High-throughput multimodal automated phenotyping (MAP) with application to PheWAS.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Nov 1, 2019

Abstract

OBJECTIVE: Electronic health records linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the ability to phenotype patients accurately and efficiently. The objective of this study was to develop an automated high-throughput phenotyping method integrating International Classification of Diseases (ICD) codes and narrative data extracted using natural language processing (NLP).

Authors

  • Katherine P Liao
    Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States.
  • Jiehuan Sun
    Division of Data Sciences, VA Boston Healthcare System, Boston, MA, USA.
  • Tianrun A Cai
    Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Boston, MA, USA.
  • Nicholas Link
    Division of Data Sciences, VA Boston Healthcare System, Boston, MA, USA.
  • Chuan Hong
    Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
  • Jie Huang
    Department of Critical Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
  • Jennifer E Huffman
    Division of Data Sciences, VA Boston Healthcare System, Boston, MA, USA.
  • Jessica Gronsbell
    Department of Biomedical Data Science, Stanford University, Stanford, California.
  • Yichi Zhang
    Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Yuk-Lam Ho
    Division of Data Sciences, VA Boston Healthcare System, Boston, MA, USA.
  • Victor Castro
    Partners Healthcare Systems, Summerville, MA, USA.
  • Vivian Gainer
  • Shawn N Murphy
  • Christopher J O'Donnell
    Cardiology Section, Department of Medicine, Boston VA Healthcare, Boston, Massachusetts.
  • J Michael Gaziano
    Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Boston, MA, USA.
  • Kelly Cho
    Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Boston, MA, USA.
  • Peter Szolovits
    Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Isaac S Kohane
    Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. Isaac_Kohane@hms.harvard.edu.
  • Sheng Yu
    Medical College, Guangxi University of Science and Technology, Liuzhou, Guangxi, 545005, China.
  • Tianxi Cai
    Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States.

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