Huschka, David J.

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 .

431 Background: The National Adult and Influenza Immunization Summit (NAIIS) promoted clinical subspecialist efforts toward vaccination assessment and recommendation as one strategy to increase adult vaccination rates. Problem Statement: Between August 1, 2022, and May 31, 2023, 0% (n=0/100) of patients seen in medical oncology at Mayo Clinic (Rochester, MN) and receiving chemotherapy for breast cancer had a documented comprehensive vaccination status assessment by breast medical oncology staff. Aim Statements: (1) To increase the rate of comprehensive vaccination status assessment performed by breast medical oncology staff from 0% to 75% of patients receiving chemotherapy for breast cancer by September 2024. (2) To increase the rate of documented vaccination recommendation for patients who were not up to date with recommended vaccinations from 0% to 50% by September 2024. Methods: We deployed multiple interventions including physician and nurse education; development of patient education materials; and a standard operating procedure (SOP) for vaccination status assessment, vaccination recommendation, and vaccine-related documentation. Our SOP utilized an Epic SmartPhrase with following elements: (1) SmartLink that autopopulated overdue vaccinations, (2) hidden tip text permitting the use to hyperlink to Health Maintenance, (3) SmartLists that captured nurse actions (e.g., provided education) and encounter outcomes (e.g., patient endorsed plans to receive vaccinations), and (4) scripting for immunization education. Results: Multi-faceted interventions were associated with an improvement in the documented rate of comprehensive vaccination status assessment from 0% (n=0/100) to 82.8% (n=101/122). Most patients (77.2%, n=78/101) were not up to date with recommended vaccinations. Recommendations for appropriate vaccinations were made for 80.8% (n=63/78) of patients who were not up to date. Only 19.2% (n=15/78) of patients who were not up to date endorsed intention to receive missing/recommended vaccines. Counterbalance: Nurses were able to assess vaccination status and make appropriate recommendations in less than 5 minutes per patient. There was no difference in nurse-reported workflow burden related to vaccination status assessment, recommendation, or documentation after intervention. Conclusions: This quality project aligned our breast medical oncology practice with vaccination-related care promoted by NAIIS. We increased rates of vaccination status assessment and vaccination recommendations without impacting nurse-reported workflow burden. Medical subspecialty clinic engagement in vaccination efforts is feasible.