Consolidated Health Economic Evaluation Reporting Standards for Interventions that use Artificial Intelligence (CHEERS-AI)
Elvidge, Jamie; Hawksworth, Claire; Avşar, Tuba Saygın; Zemplenyi, Antal; Chalkidou, Anastasia; Petrou, Stavros; Petykó, Zsuzsanna; Srivastava, Divya; Chandra, Gunjan; Delaye, Julien; Denniston, Alastair; Gomes, Manuel; Knies, Saskia; Nousios, Petros; Siirtola, Pekka; Wang, Junfeng; Dawoud, Dalia; on behalf of the The CHEERS-AI Steering Group (2024-05-23)
Elsevier
23.05.2024
Elvidge, J., Hawksworth, C., Avşar, T. S., Zemplenyi, A., Chalkidou, A., Petrou, S., Petykó, Z., Srivastava, D., Chandra, G., Delaye, J., Denniston, A., Gomes, M., Knies, S., Nousios, P., Siirtola, P., Wang, J., Dawoud, D., Arbour, S., Asche, C., … Wilson, E. (2024). Consolidated health economic evaluation reporting standards for interventions that use artificial intelligence(Cheers-ai). Value in Health, 27(9), 1196–1205. https://doi.org/10.1016/j.jval.2024.05.006
https://creativecommons.org/licenses/by-nc-nd/4.0/
© 2024, International Society for Pharmacoeconomics and Outcomes Research, Inc. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
https://creativecommons.org/licenses/by-nc-nd/4.0/
© 2024, International Society for Pharmacoeconomics and Outcomes Research, Inc. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
https://creativecommons.org/licenses/by-nc-nd/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202406244867
https://urn.fi/URN:NBN:fi:oulu-202406244867
Tiivistelmä
Abstract
Objectives:
Economic evaluations (EEs) are commonly used by decision makers to understand the value of health interventions. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) provide reporting guidelines for EEs. Healthcare systems will increasingly see new interventions that use artificial intelligence (AI) to perform their function. We developed Consolidated Health Economic Evaluation Reporting Standards for Interventions that use AI (CHEERS-AI) to ensure EEs of AI-based health interventions are reported in a transparent and reproducible manner.
Methods:
Potential CHEERS-AI reporting items were informed by 2 published systematic literature reviews of EEs and a contemporary update. A Delphi study was conducted using 3 survey rounds to elicit multidisciplinary expert views on 26 potential items, through a 9-point Likert rating scale and qualitative comments. An online consensus meeting was held to finalize outstanding reporting items. A digital health patient group reviewed the final checklist from a patient perspective.
Results:
A total of 58 participants responded to survey round 1, 42, and 31 of whom responded to rounds 2 and 3, respectively. Nine participants joined the consensus meeting. Ultimately, 38 reporting items were included in CHEERS-AI. They comprised the 28 original CHEERS 2022 items, plus 10 new AI-specific reporting items. Additionally, 8 of the original CHEERS 2022 items were elaborated on to ensure AI-specific nuance is reported.
Conclusions:
CHEERS-AI should be used when reporting an EE of an intervention that uses AI to perform its function. CHEERS-AI will help decision makers and reviewers to understand important AI-specific details of an intervention, and any implications for the EE methods used and cost-effectiveness conclusions.
Objectives:
Economic evaluations (EEs) are commonly used by decision makers to understand the value of health interventions. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) provide reporting guidelines for EEs. Healthcare systems will increasingly see new interventions that use artificial intelligence (AI) to perform their function. We developed Consolidated Health Economic Evaluation Reporting Standards for Interventions that use AI (CHEERS-AI) to ensure EEs of AI-based health interventions are reported in a transparent and reproducible manner.
Methods:
Potential CHEERS-AI reporting items were informed by 2 published systematic literature reviews of EEs and a contemporary update. A Delphi study was conducted using 3 survey rounds to elicit multidisciplinary expert views on 26 potential items, through a 9-point Likert rating scale and qualitative comments. An online consensus meeting was held to finalize outstanding reporting items. A digital health patient group reviewed the final checklist from a patient perspective.
Results:
A total of 58 participants responded to survey round 1, 42, and 31 of whom responded to rounds 2 and 3, respectively. Nine participants joined the consensus meeting. Ultimately, 38 reporting items were included in CHEERS-AI. They comprised the 28 original CHEERS 2022 items, plus 10 new AI-specific reporting items. Additionally, 8 of the original CHEERS 2022 items were elaborated on to ensure AI-specific nuance is reported.
Conclusions:
CHEERS-AI should be used when reporting an EE of an intervention that uses AI to perform its function. CHEERS-AI will help decision makers and reviewers to understand important AI-specific details of an intervention, and any implications for the EE methods used and cost-effectiveness conclusions.
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