Abstract P1-11-02: Identifying women at high-risk for breast cancer in the primary care setting

Abstract

Abstract Background: Breast cancer risk assessment and available interventions for prevention, such as chemoprevention, are underutilized in the U.S. Reasons for low uptake include inability to routinely identify high-risk women in the primary care setting, inadequate time for counseling, and insufficient knowledge about risk-reducing strategies among primary care providers (PCPs) and patients. Our goal is to expand breast cancer risk counseling to a broader population of high-risk women identified in the primary care setting by developing a novel breast cancer risk navigation (BNAV) tool integrated into the electronic health record (EHR). Methods: We propose to design the BNAV tool for PCPs, by integrating the Gail breast cancer risk assessment tool into the EHR. Our goal is to facilitate clinic workflow for the identification of high-risk women (5-year risk ≥1.7% or lifetime risk ≥20%), who may be referred for specialized risk counseling. We conducted recorded focus groups and individual interviews of PCPs (N = 20-25) at Columbia University Medical Center (CUMC), including internists, family practitioners, and gynecologists who use an EHR and see female patients, age 40-70 years, in the outpatient setting. We performed user analyses of PCPs on the characteristics of their practice and their clinic workflow. Information about the aims of BNAV and the development process were provided and PCPs were given an opportunity to ask questions and discuss the relative merits of BNAV and its potential application to clinical practice. Providers also completed a questionnaire to provide quantitative and qualitative feedback on BNAV. Verbal and written qualitative responses were condensed into themes using a qualitative approach based on grounded theory. Results: In terms of breast cancer risk assessment, few providers routinely assessed for breast cancer risk factors apart from family history. Although some were familiar with the Gail model, no one used the risk calculator in their practice. Many PCPs were concerned about the added burden of incorporating the Gail model into the clinic visit. Potential solutions included screening for high-risk women during mammography and having patients complete the Gail model while in the waiting rooms. Most PCPs preferred referring high-risk women for specialized risk counseling, rather than directly discussing chemoprevention with their patients. Results from our interviews informed the selection of electronic resources to configure the BNAV tool. Using an open application programming interface within the EHR, the BNAV tool will incorporate the following approaches to workflow integration: 1) external decision support plug-ins for risk calculation; 2) dashboards with informatics-enabled summaries of patient history and breast cancer risk factors; 3) extracting data already available in the EHR for the Gail model breast cancer risk calculation; 4) alerts indicating high-risk patients should be referred for specialized risk counseling; 5) semi-structured referral orders for high-risk consultations. Discussion: PCPs are on the front lines of preventive medicine and initiating the appropriate high-risk referrals. We propose to use health information technology methods to overcome barriers to breast cancer chemoprevention in the primary care setting. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P1-11-02.