An Extraction Tool for Venous Thromboembolism Symptom Identification in Primary Care Notes to Facilitate Electronic Clinical Quality Measure Reporting: Algorithm Development and Validation Study.

Journal: JMIR medical informatics
Published Date: Aug 26, 2025

Abstract

BACKGROUND: Diagnosis of venous thromboembolism (VTE) is often delayed, and facilitating earlier diagnosis may improve associated morbidity and mortality. Clinical notes contain information not found elsewhere in the medical record that could facilitate timely VTE diagnosis and accurate quality measurement. However, extracting relevant information from unstructured clinical notes is complex. Today, there are relatively few electronic clinical quality measures (eCQMs) in our national payment program and none that use natural language processing (NLP) techniques for data extraction. NLP holds great promise for making quality measurement more accurate and more efficient. Given the potential of NLP-based applications to facilitate more accurate VTE detection, primary care is one clinical setting in urgent need of this type of tool.

Authors

  • John Novoa-Laurentiev
    Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School Boston MA USA. Electronic address: jlaurentiev@bwh.harvard.edu.
  • Mica Bowen
    Department of Medicine, Brigham & Women's Hospital, 75 Francis Street, Boston, MA, 02115, United States, 1 8572824088.
  • Avery Pullman
    Department of Medicine, Brigham & Women's Hospital, 75 Francis Street, Boston, MA, 02115, United States, 1 8572824088.
  • Wenyu Song
    Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA.
  • Ania Syrowatka
    Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA. Electronic address: asyrowatka@bwh.harvard.edu.
  • Jin Chen
    Department of Neurology, University of Texas Health Science Center at Houston, Houston, TX.
  • Michael Sainlaire
    Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • Frank Chang
    Shady Grove Fertility, Rockville, Maryland.
  • Krissy Gray
    Department of Biomedical Informatics, University of Kentucky, Lexington, KY, United States.
  • Purushottam Panta
    Department of Biomedical Informatics, University of Kentucky, Lexington, KY, United States.
  • Luwei Liu
    Department of Orthodontics, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, 210029, China. liuluwei_orth@njmu.edu.cn.
  • Khalid Nawab
    Department of Medicine, Geisinger Holy Spirit Hospital, Camp Hill, Pennsylvania, United States.
  • Shadi Hijjawi
    Department of Information Services, Penn State Health, Hershey, PA, United States.
  • Richard Schreiber
    Geisinger Holy Spirit, Camp Hill, PA, USA.
  • Li Zhou
    School of Education, China West Normal University, Nanchong, Sichuan, China.
  • Patricia C Dykes
    Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States.

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