Extraction of Electronic Health Record Data using Fast Healthcare Interoperability Resources for Automated Breast Cancer Risk Assessment

Abstract

Women at high risk for breast cancer may benefit from enhanced screening and risk-reduction strategies. However, limited time during clinical encounters is one barrier to routine breast cancer risk assessment. We evaluated if electronic health record (EHR) data downloaded using Fast Healthcare Interoperability Resources (FHIR) is sufficient for breast cancer risk calculation in our decision support tools, RealRisks and BNAV. We accessed EHR data using FHIR for six patient advocates, and downloaded and parsed XML documents. We searched for relevant clinical variables, and evaluated if data was sufficient to calculate risk using validated models (Gail, Breast Cancer Screening Consortium [BCSC], BRCAPRO). While only one advocate had sufficient EHR data to calculate risk using the BCSC model only, we identified variables including age, race/ethnicity, mammographic density, and prior breast biopsy in most advocates. EHR data from FHIR could be incorporated into automated breast cancer risk calculation in clinical decision support tools.

Figure 1.

Example of a RealRisks patient-facing window for risk calculation using the BCSC model. Birthdate, race, and ethnicity (on the left) are automatically populated from the FHIR “Patient” resource. Family history of breast cancer in a first-degree relative was not auto-populated, and was documented as “unknown.” When family history is not available in the EHR, patients can enter this data by interacting with the pedigree generating function in RealRisks. On the right, variables including personal history of breast cancer or surgery, mammographic density, and prior breast biopsy were manually populated by the study team at the time of RealRisks account creation, and the patient is given the option to request changes in the current version.