JMIR Publications

ABSTRACT

Background:

Artificial intelligence-based medical devices have garnered attention due to their ability to revolutionize medicine. There is a lack in the adaptation of their health technology assessment framework.

Objective:

To analyze the suitability of each HTA domain for the assessment of AI-based MD

Methods:

We conducted a scoping literature review following the PRISMA methodology. We searched databases including PubMed, Embase, Cochrane Library, and from the gray literature and from HTA agency websites

Results:

Results:

78 references were included out of 775 citations. Data quality and integration are vital aspects to consider when describing and assessing the technical characteristics of AI-based medical devices during a HTA process. When it comes to implementing specialized HTA for AI-based MD, several practical challenges and potential barriers could be highlighted and should be taken into account (AI technological evolution timeline, Data Requirements, Complexity and Transparency, Clinical Validation and Safety requirements, Regulatory and Ethical Considerations, Economic Evaluation). Discussion: Adaptation of the HTA process through a methodological framework for AI-based MDs enhances the comparability of results across different evaluations and jurisdictions. By defining the necessary expertise, the framework supports the development of a skilled workforce capable of conducting robust and reliable HTAs of AI-based medical devices.

Conclusions:

A comprehensive adapted HTA framework for AI-based medical devices can provide valuable insights into the effectiveness, cost-effectiveness, and societal impact of AI-based medical devices, guiding their responsible implementation and maximizing their benefits for patients and healthcare systems.