. 2021 Jul 8;11(7):647.

doi: 10.3390/jpm11070647.

Strategies to Integrate Genomic Medicine into Clinical Care: Evidence from the IGNITE Network

Nina R Sperber^{1

2

3}, Olivia M Dong³, Megan C Roberts⁴, Paul Dexter⁵, Amanda R Elsey⁶, Geoffrey S Ginsburg³, Carol R Horowitz⁷, Julie A Johnson⁶, Kenneth D Levy⁸, Henry Ong⁹, Josh F Peterson⁹, Toni I Pollin¹⁰, Tejinder Rakhra-Burris³, Michelle A Ramos¹¹, Todd Skaar⁸, Lori A Orlando³

Affiliations

¹ Duke Department of Population Health Sciences, Duke University School of Medicine, Durham, NC 27701, USA.
² Durham VA Health Care System, Durham, NC 27705, USA.
³ Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA.
⁴ Division of Pharmaceutical Outcomes and Policy, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
⁵ Regenstrief Institute, Indianapolis, Indiana University School of Medicine and Clem McDonald Center for Biomedical Informatics, Indianapolis, IN 46202, USA.
⁶ Center for Pharmacogenomics and Precision Medicine, Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL 32610, USA.
⁷ Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
⁸ Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, 950 W. Walnut Street, Indianapolis, IN 46202, USA.
⁹ Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
¹⁰ Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
¹¹ Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

PMID: 34357114
PMCID: PMC8306482
DOI: 10.3390/jpm11070647

Strategies to Integrate Genomic Medicine into Clinical Care: Evidence from the IGNITE Network

Nina R Sperber et al. J Pers Med. 2021.

. 2021 Jul 8;11(7):647.

doi: 10.3390/jpm11070647.

Authors

Affiliations

¹ Duke Department of Population Health Sciences, Duke University School of Medicine, Durham, NC 27701, USA.
² Durham VA Health Care System, Durham, NC 27705, USA.
³ Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA.
⁴ Division of Pharmaceutical Outcomes and Policy, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
⁵ Regenstrief Institute, Indianapolis, Indiana University School of Medicine and Clem McDonald Center for Biomedical Informatics, Indianapolis, IN 46202, USA.
⁶ Center for Pharmacogenomics and Precision Medicine, Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL 32610, USA.
⁷ Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
⁸ Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, 950 W. Walnut Street, Indianapolis, IN 46202, USA.
⁹ Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
¹⁰ Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
¹¹ Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

PMID: 34357114
PMCID: PMC8306482
DOI: 10.3390/jpm11070647

Abstract

The complexity of genomic medicine can be streamlined by implementing some form of clinical decision support (CDS) to guide clinicians in how to use and interpret personalized data; however, it is not yet clear which strategies are best suited for this purpose. In this study, we used implementation science to identify common strategies for applying provider-based CDS interventions across six genomic medicine clinical research projects funded by an NIH consortium. Each project's strategies were elicited via a structured survey derived from a typology of implementation strategies, the Expert Recommendations for Implementing Change (ERIC), and follow-up interviews guided by both implementation strategy reporting criteria and a planning framework, RE-AIM, to obtain more detail about implementation strategies and desired outcomes. We found that, on average, the three pharmacogenomics implementation projects used more strategies than the disease-focused projects. Overall, projects had four implementation strategies in common; however, operationalization of each differed in accordance with each study's implementation outcomes. These four common strategies may be important for precision medicine program implementation, and pharmacogenomics may require more integration into clinical care. Understanding how and why these strategies were successfully employed could be useful for others implementing genomic or precision medicine programs in different contexts.

Keywords: clinical decision support; genomic medicine; implementation science.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

**Figure 1**
Number of ERIC implementation strategies used by IGNITE implementation project.

**Figure 2**
Number of projects implementing each of the 72 ERIC strategies.

See this image and copyright information in PMC

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Strategies to Integrate Genomic Medicine into Clinical Care: Evidence from the IGNITE Network

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Strategies to Integrate Genomic Medicine into Clinical Care: Evidence from the IGNITE Network

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