Abstract Background Patients with colonic inflammatory bowel disease (IBD) are at increased risk for colorectal cancer (CRC). Regular surveillance is essential for early detection of dysplastic lesions and prevention of malignant transformation. Determining the optimal timing for surveillance colonoscopies is complex and depends on multiple factors such as disease activity and extent, comorbidities, and co-occurrence of primary sclerosing cholangitis (PSC). We aimed to develop a nurse-led AI algorithm that integrates data from multiple sources to automatically indicate the optimal timing of colonoscopy follow-up in individual patients with IBD, supporting timely clinical planning. Methods We created an algorithm based on international guidelines for IBD CRC surveillance (fig 1).1 The clinical, endoscopic and microscopic variables feeding the algorithm are extracted from multiple structured data sources including the hospital electronic medical record (EMR), the UR-CARE local database and coded pathology reports. To address data gaps, an annual digital questionnaire is distributed through the hospital app to collect additional details requiring regular updates (e.g. family history of CRC). This information is then integrated to maintain up-to-date personalized recommendations. Results Automated feeding of a colonsurveillance algorithm is feasible using structured data input sources and leads to personalized colonoscopy timing recommendations. In case of incomplete data, the system automatically paused at the relevant decision point, prompting a precautionary recommendation for an earlier colonoscopy to ensure patient safety and maintain decision accuracy. To ensure prompt intervention and appropriate follow-up care, the output of the AI-tool is displayed on the patient’s individual monitoring dashboard and an automated red flag notification system alerts clinicians when a patient is due for a follow-up within the next year. Conclusion The implementation of a nurse-led AI-assisted, guideline-based algorithm provides an innovative, standardized and efficient framework for determining colonoscopy intervals in IBD surveillance. By combining structured clinical data and patient-reported updates, the system enhances the precision and timeliness of CRC prevention. The real-time dashboard visualization and red flag alerts support proactive patient management. A prospective study comparing the AI-based recommendations with the current standard of care is planned to evaluate its full clinical impact. Reference: East JE, Gordon M, Nigam GB, et al. British Society of Gastroenterology guidelines on colorectal surveillance in inflammatory bowel disease. Gut 2025;0:1-34. Conflict of interest: Louis, Stephanie: / Lembrechts, Nikki: / Van Brantegem, Karel: / El Idrissi, Ilham: / Pouillon, Lieven: Lieven Pouillon received advisory board fees from AbbVie, Alphasigma, Celltrion, Galápagos, Janssen-Cilag, Sandoz and Takeda consultancy fees from Ipsos NV and Ismar Healthcare funded by Viatris presentation fees from AbbVie, Alphasigma, Celltrion, Eli Lilly, Ferring, Galápagos and Pfizer and personal fees (congress support) from AbbVie, EG, Ferring, Galápagos, Janssen-Cilag, Norgine and Takeda. Bossuyt, Peter: Grant support for research from AbbVie, EG Consulting fee from AbbVie, Bristol Meyers Squibb, CIRC, Galapagos, Janssen, Jeito capital, Lilly, Pentax, Pfizer, PSI-CRO, Roche, Takeda, Tetrameros Speakers fee from AbbVie, AMC ICP, Amgen, Bristol Myers Squibb, Celltrion, Dr Falk Benelux, EG, Galapagos, Globalport, Lilly, Medtalks, Materia Prima, Pentax, Springer Media
Louis et al. (Thu,) studied this question.