Study protocol: a cluster randomized controlled trial of web-based decision support tools for increasing BRCA1/2 genetic counseling referral in primary care.

BACKGROUND: BRCA1 and BRCA2 mutations confer a substantial breast risk of developing breast cancer to those who carry them. For this reason, the United States Preventative Services Task Force (USPSTF) has recommended that all women be screened in the primary care setting for a family history indicative of a mutation, and women with strong family histories of breast or ovarian cancer be referred to genetic counseling. However, few high-risk women are being routinely screened and fewer are referred to genetic counseling. To address this need we have developed two decision support tools that are integrated into clinical care. METHOD: This study is a cluster randomized controlled trial of high-risk patients and their health care providers. Patient-provider dyads will be randomized to receive either standard education that is supplemented with the patient-facing decision aid, RealRisks, and the provider-facing Breast Cancer Risk Navigation Toolbox (BNAV) or standard education alone. We will assess these tools' effectiveness in promoting genetic counseling uptake and informed and shared decision making about genetic testing. DISCUSSION: If found to be effective, these tools can help integrate genomic risk assessment into primary care and, ultimately, help expand access to risk-appropriate breast cancer prevention options to a broader population of high-risk women. TRIAL REGISTRATION: This trial is retrospectively registered with ClinicalTrials.gov Identifier: NCT03470402 : 20 March 2018.

Content Coverage Evaluation of the OMOP Vocabulary on the Transplant Domain Focusing on Concepts Relevant for Kidney Transplant Outcomes Analysis.

BACKGROUND: Improving outcomes of transplant recipients within and across transplant centers is important with the increasing number of organ transplantations being performed. The current practice is to analyze the outcomes based on patient level data submitted to the United Network for Organ Sharing (UNOS). Augmenting the UNOS data with other sources such as the electronic health record will enrich the outcomes analysis, for which a common data model (CDM) can be a helpful tool for transforming heterogeneous source data into a uniform format. OBJECTIVES: In this study, we evaluated the feasibility of representing concepts from the UNOS transplant registry forms with the Observational Medical Outcomes Partnership (OMOP) CDM vocabulary to understand the content coverage of OMOP vocabulary on transplant-specific concepts. METHODS: Two annotators manually mapped a total of 3,571 unique concepts extracted from the UNOS registry forms to concepts in the OMOP vocabulary. Concept mappings were evaluated by (1) examining the agreement among the initial two annotators and (2) investigating the number of UNOS concepts not mapped to a concept in the OMOP vocabulary and then classifying them. A subset of mappings was validated by clinicians. RESULTS: There was a substantial agreement between annotators with a kappa score of 0.71. We found that 55.5% of UNOS concepts could not be represented with OMOP standard concepts. The majority of unmapped UNOS concepts were categorized into transplant, measurement, condition, and procedure concepts. CONCLUSION: We identified categories of unmapped concepts and found that some transplant-specific concepts do not exist in the OMOP vocabulary. We suggest that adding these missing concepts to OMOP would facilitate further research in the transplant domain.

Identifying Women at High Risk for Breast Cancer Using Data From the Electronic Health Record Compared With Self-Report.

PURPOSE: A barrier to chemoprevention uptake among high-risk women is the lack of routine breast cancer risk assessment in the primary care setting. We calculated breast cancer risk using the Breast Cancer Surveillance Consortium (BCSC) model, accounting for age, race/ethnicity, first-degree family history of breast cancer, benign breast disease, and mammographic density, using data collected from the electronic health records (EHRs) and self-reports. PATIENTS AND METHODS: Among women undergoing screening mammography, we enrolled those age 35 to 74 years without a prior history of breast cancer. Data on demographics, first-degree family history, breast radiology, and pathology reports were extracted from the EHR. We assessed agreement between the EHR and self-report on information about breast cancer risk. RESULTS: Among 9,514 women with known race/ethnicity, 1,443 women (15.2%) met high-risk criteria based upon a 5-year invasive breast cancer risk of 1.67% or greater according to the BCSC model. Among 1,495 women with both self-report and EHR data, more women with a first-degree family history of breast cancer (14.6% v 4.4%) and previous breast biopsies (21.3% v 11.3%) were identified by self-report versus EHR, respectively. However, more women with atypia and lobular carcinoma in situ were identified from the EHR. There was moderate agreement in identification of high-risk women between EHR and self-report data (κ, 0.48; 95% CI, 0.42-0.54). CONCLUSION: By using EHR data, we determined that 15% of women undergoing screening mammography had a high risk for breast cancer according to the BCSC model. There was moderate agreement between information on breast cancer risk derived from the EHR and self-report. Examining EHR data may serve as an initial screen for identifying women eligible for breast cancer chemoprevention.

