Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Sep 20, 2021
Date Accepted: May 13, 2022
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Cost-effectiveness of AI in medicine from a clinical, technical, and economic perspective: A scoping review and a framework of analysis
ABSTRACT
Background:
Research and Development (R&D) of Artificial Intelligence (AI) in medicine involve clinical, technical and economic aspects. Better understanding the relationship between these dimensions seems necessary to coordinate efforts of R&D among stakeholders.
Objective:
To assess systematically existing literature on the cost-effectiveness of Artificial Intelligence (AI) from a clinical, technical and economic perspective.
Methods:
A systematic literature review was conducted to study the cost-effectiveness of AI solutions and summarised within a scoping framework of health policy analysis developed to study clinical, technical and economic dimensions.
Results:
Of the 4820 eligible studies, 13 met the inclusion criteria. Internal medicine and emergency medicine were the most studied clinical disciplines. Technical R&D aspects have not been uniformly disclosed in the studies we analysed. Monetisation aspects such as payment models assumed have not been reported in the majority of cases.
Conclusions:
Existing scientific literature on the cost-effectiveness of AI currently does not allow to draw conclusive recommendations. Further research and improved reporting on technical and economic aspects seem necessary to assess potential use-cases of this technology, as well as to secure reproducibility of results. Clinical Trial: Not applicable
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