Implementing Family Health History Risk Stratification in Primary Care: Impact of Guideline Criteria on Populations and Resource Demand

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Vincent C. Henrich, Professor (Creator)
The University of North Carolina at Greensboro (UNCG )
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Abstract: The Genomic Medicine Model aims to facilitate patient engagement, patient/provider education of genomics/personalized medicine, and uptake of risk-stratified evidence-based prevention guidelines using MeTree, a patient-facing family health history (FHH) collection and clinical decision support (CDS) program. Here we report the number of increased risk (above population-level risk) patients identified for breast/ovarian cancer, colon cancer, hereditary syndrome risk, and thrombosis; the prevalence of FHH elements triggering increased-risk status; and the resources needed to manage their risk. Study design: hybrid implementation-effectiveness study of adults with upcoming well-visits in 2 primary care practices in Greensboro, NC. Participants: 1,184, mean age?=?58.8, female?=?58% (N?=?694), non-white?=?20% (N?=?215). Increased Risk: 44% (N?=?523). Recommendations: genetic counseling?=?26% (N?=?308), breast MRI?=?0.8% (N?=?10), breast chemoprophylaxis?=?5% (N?=?58), early/frequent colonoscopies?=?19% (N?=?221), ovarian cancer screening referral?=?1% (N?=?14), thrombosis testing/counseling?=?2.4% (N?=?71). FHH elements: 8 FHH elements lead to 37.3% of the increased risk categorizations (by frequency): first-degree-relative (FDR) with polyps age =60 (7.1%, N?=?85), three relatives with Lynch-related cancers (5.4%, N?=?65), FDR with polyps age <60 (5.1%, N?=?61), three relatives on same side of family with same cancer (4.9%, N?=?59), Gail score =1.66% (4.9%, N?=?58), two relatives with breast cancer (one =age 50) (4.1%, N?=?49), one relative with breast cancer =age 40 (4.1%, N?=?48), FDR with colon cancer age =60 (1.7%, N?=?20). MeTree identifies a high percentage of individuals in the general primary care population needing non-routine risk management/prevention for the selected conditions. Implementing risk-stratification in primary care will likely increase demand for related-resources, particularly colon screening and GC. Understanding the prevalence of FHH elements helps predict resource needs and may aid in guideline development.

Additional Information

American Journal of Medical Genetics, Part C: Seminars in Medical Genetics, 166(1), 24-33
Language: English
Date: 2014
health services, risk stratification, family history, primary prevention

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