Geisinger Health System (GHS) is an integrated, comprehensive health care delivery system that serves a large, stable, mainly rural population in north central and northeastern Pennsylvania. Geisinger has a fully functional and integrated electronic medical record (EMR) system, and is a recognized leader in the use of EMR and health information technology. GHS has received national accolades for its commitment to developing and testing information technology-enabled innovations in health care delivery. Geisinger's infrastructure and experience in this area provide a paradigm for incorporating genomic data into clinical care. To leverage the health system's assets for genomic medicine Geisinger launched an innovative biobanking program, the MyCode project that is creating a large, central repository of patient samples (blood, DNA, serum and tissue) that are linkable to data in the Geisinger EMR for broad research use in a manner that protects confidentiality of patient information. More than 30,000 Geisinger patients have consented to participate in the biobanking program. The EMR-linked biospecimen bank is being used for genomic research in cardiovascular disease, obesity, cancer, and other disorders with significant public health impact. Through this application GHS is seeking inclusion in the eMERGE Phase II.
The specific aims of this Geisinger eGenomic Medicine (GeM) program are to: 1) use existing biospecimens and EMR- generated phenotypes (ePhenotypes) to identify genetic variants associated with increased disease risk or altered treatment response;proposed new ePhenotypes are extreme obesity and related conditions, abdominal aortic aneurysm, and weight gain induced by anti-psychotic drugs;2) develop and test approaches to provide clinically relevant genetic research results to patients and clinical providers;and 3) study sociocultural concerns of patients residing in rural areas regarding Genomic Medicine research. Participation in eMERGE Phase II will substantially accelerate Geisinger's goal of using its integrated health care system, stable patient population, and advanced EMR capabilities to drive Personalized Health Care.

Public Health Relevance

The integration of genomic data into clinical practice is a necessary step in the adoption of Personalized Medicine;electronic medical record data have enormous potential to accelerate this process. Geisinger has a unique combination of resources and experience that make it an ideal setting for both the discovery and application phases of genomic medicine research and integration of genomic data into clinical care.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
3U01HG006382-02S2
Application #
8518008
Study Section
Special Emphasis Panel (ZHG1-HGR-N (M1))
Program Officer
Li, Rongling
Project Start
2011-08-15
Project End
2015-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
2
Fiscal Year
2012
Total Cost
$119,730
Indirect Cost
Name
Geisinger Clinic
Department
Type
DUNS #
079161360
City
Danville
State
PA
Country
United States
Zip Code
17822
Cutting, Elizabeth; Banchero, Meghan; Beitelshees, Amber L et al. (2016) User-centered design of multi-gene sequencing panel reports for clinicians. J Biomed Inform 63:1-10
Verma, Anurag; Verma, Shefali S; Pendergrass, Sarah A et al. (2016) eMERGE Phenome-Wide Association Study (PheWAS) identifies clinical associations and pleiotropy for stop-gain variants. BMC Med Genomics 9 Suppl 1:32
Rasmussen, Luke V; Overby, Casey L; Connolly, John et al. (2016) Practical considerations for implementing genomic information resources. Experiences from eMERGE and CSER. Appl Clin Inform 7:870-82
Garrison, Nanibaa' A; Sathe, Nila A; Antommaria, Armand H Matheny et al. (2016) A systematic literature review of individuals' perspectives on broad consent and data sharing in the United States. Genet Med 18:663-71
Homburger, Julian R; Green, Eric M; Caleshu, Colleen et al. (2016) Multidimensional structure-function relationships in human β-cardiac myosin from population-scale genetic variation. Proc Natl Acad Sci U S A 113:6701-6
Simonti, Corinne N; Vernot, Benjamin; Bastarache, Lisa et al. (2016) The phenotypic legacy of admixture between modern humans and Neandertals. Science 351:737-41
Van Driest, Sara L; Wells, Quinn S; Stallings, Sarah et al. (2016) Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records. JAMA 315:47-57
Smith, Maureen E; Sanderson, Saskia C; Brothers, Kyle B et al. (2016) Conducting a large, multi-site survey about patients' views on broad consent: challenges and solutions. BMC Med Res Methodol 16:162
Carey, David J; Fetterolf, Samantha N; Davis, F Daniel et al. (2016) The Geisinger MyCode community health initiative: an electronic health record-linked biobank for precision medicine research. Genet Med 18:906-13
Jackson, Kathryn L; Mbagwu, Michael; Pacheco, Jennifer A et al. (2016) Performance of an electronic health record-based phenotype algorithm to identify community associated methicillin-resistant Staphylococcus aureus cases and controls for genetic association studies. BMC Infect Dis 16:684

Showing the most recent 10 out of 59 publications