TY - JOUR
T1 - Benefits and challenges in implementation of artificial intelligence in colonoscopy
T2 - World Endoscopy Organization position statement
AU - Mori, Yuichi
AU - East, James E.
AU - Hassan, Cesare
AU - Halvorsen, Natalie
AU - Berzin, Tyler M.
AU - Byrne, Michael
AU - von Renteln, Daniel
AU - Hewett, David G.
AU - Repici, Alessandro
AU - Ramchandani, Mohan
AU - Al Khatry, Maryam
AU - Kudo, Shin-ei
AU - Wang, Pu
AU - Yu, Honggang
AU - Saito, Yutaka
AU - Misawa, Masashi
AU - Parasa, Sravanthi
AU - Matsubayashi, Carolina Ogawa
AU - Ogata, Haruhiko
AU - Tajiri, Hisao
AU - Pausawasdi, Nonthalee
AU - Dekker, Evelien
AU - Ahmad, Omer F.
AU - Sharma, Prateek
AU - Rex, Douglas K.
N1 - Funding Information: Author Y.M. is funded by the European Commission (Horizon Europe 101057099) and Japan Society for Promotion of Science (22H03357); J.E.E. is funded by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the Department of Health. Publisher Copyright: © 2023 Japan Gastroenterological Endoscopy Society.
PY - 2023/5
Y1 - 2023/5
N2 - The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost-effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO Position Statement: Statement 1.1: Computer-aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short term, use of CADe is likely to increase health-care costs by detecting more adenomas; Statement 1.3: In the long term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe-related cancer prevention; Statement 1.4: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer-aided diagnosis (CADx) for diminutive polyps (≤5 mm), when it has sufficient accuracy, is expected to reduce health-care costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high-quality cost-effectiveness research should be undertaken to understand whether AI implementation benefits populations and societies in different health-care systems.
AB - The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost-effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO Position Statement: Statement 1.1: Computer-aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short term, use of CADe is likely to increase health-care costs by detecting more adenomas; Statement 1.3: In the long term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe-related cancer prevention; Statement 1.4: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer-aided diagnosis (CADx) for diminutive polyps (≤5 mm), when it has sufficient accuracy, is expected to reduce health-care costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high-quality cost-effectiveness research should be undertaken to understand whether AI implementation benefits populations and societies in different health-care systems.
KW - colon polyp
KW - colonoscopy
UR - http://www.scopus.com/inward/record.url?scp=85149924848&partnerID=8YFLogxK
U2 - https://doi.org/10.1111/den.14531
DO - https://doi.org/10.1111/den.14531
M3 - Article
C2 - 36749036
SN - 0915-5635
VL - 35
SP - 422
EP - 429
JO - Digestive Endoscopy
JF - Digestive Endoscopy
IS - 4
ER -