Artificial Intelligence to Support HTA and Conducting HTA for Artificial Intelligence Technologies: Recent Developments and Reflections

Speaker(s)

Discussion Leader: Jamie Elvidge, MSc, Science, Evidence and Analytics Directorate, National Institute for Health and Care Excellence, Manchester, UK
Discussants: Gunjan Chandra, MSc, Biomimetics and Intelligent Systems Group, University of Oulu, Oulu, 14, Finland; Antal Tamas Zemplenyi, PhD, Center for Health Technology Assessment, University of Pécs, Pécs, Hungary; Julien Delaye, MS, Eurordis, ., Belgium

PURPOSE: This workshop will present findings from the Next Generation Health Technology Assessment project (HTx) relating to the juncture between HTA and artificial intelligence (AI). It will explore both how novel AI methods may be used to enhance the conduct of HTA and important considerations for HTA organizations when assessing AI-based healthcare technologies. Attendees will learn about recent developments in both directions.

DESCRIPTION: There is increasing interest in how AI can be used to conduct HTA. It may have the potential to accelerate HTA processes, for example by automating evidence identification, or to directly inform reimbursement decision making, by facilitating a deeper use of real-world data and more personalised clinical and cost-effectiveness conclusions. Furthermore, the growing presence of AI-driven health technologies means HTA organisations will increasingly have to assess the value of interventions that use AI, which may introduce novel challenges.

Jamie Elvidge will provide a summary of the HTx project, and describe work to develop an AI extension to the CHEERS checklist (“CHEERS-AI”) for reporting economic evaluations of AI-based health technologies (12`).

Gunjan Chandra will present an application of “explainable” AI, using real-world data to predict individual glycated haemoglobin responses to a range of possible treatments for type 2 diabetes, incorporating both clinical and socioeconomic predictors (12`).

Antal Zemplenyi will summarise the recommendations from a multi-stakeholder workshop to support healthcare decision-makers in integrating AI into HTA processes, with a special focus on Central and Eastern European countries (12`).

François Houÿez will discuss the patient perspective on how AI could contribute to develop more targeted health interventions and assist healthcare decision making that accounts for patients’ preferences, and what should done to build trust in AI-based interventions (12`).

There will be time for audience interaction. This workshop will be of interest to HTA stakeholders, and developers and users of AI health technologies.

Code

124

Topic

Health Technology Assessment