There is no standard clinical trial screening process in gynecologic oncology. In our low resource, highly diverse gynecologic oncology patient population, we sought to create an equitable, adaptable, manual screening process. Our objective is to describe our clinical trial screening process and success in improving trial enrollment. An Institutional Review Board (IRB) approved quality improvement (QI) project was implemented in July 2022 to evaluate trial access. Screenable events were defined. Potential patients were those with a screenable event: new patients or diagnoses, regimen changes, progressions, and recurrences. Events were categorized into screen positive or screened no trial available. Screen positives were further categorized as screen positive, enrollment failure events or enrollments. Data about patients were collected via weekly research team meetings. Monthly meetings occurred to review progress. The data were compared to trials available, number of patients with trail available, and those that enrolled. Reasons for enrollment fails were tracked. Over time, “screen no trial available” (SNTA) rates stayed stable, but enrollment rates increased. Patient preference accounted for 32.8 % of enrollment failures (n = 42), pre-existing symptoms 23.4 % (n = 30), and location 21.1 % (n = 27). During increased employee turnover, there was a rise in enrollment fails due to staffing (n = 6, 4.7 %). We describe an effective process of clearly defining and tracking our patient population and ‘screenable events’ for which all patients are screened and offered trial participation if eligible. We show that we improved understanding of the patient population, built a clinical trial portfolio better matched to population served, exceeded national averages for enrolling patients on trials, and are improving number eligible.

Objective: Clinical trials are the cornerstone of medical innovation and set the standard for medical care. Cancer clinical trials drive critical innovation and availability of new treatments. However, obstacles to successful recruitment and participation of patients in clinical trials still significantly limit their success. Our objective is to evaluate trial enrollment trends according to both patient and trial demographics/features for those who have sought care at our multi-center, mixed-setting Gynecologic Oncology practice, allowing for us to describe specific trial criteria designs that are negatively associated with diverse enrollment or lack of enrollment completion on cancer clinical trials. Methods: An IRB-approved, retrospective cohort study was completed to evaluate patients who screened positive for a clinical trial through the Gynecologic Oncology practice’s manual screening process. We looked at how trial characteristics affect enrollment success. Results: After adjustment, there were no significant differences between patient factors and enrollment status. Higher rates of enrollment were seen among Asian patients and patients whose race was reported as “unknown” (>50%, p = 0.125). There was a drastic, unadjusted estimated increase in enrollment for Medicaid patients compared to patients with other insurance types (55.2% vs. 32%, p = 0.031), but multivariable logistic regression showed that insurance status (Medicaid vs. others) lost significance, p = 0.148. Patients with Stage I cancer accounted for 42.1% of patients enrolled, and enrollment rates were higher than for other cancer stages (p = 0.087). There was a significant increase in enrollment likelihood if the trial did not exclude subjects with prior cancer (50.0% vs. 33.3%, p = 0.046). Conclusions: We demonstrated equitable trial enrollment across different races and insurance statuses and were able to identify criteria that lend itself towards higher rates of enrollment. These findings can be used to tailor cancer trial portfolios to a diverse patient catchment.