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DOI 10.3390/curroncol33090540

Медицинская библиотека · Current oncology (Toronto, Ont.) · 2026

Assessing Quality Gaps and Clinician Perspectives on AI Integration in Colorectal Cancer NGS Pathways.

Thanabalachandran Luxiga, Ali Darya, Newman-Simmons Avery, Norman Claire, Jafari Daniel, Grahovac Tamara, Pollett Aaron, Huang Weei-Yuarn, Chen Lina, Kassam Shaqil, Barron Carly C, Khanna Suneil, Wright Kristin, Snow Stephanie, Burkes Ron, Wang Tao, Grin Andrea, Moffat Taylor, Li Yuchen

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Аннотация

Next-generation sequencing (NGS) is integral to colorectal cancer (CRC) care, but its value depends on results being available when treatment decisions are made. We conducted a qualitative study to identify quality gaps in CRC NGS pathways and assess perspectives on digital and artificial intelligence (AI)-enabled workflow support. Semi-structured interviews were conducted with 22 medical oncologists and pathologists from 14 Ontario hospitals, and transcripts were analyzed thematically. Five themes emerged: (1) clinical indications and test ordering, where initiation was inconsistent because of unclear reflex-testing criteria, reliance on upstream clinicians, staging uncertainty, evolving indications, and funding constraints; (2) tissue, pathology, and laboratory workflow, where participants attributed bottlenecks and turnaround variability to send-out testing, staffing, infrastructure, and capacity; (3) interdisciplinary communication and tracking, where informal communication, unclear ownership, and manual tracking highlighted the need for closed-loop confirmation and alerts; (4) reporting and clinical integration, where report clarity, interpretability, and timing affected use; and (5) electronic health record integration and AI integration, where fragmented systems and limited interoperability delayed result access. Participants supported clinician-supervised digital or AI-enabled tools for case identification, triage, tracking, and overdue-result alerts. CRC NGS optimization requires standardized reflex criteria, clearer ownership, closed-loop tracking, reliable routing, structured reporting, and interoperable infrastructure.

Для цитирования: Thanabalachandran Luxiga, Ali Darya, Newman-Simmons Avery, Norman Claire, Jafari Daniel, Grahovac Tamara, Pollett Aaron, Huang Weei-Yuarn, Chen Lina, Kassam Shaqil, Barron Carly C, Khanna Suneil, Wright Kristin, Snow Stephanie, Burkes Ron, Wang Tao, Grin Andrea, Moffat Taylor, Li Yuchen. Assessing Quality Gaps and Clinician Perspectives on AI Integration in Colorectal Cancer NGS Pathways.. Current oncology (Toronto, Ont.). 2026. DOI: 10.3390/curroncol33090540.

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