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Luke Rasmussen Marshfield Clinic David Carrell, PhD Group Health Research Institute

CRI-09: Cross-Institutional Systems to Support Phenotyping in Biomedical Research: Experiences from the eMERGE Network. Luke Rasmussen Marshfield Clinic David Carrell, PhD Group Health Research Institute William Thompson, PhD Northwestern University Hua Xu, PhD Vanderbilt University

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Luke Rasmussen Marshfield Clinic David Carrell, PhD Group Health Research Institute

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  1. CRI-09: Cross-Institutional Systems to Support Phenotyping in Biomedical Research: Experiences from the eMERGE Network Luke RasmussenMarshfield Clinic David Carrell, PhDGroup Health Research Institute William Thompson, PhDNorthwestern University Hua Xu, PhDVanderbilt University Jyoti Pathak, PhDMayo Clinic AMIA CRI Summit 2011

  2. eMERGE Consortium Principal sponsor: NHGRI with additional funding from NIGMS NIH-funded consortium (CTSA awardee institutions) DNA Biobanks linked to EHR data Consortium members Group Health of Puget Sound Marshfield Clinic Mayo Clinic Northwestern University Vanderbilt University

  3. Cataracts Type II diabetes Dementia Coordinating center Peripheral vascular disease QRS duration

  4. Marshfield Clinic Biobank Population Geographically defined cohort Stable population Minimal selection bias Over 95% of medical events captured in EMR Data All levels of inpatient and outpatient care 5 decades of retrospective clinical data Prospective & continuous data collection via EHR Event, testing, treatment and outcomes represented High utilization of primary care to classify controls Clinical, financial and environment data Health Events

  5. eMERGE Contributors NHGRI Rongling Li Heather Junkins Teri Manolio Jim Ostell Group Health Eric Larson Gail Jarvik Chris Carlson Wylie Burke Gene Jart David Carrell Malia Fullerton Walter Kukull Paul Crane Noah Weston Northwestern Rex Chisholm Bill Lowe Phil Greenland Wendy Wolf Maureen Smith Geoff Hayes Pedro Avila Joel Humowiecki Jen Allen-Pacheco Amy Lemke Will Thompson Marshfield Cathy McCarty Peggy Peissig Luke Rasmussen Marilyn Ritchie Justin Starren Russ Wilke Dick Berg Jim Linneman Mayo Clinic Christopher G. Chute Iftikhar J. Kullo Barbara Koenig Suzette Bielinski Mariza de Andrade Vanderbilt Dan Roden Dan Masys Josh Denny Brad Malin Ellen Wright Clayton Dana Crawford Jonathan Haines Jonathan Schildcrout Jill Pulley Melissa Basford Marilyn Ritchie

  6. RFA HG-07-005:Genome-Wide Studies in Biorepositories with Electronic Medical Record Data 2007 NIH Request for Applications from the National Human Genome Research Institute “The purpose of this funding opportunity is to provide support for investigative groups affiliated with existing biorepositories to develop necessary methods and procedures for, and then to perform, if feasible, genome-wide studies in participants with phenotypes and environmental exposures derived from electronic medical records, with the aim of widespread sharing of the resulting individual genotype-phenotype data to accelerate the discovery of genes related to complex diseases.” (Emphasis added)

  7. Idea Issues More Ideas Develop Disseminate Development and Growth • Pre-existing and new systems/methods • Applied to common (yet different) tasks • Different locations/environments

  8. Tools and Methods

  9. Reusable Phenotype Algorithms Luke Rasmussen Senior Programmer/Analyst Marshfield Clinic Research Foundation Biomedical Informatics Research Center AMIA CRI Summit 2011

  10. Phenotype Development • Multi-disciplinary teams • Multiple sites • Iterative • Intangible →Tangible

  11. EMR-based Phenotype Algorithms • Typical components • Billing and diagnoses codes • Procedure codes • Labs • Medications • Phenotype-specific co-variates (e.g., Demographics, Vitals, Smoking Status, CASI scores) • Pathology • Imaging? • Organized into inclusion and exclusion criteria

  12. EMR-based Phenotype Algorithms Iteratively refine case definitions through partial manual review to achieve ~PPV ≥ 95% For controls, exclude all potentially overlapping syndromes and possible matches; iteratively refine such that ~NPV ≥ 98%

  13. Primary Phenotypes

  14. Supplemental Phenotypes * - Not available at this time

  15. Phenotype Reuse • T2DM  Diabetic Retinopathy • Identification of DM • T2DM included T1DM for exclusion • Low HDL Lipids

  16. Phenotype Reuse Diabetic Retinopathy T2DM

  17. Condition - Subtype A Condition - Subtype B Subtype A Subtype B Condition Iterative Refinement for Reuse

  18. Formalizing Reuse • Identified potential for reuse • Leverage significant work • Phenotypes available: www.gwas.org • Limitations • Site-specific implementations

  19. Impressions • Easy to do • Fits with eMERGE goals • Can fit retrospectively • Prospective mindset

  20. Thank You Luke Rasmussen rasmussen.luke@mcrf.mfldclin.edu AMIA CRI Summit 2011

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