Integrating ARAS with PyFWZIC to evaluate and benchmark patient-facing genetic services digital tools

Digital tools are revolutionizing patient care by enhancing the quality of care and facilitating the development of patient-oriented solutions that improve patients’ well-being. Evaluating and comparing these digital tools requires the consideration of several essential key criteria, which turns it into a multicriteria decision-making (MCDM) problem. This study introduces a decision-making framework that integrates the additive ratio assessment (ARAS) method with an extension of the fuzzy weighted zero inconsistency based on the Pythagorean fuzzy environment (PyFWZIC). The framework is used to evaluate and benchmark genetic services tools used by patients based on a decision matrix formed of eight key attributes and 69 existing digital tools as alternatives grouped in five main categories. PyFWZIC is used to compute the weights of the criteria based on the opinion of three domain experts. The ARAS method is used to benchmark the digital tools and rank them for effectiveness. The findings of the study reveal that PyFWZIC effectively weighs the key criteria required for the development and benchmarking of genetic services digital tools while considering the vagueness and ambiguities of subjective opinions and eliminating inconsistencies that arise thereof. The robustness and reliability of the result is evaluated using sensitivity analysis and comparative analysis.