Longitudinal cohorts for harnessing the electronic health record for disease prediction in a US population.

Journal: BMJ open
Published Date: Jun 8, 2021

Abstract

PURPOSE: The depth and breadth of clinical data within electronic health record (EHR) systems paired with innovative machine learning methods can be leveraged to identify novel risk factors for complex diseases. However, analysing the EHR is challenging due to complexity and quality of the data. Therefore, we developed large electronic population-based cohorts with comprehensive harmonised and processed EHR data.

Authors

  • Sheila M Manemann
    Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Jennifer L St Sauver
    Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Hongfang Liu
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • Nicholas B Larson
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Sungrim Moon
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • 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.
  • Walter A Rocca
    Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Virginia M Miller
    Mayo Clinic Women's Health Research Center, Mayo Clinic, Rochester, Minnesota, USA.
  • Terry M Therneau
    Department of Health Science Research, Mayo Clinic, MN, USA.
  • Che G Ngufor
    Mayo Clinic Rochester, Rochester, MN.
  • Véronique L Roger
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Yiqing Zhao
    Department of Health Informatics and Administration, Center for Biomedical Data and Language Processing, University of Wisconsin-Milwaukee, 2025 E Newport Ave, NWQ-B Room 6469, Milwaukee, WI, 53211, USA.
  • Paul A Decker
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Jill M Killian
    Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Suzette J Bielinski
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA. bielinski.suzette@mayo.edu.

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