Journal of Pathology Informatics Journal of Pathology Informatics
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RESEARCH ARTICLE
Year : 2015  |  Volume : 6  |  Issue : 1  |  Page : 50

Practical considerations in genomic decision support: The eMERGE experience


1 Department of Preventive Medicine, Division of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
2 Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
3 The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine, Mount Sinai, New York, USA
4 Division of Genetics and Endocrinology, Cook Children's Medical Center, Fort Worth, Texas, USA
5 Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
6 Division of General Internal Medicine, Johns Hopkins University, Baltimore, Maryland, USA
7 Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
8 Department of Biomedical Informatics, Vanderbilt University, Baltimore, MD, USA
9 Department of Pediatrics, The Children's Hospital of Philadelphia, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
10 Group Health Research Institute, Seattle, Washington, USA
11 Department of Biomedical Informatics, Columbia University Medical Center, New York, USA
12 Icahn School of Medicine, Mount Sinai, New York, USA
13 Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
14 Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
15 Nationwide Children's Hospital, Columbus, Ohio, USA
16 Department of Pharmacy, Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA
17 Department of Pediatrics, University of Cincinnati College of Medicine, Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
18 University of Maryland School of Medicine, Baltimore, Maryland, USA
19 Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
20 Vanderbilt University School of Medicine, Nashville, Tennessee, USA
21 Weis Center for Research, Geisinger Clinic, Danville, Pennsylvania, USA
22 Molecular Pathology, Mashfield Labs, Marshfield, Wisconsin, USA
23 Department of Biomedical Informatics, Columbia University, New York, USA
24 Department of Pediatrics, Harvard Medical School, Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA
25 Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA

Correspondence Address:
Timothy M Herr
Department of Preventive Medicine, Division of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, Illinois
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2153-3539.165999

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Background: Genomic medicine has the potential to improve care by tailoring treatments to the individual. There is consensus in the literature that pharmacogenomics (PGx) may be an ideal starting point for real-world implementation, due to the presence of well-characterized drug-gene interactions. Clinical Decision Support (CDS) is an ideal avenue by which to implement PGx at the bedside. Previous literature has established theoretical models for PGx CDS implementation and discussed a number of anticipated real-world challenges. However, work detailing actual PGx CDS implementation experiences has been limited. Anticipated challenges include data storage and management, system integration, physician acceptance, and more. Methods: In this study, we analyzed the experiences of ten members of the Electronic Medical Records and Genomics (eMERGE) Network, and one affiliate, in their attempts to implement PGx CDS. We examined the resulting PGx CDS system characteristics and conducted a survey to understand the unanticipated implementation challenges sites encountered. Results: Ten sites have successfully implemented at least one PGx CDS rule in the clinical setting. The majority of sites elected to create an Omic Ancillary System (OAS) to manage genetic and genomic data. All sites were able to adapt their existing CDS tools for PGx knowledge. The most common and impactful delays were not PGx-specific issues. Instead, they were general IT implementation problems, with top challenges including team coordination/communication and staffing. The challenges encountered caused a median total delay in system go-live of approximately two months. Conclusions: These results suggest that barriers to PGx CDS implementations are generally surmountable. Moreover, PGx CDS implementation may not be any more difficult than other healthcare IT projects of similar scope, as the most significant delays encountered were not unique to genomic medicine. These are encouraging results for any institution considering implementing a PGx CDS tool, and for the advancement of genomic medicine.


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