Reducing effort through informatics-driven identification, recruitment, and data capture on a trial to improve adjuvant endocrine therapy adherence.

A Ahauve Orusa (Mayo Clinic Rochester, Rochester, MN) J Joan Marie Neuner (Medical College of Wisconsin, Milwaukee, WI) K Kathryn Jean Ruddy (Department of Oncology, Mayo Clinic Rochester, Rochester, MN) B Becca Benoy (Medical College of Wisconsin, Milwaukee, WI) D David Huschka (Mayo Clinic Rochester, Rochester, MN) R Rama Volety (Mayo Clinic Rochester, Rochester, MN) N Nicole Larson (Mayo Clinic Rochester, Rochester, MN) V Victoria Dolmann (Mayo Clinic Rochester, Rochester, MN) J Jodi L. Taraba (Mayo Clinic Rochester, Rochester, MN) K Kathryn E. Flynn (Department of Medicine, Medical College of Wisconsin, Milwaukee, WI) A Amye Juliet Tevaarwerk (Mayo Clinic Rochester, Rochester, MN)

Abstract

11025 Background: Adjuvant endocrine therapy (AET) improves outcomes in HR+ breast cancer. Nonadherence to AET is common, but manual screening for nonadherence is fraught. High-specificity structured cancer electronic health record (EHR) data, particularly if it includes key variables like stage, could streamline these steps for both clinical care and research purposes. We conducted an analysis of approaches to identifying patients as eligible for a multi-site AET adherence study to understand how variation in structured data informatics-supported screening impacts coordinator time. Methods: Mayo Clinic implemented a two-step identification: (1) EHR structured data (diagnosis date, stage, ER/PR/HER2 positivity, medication script) to prescreen for eligibility; (2) SureScripts fills to flag nonadherence using proportion of days covered < 80% across early fills. Medical College of Wisconsin (MCW) implemented a more manual screening process for Step 1 using only medication scripts. Coordinators at both sites then conducted a medical record review to assess if the resulting list of patients had a plan to continue AET for at least two additional years. Opt-out clinician permission preceded patient contact; pharmacists delivered a patient reported outcome (PRO)-guided intervention and documented encounters. Results: At Mayo, 829 patients were prescreened for study eligibility through informatics workflow; 120 (14.5%) met eligibility criteria. At MCW, 1,763 patients were prescreened; 168 (9.5%) were eligible. EHR filters included non–breast cancer encounters (50% at MCW) and ineligible based on time since cancer (36% at Mayo; 26% at MCW). At Mayo, screening required 5.6 minutes/patient for experienced coordinators. At MCW, experienced coordinators averaged 6.67 minutes/patient and inexperienced coordinators averaged 9.33 minutes/patient. Conclusions: Structured EHR data, pharmacy-fill information, and standardized workflows allowed consistent prescreening, intervention and recruitment processes across sites. Higher-specificity informatics-supported screening reduced the percentage of patients requiring manual review and reduced coordinator screening time. It also supported timely provider-permission steps and patient outreach. These workflows were feasible to implement at both institutions, and study enrollment is ongoing. Clinical trial information: NCT06765707 .

Article Details

Volume / Issue Vol. 44, Issue 16_suppl
Published June 01, 2026
Pages 11025-11025
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (11)

A

Ahauve Orusa

Mayo Clinic Rochester, Rochester, MN

J

Joan Marie Neuner

Medical College of Wisconsin, Milwaukee, WI

K

Kathryn Jean Ruddy

Department of Oncology, Mayo Clinic Rochester, Rochester, MN

B

Becca Benoy

Medical College of Wisconsin, Milwaukee, WI

D

David Huschka

Mayo Clinic Rochester, Rochester, MN

R

Rama Volety

Mayo Clinic Rochester, Rochester, MN

N

Nicole Larson

Mayo Clinic Rochester, Rochester, MN

V

Victoria Dolmann

Mayo Clinic Rochester, Rochester, MN

J

Jodi L. Taraba

Mayo Clinic Rochester, Rochester, MN

K

Kathryn E. Flynn

Department of Medicine, Medical College of Wisconsin, Milwaukee, WI

A

Amye Juliet Tevaarwerk

Mayo Clinic Rochester, Rochester, MN