Hass, David J.

INTRODUCTION: The American College of Gastroenterology assembled a multidisciplinary task force to evaluate the current state and future direction of artificial intelligence (AI) in gastroenterology, hepatology, and endoscopy leading to the development of consensus-based recommendations for responsible AI integration in clinical practice. METHODS: A total of 32 subject-matter experts and 12 industry partners, representing diverse practice settings and expertise, conducted subgroup literature reviews across 5 key areas (endoscopy, practice management clinical applications, training and education, inflammatory bowel disease and liver disease, ethics and equity). Draft statements were developed and rated on a 5-point Likert scale using a modified Delphi process. A consensus was set at ≥70% combined agreement. Nonconsensus items were revised and revoted electronically. RESULTS: A total of 43 statements, 40 (93%) reached consensus in round 1 and the remaining 3 achieved consensus after round 2. Evidence supports computer-aided detection improving adenoma detection rate and miss rate in controlled studies, with mixed real-world impact and insufficient long-term outcomes (e.g., interval colon cancer rate). Recommendations emphasize thorough validation and reduction of bias by heterogeneous Data sets. Outside endoscopy, ambient AI scribes, natural language processing (NLP)-enabled coding, workflow optimization, and previous authorization support show potential. Training recommendations endorse a structured AI curriculum while preserving independent procedural competence to avoid deskilling. In inflammatory bowel disease and hepatology, AI could help improve diagnostic accuracy, help predict risk of disease progression, and help guide therapy. Equity, governance, and reimbursement statements call for chain-of-custody data protections, specialty-society oversight, and payment models that reward quality and cost reduction. DISCUSSION: This consensus outlines how AI can augment rather than replace clinical expertise while promoting safety, transparency, interoperability, and equity. Priorities include pragmatic and prospective trials, multi-institutional data-sharing consortia, bias mitigation, and workforce training to enable trustworthy and clinically impactful AI adoption in gastroenterology, liver, and endoscopy care.

INTRODUCTION: Capsule endoscopy (CE) and deep enteroscopy (DE) can be useful for diagnosing and treating suspected small-bowel disease. Guidelines and detailed recommendations exist for the use of CE/DE, but comprehensive quality indicators are lacking. The goal of this task force was to develop quality indicators for appropriate use of CE/DE by using a modified RAND/UCLA Appropriateness Method. METHODS: An expert panel of 7 gastroenterologists with diverse practice experience was assembled to identify quality indicators. A literature review was conducted to develop a list of proposed quality indicators applicable to preprocedure, intraprocedure, and postprocedure periods. The panelists reviewed the literature; identified and modified proposed quality indicators; rated them on the basis of scientific evidence, validity, and necessity; and determined proposed performance targets. Agreement and consensus with the proposed indicators were verified using the RAND/UCLA Appropriateness Method. RESULTS: The voting procedure to prioritize metrics emphasized selecting measures to improve quality and overall patient care. Panelists rated indicators on the perceived appropriateness and necessity for clinical practice. After voting and discussion, 2 quality indicators ranked as inappropriate or uncertain were excluded. Each quality indicator was categorized by measure type, performance target, and summary of evidence. The task force identified 13 quality indicators for CE and DE. DISCUSSION: Comprehensive quality indicators have not existed for CE or DE. The task force identified quality indicators that can be incorporated into clinical practice. The panel also addressed existing knowledge gaps and posed research questions to better inform future research and quality guidelines for these procedures.