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


Journal Article

BACKGROUND: 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. OBJECTIVES: Develop and validate a strategy for ascertaining aspirin exposure, utilizing a combination of structured and unstructured data. RESEARCH DESIGN: This is a retrospective cohort study. SUBJECTS: In total, 1,869,439 Veterans who underwent usual care colonoscopy 1999-2014 within the Department of Veterans Affairs. MEASURES: 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. RESULTS: 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%). CONCLUSIONS: 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.

Full Text

Duke Authors

Cited Authors

  • Bustamante, R; Earles, A; Murphy, JD; Bryant, AK; Patterson, OV; Gawron, AJ; Kaltenbach, T; Whooley, MA; Fisher, DA; Saini, SD; Gupta, S; Liu, L

Published Date

  • October 2019

Published In

Volume / Issue

  • 57 / 10

Start / End Page

  • e60 - e64

PubMed ID

  • 30807451

Pubmed Central ID

  • 30807451

Electronic International Standard Serial Number (EISSN)

  • 1537-1948

Digital Object Identifier (DOI)

  • 10.1097/MLR.0000000000001065


  • eng

Conference Location

  • United States