The enduring importance of family health history in the era of genomic medicine and risk assessment.
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2020-04-22
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Abstract
Improving disease risk prediction and tailoring preventive interventions to patient risk factors is one of the primary goals of precision medicine. Family health history is the traditional approach to quickly gather genetic and environmental data relevant to the patient. While the utility of family health history is well-documented, its utilization is variable, in part due to lack of patient and provider knowledge and incomplete or inaccurate data. With the advances and reduced costs of sequencing technologies, comprehensive sequencing tests can be performed as a risk assessment tool. We provide an overview of each of these risk assessment approaches, the benefits and limitations and implementation challenges.
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Haga, Susanne B, and Lori A Orlando (2020). The enduring importance of family health history in the era of genomic medicine and risk assessment. Per Med. 10.2217/pme-2019-0091 Retrieved from https://hdl.handle.net/10161/20584.
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Susanne B Haga
My research interests focus on issues affecting the translation of genomics to clinical practice. Specifically, I have a strong interest in education, with each of my research projects involving some component of professional, public or patient education, including development of educational materials about genomic research in general, pharmacogenetic testing, and communicating genetic test results, in addition to undergraduate teaching in genetics/genomics, ethics, and policy.
Areas of expertise: Bioethics and Health Behavior
Lori Ann Orlando
Dr. Lori A. Orlando, MD MHS MMCI is a Professor of Medicine and Director of the Precision Medicine Program in the Center for Applied Genomics and Precision Medicine at Duke University. She attended Tulane Medical Center for both medical school (1994-1998) and Internal Medicine residency (1998-2000). There she finished AOA and received a number of awards for teaching and clinical care from the medical school and the residency programs, including the Musser-Burch-Puschett award in 2000 for academic excellence. After completing her residency, she served as Chief Medical Resident in Internal Medicine (2001) and then completed a Health Services Research Fellowship at Duke University Medical Center (2002-2004). In 2004 she also received her MHS from the Clinical Research Training Program at Duke University and joined the academic faculty at Duke. In 2005 she received the Milton W. Hamolsky Award for Outstanding Junior Faculty by the Society of General Internal Medicine. Her major research interests are decision making and patient preferences, implementation research, risk stratification for targeting preventive health services, and decision modeling. From 2004-2009 she worked with Dr. David Matchar in the Center for Clinical Heath Policy Research (CCHPR), where she specialized in decision modeling, decision making, and technology assessments. In 2009 she began working with Dr. Geoffrey Ginsburg in what is now the Center for Applied Genomics and Precision Medicine (CAGPM) and in 2014 she became the director of the Center’s Precision Medicine Program. Since joining the CAGPM she has been leading the development and implementation of MeTree, a patient-facing family health history based risk assessment and clinical decision support program designed to facilitate the uptake of risk stratified evidence-based guidelines. MeTree was designed to overcome the major barriers to collecting and using high quality family health histories to guide clinical care and has been shown to be highly effective when integrated into primary care practices. This effort started with the Genomic Medicine Model, a multi-institutional project, whose goal was to implement personalized medicine in primary care practices. The success of that project has led to funding as part of NHGRI’s IGNITE (Implementing Genomics in Clinical Practice) network. She is currently testing methods for integrating patient preferences and decision making processes into clinical decision support recommendations for patients and providers to facilitate management of patients’ risk for chronic disease using mHealth and other behavioral interventions.
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