What does this research mean for the field?

Implementing an EMR-based clinical trial screening prompt significantly increases screening rates and improves equity by increasing screening odds among African American patients in gynecologic oncology clinics. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This research aims to assess the impact of EMR prompts on increasing trial enrollment in gynecologic oncology, particularly focusing on diversity.

May 30, 2026

Leveraging EMR prompts to promote equitable clinical trial participation in gynecologic oncology: RE-AIM implementation results.

Key Points

This research aims to assess the impact of EMR prompts on increasing trial enrollment in gynecologic oncology, particularly focusing on diversity.
Modified clinical trial prompts in EMR for provider use during patient visits.
Conducted a retrospective review pre- and post-implementation using ICD-10 codes for cancer identification.
Utilized Firth penalized logistic regression to assess associations between screening and patient characteristics.
Screening increased significantly post-implementation (OR 3.63, 95% CI 1.92–7.12; p < 0.001).
African American patients had higher odds of screening compared to White patients (OR 3.88, 95% CI 1.28–19.1; p = 0.013).
Variation in screening was observed based on cancer type and disease status, indicating ongoing improvement targets.

Abstract

e23294 Background: Lack of diversity and low enrollment limit clinical trial success in gynecologic oncology. Providers represent an underutilized resource for trial recruitment. Methods: At a single urban academic institution, gyn onc clinic note templates for new and return visits were modified to include a clinical trial screening prompt (“This patient was considered for clinical trial:” yes/no). Implementation was guided by the RE-AIM framework. A retrospective pre- and post-implementation review evaluated provider screening and trial enrollment. Patients were identified using clinic location and ICD-10 codes for cervical, uterine, and ovarian cancers; all confirmed diagnoses were included. Collected variables included cancer status, age, sex, race/ethnicity, insurance, and provider type. Descriptive statistics summarized patient characteristics. Associations were assessed using Firth penalized logistic regression. Results: Screening increased significantly post-implementation (OR 3.63, 95% CI 1.92–7.12; p < 0.001). African American patients had higher odds than White patients (OR 3.88, 95% CI 1.28–19.1; p = 0.013), indicating improved equity. Screening was higher among recurrence visits versus at the time of new diagnoses (OR 7.22, 95% CI 3.74–14.0; p < 0.001) and lower among surveillance patients (OR 0.09, 95% CI 0.01–0.37; p < 0.001). Compared with ovarian cancer, cervical cancer had lower odds, while corpus uteri cancer showed no difference. Post-implementation, use of the tool was higher for new diagnoses (OR 1.71, 95% CI 1.08–2.71; p = 0.022) and recurrence (OR 4.53, 95% CI 2.27–9.34; p < 0.001) versus surveillance. Conclusions: EMR-based clinical trial prompts significantly increased screening in Gyn Onc clinics. Higher screening among African American patients suggests this low-cost intervention may reduce inequities. Variability by disease status and cancer type identifies targets for ongoing improvement. EMR-integrated prompts offer a scalable strategy to promote equitable trial access. Characteristic N Event N Event % OR 95% CI p-value Race/Ethnicity White 203 2 1.0% — — African American 706 32 4.5% 3.88 1.28, 19.11 0.013 Other 57 3 5.3% 5.18 0.98, 31.75 0.052 Hispanic 41 2 4.9% 5.10 0.77, 33.94 0.087 Unknown 20 2 10% 10.89 1.60, 74.47 0.018 Asian 16 0 0% 2.44 0.02, 31.70 0.606 Diagnosis Code C56.X: Malignant neoplasm of ovary 284 11 3.9% — — C54.X: Malignant neoplasm of corpus uteri 608 30 4.9% 1.25 0.64, 2.61 0.516 <

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