Research on establishment decision of medical equipment measurement standard based on GDM-AHP

The problems in the current medical equipment measurement work have made many medical institutions begin to consider establishing a convenient, long-term stable and low-cost measurement service model by establishing internal measurement standards, but they have not made further in-depth exploration and the construction of a perfect measurement standard to establish a feasibility evaluation system. This study aims to construct a feasibility evaluation system for establishing measurement standards based on the Group Decision Making-Analytical Hierarchy Processes and provide a reference basis for decision-making in the establishment of measurement standards for medical equipment. A feasibility evaluation system for the establishment of measurement standards based on Group Decision Making-Analytical Hierarchy Processes is constructed, which includes 5 main criteria-level evaluation indicators and 14 sub-criteria-level evaluation indicators. The relative weights of the criteria-level evaluation indicators are calculated by constructing a judgment matrix through pairwise comparisons of the evaluation indicators using the Saaty scale method. Additionally, sensitivity analysis of the constructed model is conducted using the perturbation method. Then, we applied the constructed evaluation system to the feasibility evaluation of establishing measurement standards for eight different types of medical equipment in seven medical institutions. Differences in medical institutions and categories of medical equipment both have an impact on the values of the feasibility indicators for the establishment of measurement standards for medical equipment. The results of this study show that, the feasibility evaluation system for establishing measurement standards based on Group Decision Making-Analytical Hierarchy Processes can transform the problem of exploring the feasibility of establishing measurement standards in medical institutions into a multi-indicator quantitative evaluation problem, making the difficult-to-quantify decision-making process more scientific and objective.