Evaluation for hierarchical diagnosis and treatment policy proposals in China: A novel multi-attribute group decision-making method with multi-parametric distance measures.

The policy 'hierarchical medical treatment system' promulgated by the State Council of China is an effective way to solve the problem of insufficient and unbalanced medical resources. In response, governments in different provinces explore a variety of different strategies to promote this policy, producing different results. To better strengthen the policy development, it is worthy to help policy-makers make decisions to elect the best one from different proposals. Thus, the aim of this paper is to develop a multi-attribute group decision-making (MAGDM) framework to better assist government select the optimal proposal. This study proposes a MAGDM method based on a family of q-rung orthopair fuzzy interaction power point Hamy mean operators to solve the above problem. To this end, new multi-parametric distance measures based on point operators in the framework of q-rung orthopair fuzzy set are proposed. With the help of the point distance measures, new power point operators average operator is also proposed. The results show that the proposed MAGDM method in this paper outperforms some existing methods and provides promising results for policy-makers seeking to identify the optimal hierarchical diagnosis and treatment policy (HDTP) proposal. Specifically, the results also revealed the best proposal for developing the HDTP proposals is Xiamen mode.