Improving Oncotype DX turnaround time for timeliness of adjuvant therapy: A single-system, multi-site quality improvement study in early-stage HR-positive breast cancer.

464 Background: Timely initiation of adjuvant therapy based on genomic risk is critical in early-stage, HR-positive breast cancer. The Oncotype DX test guides chemotherapy decision-making, but delays in ordering and processing can hinder prompt treatment. At the West Virginia University Cancer Institute (WVUCI)—a single system with 15 satellite sites, these delays represent a significant gap in care delivery. This quality improvement (QI) initiative targeted Oncotype DX turnaround time as a modifiable factor to improve timely initiation of risk-adapted adjuvant therapy. Methods: A critical process analysis identified three major contributors to delayed turnaround time (TAT), defined as order to result date: (1) lack of electronic medical record (EMR) integration, (2) insurance pre-authorization delays, and (3) internal pathology approval prior to specimen shipment. Sequential targeted interventions were implemented, including: (1) EMR integration of test ordering via Epic Aura (August 2025), (2) bypass of insurance pre-authorization for processing (January 2025), and (3) removal of pathologist sample pre-selection (February 2025). An IRB-approved protocol was used to track all orders from January 2024 to March 2025. Three groups were compared: (1) baseline, (2) post-EMR integration, and (3) post-full interventions. Outcomes assessed were mean total TAT, time from order to company arrival and time from arrival to result. Statistical analyses included the Kruskal-Wallis and Mann–Whitney U tests due to non-normal data distribution and a post-hoc Dunn’s test. Results: The study sample included 355 Oncotype DX orders across the health system. A significant difference in TAT was observed across the three groups, as determined by the Kruskal-Wallis test (p<0.05). Post-hoc analyses revealed that Group 2 had a significantly lower TAT than Group 1 (p < 0.05), and Group 3 had a significantly lower TAT than Group 1 (p < 0.05). The total mean TAT improved from 17.3 days (95% CI: 15.3-19.4) at baseline to 9.9 days (95% CI: 8.1-11.7) post-full interventions (p<0.001), reflecting an approximately 43% reduction. The mean time from order to company arrival decreased from 8.4 days (95% CI: 6.5-10.0) to 2.9 days (95% CI: 2.3-3.5, p<0.001), while the mean time from arrival to result decreased from 9.0 days (95% CI: 7.9-10.1) to 7.0 days (95% CI: 5.3-8.7, p<0.05). Subgroup analysis showed a reduction of 6.0 days in mean TAT at the main site (p<0.05) and 8.0 days at the satellite sites (p<0.05) following all interventions. Conclusions: This multi-site QI initiative achieved a 43% mean reduction in Oncotype DX TAT. The EMR integration, insurance streamlining, and pathology workflow changes were both feasible and effective across a large cancer network. Ongoing research will evaluate the impact of reduced TAT on timely initiation of adjuvant therapy.