroots level, a two-way referral system, separated treatment for acute and chronic diseases, and dynamic cooperation. Thus, comprehensive performance evaluation for medical alliance is a necessary research that involves a multi-attribute group decision-making problem.

Objective: The aim of this paper is to develop a new multi-attribute group decision-making evaluation framework and new weight method to better efficaciously resolve the issues of evaluation for the medical alliance.

Methods: Firstly, Archimedean copula and co-copula operational rules, called Archimedean co-copula, and the form of q-rung orthopair fuzzy Hamy mean aggregation operator based on Archimedean co-copula operational rules are also developed. Secondly, an extended q-rung orthopair fuzzy extended best-worst method satisfying multiplicative consistency is developed to originate the weight information of the attributes. The new weight method can integrate the membership and non-membership of assessment information, improve constancy for group decision making and get an extremely reliable weight consequence. Finally, a novel multi-attribute group decision-making framework is presented based on the proposed q-rung orthopair fuzzy Archimedean copula and co-copula Hamy mean aggregation operator and q-rung orthopair fuzzy Euclidean best-worst method. Furthermore, the new multi-attribute group decision-making method is applied to comprehensive performance evaluation for medical alliance in Shanghai, and the effectiveness of the new method is also demonstrated.

Results: The results show that the proposed multi-attribute group decision-making method with Archimedean copulas-based Hamy operators and extended best-worst in this paper outperforms some existing methods and provides support for policymakers seeking the use of patient- and community-centered health evaluations to improve health services.

Conclusion: The proposed method is a theoretical guidance method and a good reference for the evaluation of medical alliances of other regions in China.

Keywords: Archimedean copula and co-copula; Medical alliance; comprehensive performance evaluation; multi-attribute group decision-making method; q-ROFWCDHYM operator; q-rung orthopair fuzzy extended best-worst method.