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.
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.
|El Rouby, Nihal; McDonough, Caitrin W; Gong, Yan et al. (2018) Genome-wide association analysis of common genetic variants of resistant hypertension. Pharmacogenomics J :|
|Mosley, Jonathan D; Feng, QiPing; Wells, Quinn S et al. (2018) A study paradigm integrating prospective epidemiologic cohorts and electronic health records to identify disease biomarkers. Nat Commun 9:3522|
|Antommaria, Armand H Matheny; Brothers, Kyle B; Myers, John A et al. (2018) Parents' attitudes toward consent and data sharing in biobanks: A multisite experimental survey. AJOB Empir Bioeth 9:128-142|
|Almoguera, Berta; Vazquez, Lyam; Mentch, Frank et al. (2017) Identification of Four Novel Loci in Asthma in European American and African American Populations. Am J Respir Crit Care Med 195:456-463|
|Holzinger, Emily R; Verma, Shefali S; Moore, Carrie B et al. (2017) Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min 10:25|
|Rasmussen-Torvik, Laura J; Almoguera, Berta; Doheny, Kimberly F et al. (2017) Concordance between Research Sequencing and Clinical Pharmacogenetic Genotyping in the eMERGE-PGx Study. J Mol Diagn 19:561-566|
|Rohrer Vitek, Carolyn R; Abul-Husn, Noura S; Connolly, John J et al. (2017) Healthcare provider education to support integration of pharmacogenomics in practice: the eMERGE Network experience. Pharmacogenomics 18:1013-1025|
|Peissig, Peggy; Schwei, Kelsey M; Kadolph, Christopher et al. (2017) Prototype Development: Context-Driven Dynamic XML Ophthalmologic Data Capture Application. JMIR Med Inform 5:e27|
|Sanderson, Saskia C; Brothers, Kyle B; Mercaldo, Nathaniel D et al. (2017) Public Attitudes toward Consent and Data Sharing in Biobank Research: A Large Multi-site Experimental Survey in the US. Am J Hum Genet 100:414-427|
|Nadkarni, Girish N; Galarneau, Geneviève; Ellis, Stephen B et al. (2017) Apolipoprotein L1 Variants and Blood Pressure Traits in African Americans. J Am Coll Cardiol 69:1564-1574|
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