Case study applies the MAS-AI framework to assess an AI model in surgical scheduling, indicating its versatility.
This work aims to explore the transferability of the Model for Assessing the value of Artificial Intelligence in medical imaging (MAS-AI) in the Italian context through a case-study. We applied the MAS-AI, a model for assessing AI in healthcare, to fulfil a technology assessment of an AI model developed within our institution. The model, called New organization model for the surgical unit (BLOC-OP), uses AI to improve the schedule efficiency of the surgical unit. The analysis of BLOC-OP’s features, as they were described in the project presentation, was conducted through the requirements for the assessment contained in the MAS-AI model. The methodological framework of MAS-AI was fully followed, allowing us to conduct a comprehensive assessment of the BLOC-OP model in all its aspects. We provided a detailed description of each domain within the framework, along with a summary table. The case study demonstrates the feasibility of applying MAS-AI to organizational AI models in a national context different from where the framework was originally developed. Rather than proposing a new model, we tested the adaptability of MAS-AI in evaluating a non-imaging AI system. This confirms its flexibility beyond its original scope and supports its potential as a generalizable tool for AI evaluation in healthcare.
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Bellini et al. (2025) studied this question.
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