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

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.