Applying the Model for Assessing the Value of AI (MAS-AI) Framework To Organizational AI: A Case Study of Surgical Scheduling Assessment in Italy.

Journal: Journal of medical systems
Published Date:

Abstract

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.

Authors

  • Valentina Bellini
    Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126, Parma, Italy.
  • Francesco CalabrĂ²
    Department of Mathematics and Applications "Renato Caccioppoli", University of Naples "Federico II", Via Cintia, Monte S. Angelo, 80126, Naples, Italy. francesco.calabro@unina.it.
  • Elena Bignami
    Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy. Electronic address: bignami.elena@hsr.it.
  • Tudor Mihai Haja
    Laboratory of Forensic Medicine, Department of Medicine and Surgery, University of Parma, Parma, Italy.
  • Iben Fasterholdt
    CIMT - Centre for Innovative Medical Technology, Odense University Hospital, Sdr. Boulevard 29, Entrance 102, 4rd Floor, 5000, Odense C, Denmark. if@rsyd.dk.
  • Benjamin Sb Rasmussen
    CAI-X - Centre for Clinical Artificial Intelligence, Odense Universitetshospital.
  • Rossana Cecchi
    Laboratory of Forensic Medicine, Department of Medicine and Surgery, University of Parma, Parma, Italy. rossana.cecchi@unipr.it.