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

IF 5.7 3区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Valentina Bellini, Francesco Calabrò, Elena Bignami, Tudor Mihai Haja, Iben Fasterholdt, Benjamin Sb Rasmussen, Rossana Cecchi
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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.

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人工智能价值评估模型(MAS-AI)框架在组织人工智能中的应用——以意大利手术调度评估为例
这项工作旨在通过案例研究探索意大利背景下评估医学成像(MAS-AI)人工智能价值模型的可转移性。我们应用MAS-AI(一种用于评估医疗保健领域人工智能的模型)来完成对我们机构内开发的人工智能模型的技术评估。该模型被称为手术单元的新组织模型(block - op),利用人工智能来提高手术单元的调度效率。正如项目介绍中所描述的那样,对block - op特征的分析是通过MAS-AI模型中包含的评估需求进行的。完全遵循MAS-AI的方法框架,使我们能够对block - op模型的各个方面进行全面评估。我们提供了框架中每个领域的详细描述,以及汇总表。案例研究表明,在不同于最初开发框架的国家背景下,将MAS-AI应用于组织AI模型是可行的。我们没有提出新的模型,而是测试了MAS-AI在评估非成像AI系统中的适应性。这证实了其超出原始范围的灵活性,并支持其作为医疗保健领域人工智能评估的通用工具的潜力。
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来源期刊
Journal of Medical Systems
Journal of Medical Systems 医学-卫生保健
CiteScore
11.60
自引率
1.90%
发文量
83
审稿时长
4.8 months
期刊介绍: Journal of Medical Systems provides a forum for the presentation and discussion of the increasingly extensive applications of new systems techniques and methods in hospital clinic and physician''s office administration; pathology radiology and pharmaceutical delivery systems; medical records storage and retrieval; and ancillary patient-support systems. The journal publishes informative articles essays and studies across the entire scale of medical systems from large hospital programs to novel small-scale medical services. Education is an integral part of this amalgamation of sciences and selected articles are published in this area. Since existing medical systems are constantly being modified to fit particular circumstances and to solve specific problems the journal includes a special section devoted to status reports on current installations.
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