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Genet Med. 2018 Jun;20(6):655-663. doi: 10.1038/gim.2017.144. Epub 2017 Sep 14.

Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group.

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Department of Medicine and The Center for Applied Genomics and Precision Medicine, Duke University, Durham, North Carolina, USA.
Center for Health Services Research in Primary Care, Veterans Affairs Medical Center, Durham, North Carolina, USA.
Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Department of Medicine and the Ingram Cancer Center, Vanderbilt University, Nashville, Tennessee, USA.
Department of Medicine, University of Maryland, Baltimore, Maryland, USA.
Department of Population Health Sciences and Policy and The Center for Health Equity and Community Engaged Research, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Department of Medicine, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, Florida, USA.
National Human Genome Research Institute, Bethesda, Maryland, USA.
Implementation Pathways, LLC, Ann Arbor, Michigan, USA.
VA Center for Clinical Management Research, Ann Arbor, Michigan, USA.


PurposeImplementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing Genomics in Practice (IGNITE) Network's efforts to promote (i) a broader understanding of genomic medicine implementation research and (ii) the sharing of knowledge generated in the network.MethodsTo facilitate this goal, the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide its approach to identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross-network analyses.ResultsCMG identified 10 high-priority CFIR constructs as important for genomic medicine. Of those, eight did not have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model.ConclusionWe developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field.

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