Despite advances in identifying genetic markers of high risk patients and the availability of genetic testing, it remains challenging to efficiently identify women who are at hereditary risk and to manage their care appropriately. HughesRiskApps, an open-source family history collection, risk assessment, and Clinical Decision Support (CDS) software package, was developed to address the shortcomings in our ability to identify and treat the high risk population. This system is designed for use in primary care clinics, breast centers, and cancer risk clinics to collect family history and risk information and provide the necessary CDS to increase quality of care and efficiency. This paper reports on the first implementation of HughesRiskApps in the community hospital setting. HughesRiskApps was implemented at the Newton-Wellesley Hospital. Between April 1, 2007 and March 31, 2008, 32,966 analyses were performed on 25,763 individuals. Within this population, 915 (3.6%) individuals were found to be eligible for risk assessment and possible genetic testing based on the 10% risk of mutation threshold. During the first year of implementation, physicians and patients have fully accepted the system, and 3.6% of patients assessed have been referred to risk assessment and consideration of genetic testing. These early results indicate that the number of patients identified for risk assessment has increased dramatically and that the care of these patients is more efficient and likely more effective.

The American Cancer Society (ACS) guidelines define the appropriate use of MRI as an adjunct to mammography for breast cancer screening. Three risk assessment models are recommended to determine if women are at sufficient risk to warrant the use of this expensive screening tool, however, the real-world application of these models has not been explored. We sought to understand how these models behave in a community setting for women undergoing mammography screening. We conducted a retrospective analysis of 5,894 women, who received mammography screening at a community hospital and assessed their eligibility for MRI according to the ACS guidelines. Of the 5,894 women, 342 (5.8%) were eligible for MRI, but we found significant differences in the number of eligible women identified by each model. Our results indicate that these models identify very different populations, implying that the ACS guidelines deserve further development and consideration. Cancer Epidemiol Biomarkers Prev; 22(1);