TY - JOUR
T1 - Consolidated Health Economic Evaluation Reporting Standards for Interventions That Use Artificial Intelligence (CHEERS-AI)
AU - The CHEERS-AI Steering Group
AU - Elvidge, Jamie
AU - Hawksworth, Claire
AU - Avşar, Tuba Saygın
AU - Zemplenyi, Antal
AU - Chalkidou, Anastasia
AU - Petrou, Stavros
AU - Petykó, Zsuzsanna
AU - Srivastava, Divya
AU - Chandra, Gunjan
AU - Delaye, Julien
AU - Denniston, Alastair
AU - Gomes, Manuel
AU - Knies, Saskia
AU - Nousios, Petros
AU - Siirtola, Pekka
AU - Wang, Junfeng
AU - Dawoud, Dalia
AU - Arbour, Sylvie
AU - Asche, Carl
AU - Ashurst, Carolyn
AU - Balkanyi, Laszlo
AU - Bennett, Hayley
AU - Boros, Gerzson
AU - Boyce, Rebecca
AU - Carswell, Chris
AU - Chaiyakunapruk, Nathorn
AU - Chhatwal, Jagpreet
AU - Ciani, Oriana
AU - Collins, Gary
AU - Dawson, David
AU - Vanness, David
AU - Di Bidino, Rossella
AU - Faulding, Susan
AU - Felizzi, Federico
AU - Haig, Madeleine
AU - Hawkins, James
AU - Hiligsmann, Mikaël
AU - Holst-Kristensen, Annette Willemoes
AU - Isla, Julian
AU - Koffijberg, Erik
AU - Kostyuk, Alexander
AU - Krief, Noemi
AU - Lee, Dawn
AU - Lee, Karen
AU - Lundin, Douglas
AU - Markiewicz-Barreaux, Katarzyna
AU - Mauskopf, Josephine
AU - Moons, Karel
AU - Németh, Bertalan
AU - Petrova, Guenka
N1 - Publisher Copyright:
© 2024
PY - 2024/9
Y1 - 2024/9
N2 - 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.
AB - 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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U2 - 10.1016/j.jval.2024.05.006
DO - 10.1016/j.jval.2024.05.006
M3 - Article
C2 - 38795956
AN - SCOPUS:85196424591
SN - 1098-3015
VL - 27
SP - 1196
EP - 1205
JO - Value in Health
JF - Value in Health
IS - 9
ER -