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Publication Detail
The Genomic Medicine Integrative Research Framework: A Conceptual Framework for Conducting Genomic Medicine Research.
  • Publication Type:
    Journal article
  • Publication Sub Type:
  • Authors:
    Horowitz CR, Orlando LA, Slavotinek AM, Peterson J, Angelo F, Biesecker B, Bonham VL, Cameron LD, Fullerton SM, Gelb BD, Goddard KAB, Hailu B, Hart R, Hindorff LA, Jarvik GP, Kaufman D, Kenny EE, Knight SJ, Koenig BA, Korf BR, Madden E, McGuire AL, Ou J, Wasserstein MP, Robinson M, Leventhal H, Sanderson SC
  • Publication date:
  • Journal:
    Am J Hum Genet
  • Status:
    Published online
  • Country:
    United States
  • PII:
  • Language:
  • Keywords:
    conceptual, diversity, framework, genomics, implementation, model, translational research
Conceptual frameworks are useful in research because they can highlight priority research domains, inform decisions about interventions, identify outcomes and factors to measure, and display how factors might relate to each other to generate and test hypotheses. Discovery, translational, and implementation research are all critical to the overall mission of genomic medicine and prevention, but they have yet to be organized into a unified conceptual framework. To fill this gap, our diverse team collaborated to develop the Genomic Medicine Integrative Research (GMIR) Framework, a simple but comprehensive tool to aid the genomics community in developing research questions, strategies, and measures and in integrating genomic medicine and prevention into clinical practice. Here we present the GMIR Framework and its development, along with examples of its use for research development, demonstrating how we applied it to select and harmonize measures for use across diverse genomic medicine implementation projects. Researchers can utilize the GMIR Framework for their own research, collaborative investigations, and clinical implementation efforts; clinicians can use it to establish and evaluate programs; and all stakeholders can use it to help allocate resources and make sure that the full complexity of etiology is included in research and program design, development, and evaluation.
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