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As part of our role in the Next Generation Health Technology Assessment (HTx) project, funded by the EU, we’ve developed CHEERS-AI.

It’s a new reporting standard for health economic evaluations of AI technologies. The tool aims to improve transparency and quality in how cost-effectiveness studies of AI-enabled healthcare interventions are reported. This will help healthcare decision-makers understand the value of AI-enabled treatments, helping patients gain faster access to the most promising ones.

The challenge 

Our systematic review, Economic evaluations of artificial intelligence-based healthcare interventions: a systematic literature review of best practices in their conduct and reporting, revealed variable quality in published health economic evaluations for AI-based health interventions. Key limitations included:

  • poor quality input data

  • author conflicts of interest

  • lack of transparent reporting

  • unclear information about AI functionality.

We realised that setting out specific reporting standards for economic evaluation studies of AI interventions would help improve transparency in this emerging field and increase their usefulness for health and care system decision-makers. This is crucial for reimbursement decisions about this new field of healthcare technology.

Our solution: CHEERS-AI

We designed CHEERS-AI (Consolidated Health Economic Evaluation Reporting Standards for Interventions that Use Artificial Intelligence) for study authors and reviewers.

CHEERS-AI builds on existing best practice in health economic evaluation reporting by including the original 28 standards from the previously published CHEERS-2022. To these, we’ve added 8 extra details for AI-related nuances. There are also 10 new AI-specific standards covering areas such as:

  • user autonomy

  • AI learning over time

  • development of the AI component.

Our CHEERS-AI checklist helps to ensure transparent and reproducible reporting of AI-specific details in health economic evaluations. This supports the interpretation and comparison of such studies by reviewers and decision-makers. We hope that it will raise the standard of economic evaluation reporting as AI’s presence in healthcare grows.

The professional society for health economics and outcomes research, ISPOR, has endorsed CHEERS-AI and it’s included in the Equator Network list of reporting checklists.

To learn more, watch our webinar delivered in collaboration with ISPOR and the University of York.

NICE participates in various methodological research projects with partners worldwide, such as HTx. These partnerships help us improve our work. They also help us anticipate and adapt to policy developments, including changes in health and social care delivery.

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