Making genomic medicine evidence-based and patient-centered: a structured review and landscape analysis of comparative effectiveness research.

Abstract

Comparative effectiveness research (CER) in genomic medicine (GM) measures the clinical utility of using genomic information to guide clinical care in comparison to appropriate alternatives. We summarized findings of high-quality systematic reviews that compared the analytic and clinical validity and clinical utility of GM tests. We focused on clinical utility findings to summarize CER-derived evidence about GM and identify evidence gaps and future research needs. We abstracted key elements of study design, GM interventions, results, and study quality ratings from 21 systematic reviews published in 2010 through 2015. More than half (N = 13) of the reviews were of cancer-related tests. All reviews identified potentially important clinical applications of the GM interventions, but most had significant methodological weaknesses that largely precluded any conclusions about clinical utility. Twelve reviews discussed the importance of patient-centered outcomes, although few described evidence about the impact of genomic medicine on these outcomes. In summary, we found a very limited body of evidence about the effect of using genomic tests on health outcomes and many evidence gaps for CER to address.Genet Med advance online publication 13 April 2017Genetics in Medicine (2017); doi:10.1038/gim.2017.21.

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Published Version (Please cite this version)

10.1038/gim.2017.21

Publication Info

Phillips, Kathryn A, Patricia A Deverka, Harold C Sox, Muin J Khoury, Lewis G Sandy, Geoffrey S Ginsburg, Sean R Tunis, Lori A Orlando, et al. (2017). Making genomic medicine evidence-based and patient-centered: a structured review and landscape analysis of comparative effectiveness research. Genet Med. 10.1038/gim.2017.21 Retrieved from https://hdl.handle.net/10161/14222.

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Scholars@Duke

Ginsburg

Geoffrey Steven Ginsburg

Adjunct Professor in the Department of Medicine

Dr. Geoffrey S. Ginsburg's research interests are in the development of novel paradigms for developing and translating genomic information into medical practice and the integration of personalized medicine into health care.

Orlando

Lori Ann Orlando

Professor of Medicine

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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