A Robust e-Epidemiology Tool in Phenotyping Heart Failure with Differentiation for Preserved and Reduced Ejection Fraction: the Electronic Medical Records and Genomics (eMERGE) Network.

Journal: Journal of cardiovascular translational research
Published Date: Jul 21, 2015

Abstract

Identifying populations of heart failure (HF) patients is paramount to research efforts aimed at developing strategies to effectively reduce the burden of this disease. The use of electronic medical record (EMR) data for this purpose is challenging given the syndromic nature of HF and the need to distinguish HF with preserved or reduced ejection fraction. Using a gold standard cohort of manually abstracted cases, an EMR-driven phenotype algorithm based on structured and unstructured data was developed to identify all the cases. The resulting algorithm was executed in two cohorts from the Electronic Medical Records and Genomics (eMERGE) Network with a positive predictive value of >95 %. The algorithm was expanded to include three hierarchical definitions of HF (i.e., definite, probable, possible) based on the degree of confidence of the classification to capture HF cases in a whole population whereby increasing the algorithm utility for use in e-Epidemiologic research.

Authors

  • Suzette J Bielinski
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA. bielinski.suzette@mayo.edu.
  • Jyotishman Pathak
    Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
  • David S Carrell
    Group Health Research Institute, Seattle, WA, 98101, USA.
  • Paul Y Takahashi
    Community Internal Medicine, Mayo Clinic, Rochester, MN, USA.
  • Janet E Olson
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Nicholas B Larson
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Hongfang Liu
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • Sunghwan Sohn
    Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, USA.
  • Quinn S Wells
    Department of Medicine, Vanderbilt University, Nashville, TN, 37232, USA.
  • Joshua C Denny
    Vanderbilt University, Nashville, TN.
  • Laura J Rasmussen-Torvik
    Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
  • Jennifer Allen Pacheco
    Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
  • Kathryn L Jackson
    Center for Healthcare Studies, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
  • Timothy G Lesnick
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Rachel E Gullerud
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Paul A Decker
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Naveen L Pereira
    Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA.
  • Euijung Ryu
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Richard A Dart
    Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI, 54449, USA.
  • Peggy Peissig
    Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI, 54449, USA.
  • James G Linneman
    Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI, 54449, USA.
  • Gail P Jarvik
    Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, 98195, USA.
  • Eric B Larson
    Group Health Research Institute, Seattle, WA, 98101, USA.
  • Jonathan A Bock
    The Sigfried and Janet Weis Center for Research, Geisinger Health System, Danville, PA, 17822, USA.
  • Gerard C Tromp
    The Sigfried and Janet Weis Center for Research, Geisinger Health System, Danville, PA, 17822, USA.
  • Mariza de Andrade
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Véronique L Roger
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.

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