Full title: Model for ASsessment of Artificial Intelligence
In the coming years, artificial intelligence (AI) will play an increasingly bigger role at hospitals in Denmark and abroad, but we lack models to assess the effects and value of the technologies.
The project wanted to develop a model to assess the value of AI-technologies in the field of medical imaging. The assessments can help decision-makers select the AI-technologies that create value and avoid implementing technologies with no or unintentional effects.
The model was developed based on the following steps:
- A review of existing guides, evaluations and assessments of the value of AI in the field of medical imaging
- Interviews with leading researchers in AI in Denmark
- Workshops with decision-makers, patient organisations and researchers
Based on the results from the steps above, the project developed an overall model, which provides administrative and clinical decision-makers with an overview of the consequences of AI technology in the field of medical imaging.
The project developed the model MAS-AI which is an HTA-based framework to support the introduction of novel AI technologies into healthcare.
The model was developed by a multidisciplinary group of experts, researchers and patient representatives, and it consists of two steps covering nine domains and process factors supporting the assessment.
Step one contains a description of patients, how the AI was developed, and initial ethical and legal considerations. Finishing the four domains in step one is a prerequisite for moving to step two. In step two, a multidisciplinary assessment of outcomes of the AI application is done for the five remaining domains: safety, clinical aspects, economics, organisational aspects and patient aspects.
MAS-AI can help support decision-making and provide greater transparency for all parties involved.
The project is a cooperation with the Department of Radiology and the Department of Nuclear Medicine at OUH. Further, a Canadian validation of MAS-AI is carried out in collaboration with Theta Collaborative and Transform HF, including Dr. Valeria E. Rac, who is Director of the Clinical Research Division of Theta.
Read the article Model for ASsessing the value of Artificial Intelligence in medical imaging (MAS-AI) in the Journal of Technology Assessment in Health Care (login required).
Read the review behind MAS-AI in BMC Medical Imaging, part of Springer Nature.