The Genomic Medicine Model: An Integrated Approach to Implementation of Family Health History in Primary Care
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Vincent C. Henrich, Professor (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
Abstract: As an essential tool for risk stratification, family health history (FHH) is a central component of personalized medicine; yet, despite its widespread acceptance among professional societies and its established place in the medical interview, its widespread adoption is hindered by three major barriers: quality of FHH collection, risk stratification capabilities and interpretation of risk stratification for clinical care. To overcome these barriers and bring FHH to the forefront of the personalized medicine effort, we developed the genomic medicine model (GMM) for primary care. The GMM, founded upon the principles of the Health Belief Model, Adult Learning Theory and the implementation sciences, shifts responsibility for FHH onto the patient, uses information technology (MeTree©) for risk stratification and interpretation, and provides education across multiple levels for each stakeholder, freeing up the clinical encounter for discussion around personalized preventive healthcare plans. The GMM has been implemented and optimized as part of an implementation-effectiveness hybrid pilot study for breast/ovarian cancer, colon cancer and thrombosis, and risk for hereditary cancer syndromes in two primary care clinics in NC, USA. This paper describes the conceptual development of the model and key findings relevant for broader uptake and sustainability in the primary care community.
The Genomic Medicine Model: An Integrated Approach to Implementation of Family Health History in Primary Care
PDF (Portable Document Format)
92 KB
Created on 12/10/2014
Views: 1898
Additional Information
- Publication
- Personalized Medicine, 10(3), 295-306
- Language: English
- Date: 2013
- Keywords
- community health, decision support, disease prevention, health education, risk assessment