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Ascertainment of Aspirin Exposure Using Structured and Unstructured Large-scale Electronic Health Record Data.

  • Bustamante, Ranier1
  • Earles, Ashley1
  • Murphy, James D2, 3
  • Bryant, Alex K2
  • Patterson, Olga V4, 5
  • Gawron, Andrew J4, 5
  • Kaltenbach, Tonya6, 7
  • Whooley, Mary A6, 7
  • Fisher, Deborah A8, 9
  • Saini, Sameer D10, 11
  • Gupta, Samir1, 2, 3
  • Liu, Lin1, 2, 3
  • 1 VA San Diego Healthcare System.
  • 2 University of California, San Diego.
  • 3 Moores Cancer Center, La Jolla, CA.
  • 4 VA Salt Lake City Health Care System.
  • 5 University of Utah, Salt Lake City, UT.
  • 6 San Francisco VA Medical Center.
  • 7 University of California, San Francisco, San Francisco, CA.
  • 8 Durham VA Medical Center.
  • 9 Duke University, Durham, NC.
  • 10 VA Ann Arbor Healthcare System.
  • 11 University of Michigan, Ann Arbor, MI.
Published Article
Medical care
Publication Date
Oct 01, 2019
DOI: 10.1097/MLR.0000000000001065
PMID: 30807451


Aspirin impacts risk for important outcomes such as cancer, cardiovascular disease, and gastrointestinal bleeding. However, ascertaining exposure to medications available both by prescription and over-the-counter such as aspirin for research and quality improvement purposes is a challenge. Develop and validate a strategy for ascertaining aspirin exposure, utilizing a combination of structured and unstructured data. This is a retrospective cohort study. In total, 1,869,439 Veterans who underwent usual care colonoscopy 1999-2014 within the Department of Veterans Affairs. Aspirin exposure and dose were obtained from an ascertainment strategy combining query of structured medication records available in electronic health record databases and unstructured data extracted from free-text progress notes. Prevalence of any aspirin exposure and dose-specific exposure were estimated. Positive predictive value and negative predictive value were used to assess strategy performance, using manual chart review as the reference standard. Our combined strategy for ascertaining aspirin exposure using structured and unstructured data reached a positive predictive value and negative predictive value of 99.2% and 97.5% for any exposure, and 92.6% and 98.3% for dose-specific exposure. Estimated prevalence of any aspirin exposure was 36.3% (95% confidence interval: 36.2%-36.4%) and dose-specific exposure was 35.4% (95% confidence interval: 35.3%-35.5%). A readily accessible approach utilizing a combination of structured medication records and query of unstructured data can be used to ascertain aspirin exposure when manual chart review is impractical.

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