Study protocol: Randomized controlled trial of web-based decision support tools for high-risk women and healthcare providers to increase breast cancer chemoprevention.

BACKGROUND: Chemoprevention using selective estrogen receptor modulators and aromatase inhibitors has been shown to reduce invasive breast cancer incidence in high-risk women. Despite this evidence, few high-risk women who are eligible for chemoprevention utilize it as a risk-reducing strategy. Reasons for low uptake include inadequate knowledge about chemoprevention among patients and healthcare providers, concerns about side effects, time constraints during the clinical encounter, and competing comorbidities. METHODS/DESIGN: We describe the study design of a randomized controlled trial examining the effect of two web-based decision support tools on chemoprevention decision antecedents and quality, referral for specialized counseling, and chemoprevention uptake among women at an increased risk for breast cancer. The trial is being conducted at a large, urban medical center. A total of 300 patients and 50 healthcare providers will be recruited and randomized to standard educational materials alone or in combination with the decision support tools. Patient reported outcomes will be assessed at baseline, one and six months after randomization, and after their clinic visit with their healthcare provider. DISCUSSION: We are conducting this trial to provide evidence on how best to support personalized breast cancer risk assessment and informed and shared decision-making for chemoprevention. We propose to integrate the decision support tools into clinical workflow, which can potentially expand quality decision-making and chemoprevention uptake. TRIAL REGISTRATION: NCT03069742.

An Applied Framework in Support of Shared Decision Making about BRCA Genetic Testing.

The United States Preventive Services Taskforce recommends that primary care providers screen patients for an increased risk of carrying a BRCA1 or BRCA2 mutation and refer those who meet family history criteria to genetic counseling. Such screening requires detailed and accurate family history data, which often goes uncollected during a primary care visit due to time constraints, competing priorities, and lack of awareness on behalf of both patients and providers. In order to address these barriers and promote appropriate genetic counseling referral, we developed a user-centered framework that collects and communicates relevant data in order to prepare patients and their primary care providers for an informed discussion on genetic counseling referral. This paper describes this framework and the underlining data schema that makes it possible.

Automatic Genetic Risk Assessment Calculation Using Breast Cancer Family History Data from the EHR compared to Self-Report.

Genetic testing is a method to assess hereditary cancer risk. However, it is under-utilized and various methods of family history intake have been evaluated in previous studies. The six-point-scale (SPS) is a validated family history screener that is used to determine eligibility for BRCA genetic counseling. We automated the calculation of the SPS score using structured family history data along with free text from the electronic health record (EHR) to detect detailed family history information of breast cancer. We extracted data for all women aged 35 to 74 who had screening mammography at Columbia University Medical Center (CUMC) from January 2015 to May 2017 (N=37,596). After we calculated SPS scores using structured and free-text EHR data, we compared the results with SPS score calculated from a baseline survey conducted for a prospective study called Know Your Risks: Assessment at Screening (KYRAS). Among 1,202 patients with EHR structured family history data, we found 1.43% had an SPS score of 6 higher which meets criteria for genetic counseling referral, while 12.05% of the survey respondents had SPS score of 6 or higher. Results show there is a need for more efficient methods to identify patients eligible for genetic counseling through EHR analysis.