Regular expression-based learning to extract bodyweight values from clinical notes.

Journal: Journal of biomedical informatics
Published Date: Mar 5, 2015

Abstract

BACKGROUND: Bodyweight related measures (weight, height, BMI, abdominal circumference) are extremely important for clinical care, research and quality improvement. These and other vitals signs data are frequently missing from structured tables of electronic health records. However they are often recorded as text within clinical notes. In this project we sought to develop and validate a learning algorithm that would extract bodyweight related measures from clinical notes in the Veterans Administration (VA) Electronic Health Record to complement the structured data used in clinical research.

Authors

  • Maureen A Murtaugh
    IDEAS Center, Veterans Administration, Salt Lake City Health Care System, Salt Lake City, UT, United States; Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States. Electronic address: Maureen.Murtaugh@hsc.utah.edu.
  • Bryan Smith Gibson
    IDEAS Center, Veterans Administration, Salt Lake City Health Care System, Salt Lake City, UT, United States; Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States.
  • Doug Redd
    IDEAS Center, Veterans Administration, Salt Lake City Health Care System, Salt Lake City, UT, United States; Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, United States.
  • Qing Zeng-Treitler
    Veterans Affairs Medical Center, Washington, DC; George Washington University, Washington, DC.

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