Ascertainment of Aspirin Exposure Using Structured and Unstructured Large-scale Electronic Health Record Data
| Autor: | Olga V. Patterson, Alex K. Bryant, Tonya Kaltenbach, Lin Liu, Sameer D. Saini, Ashley Earles, Samir Gupta, James D. Murphy, Andrew J. Gawron, Ranier Bustamante, Deborah A. Fisher, Mary A. Whooley |
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| Rok vydání: | 2019 |
| Předmět: |
Adult
Male medicine.medical_specialty Gastrointestinal bleeding Quality management Databases Factual Drug-Related Side Effects and Adverse Reactions MEDLINE Nonprescription Drugs Disease Drug Prescriptions Sensitivity and Specificity 03 medical and health sciences 0302 clinical medicine medicine Humans 030212 general & internal medicine Medical prescription Online Article: Applied Methods Intensive care medicine Aged Retrospective Studies Veterans Aspirin business.industry Data Collection 030503 health policy & services Public Health Environmental and Occupational Health Retrospective cohort study Colonoscopy Middle Aged medicine.disease ascertainment United States 3. Good health electronic health records Scale (social sciences) ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Female 0305 other medical science business medicine.drug |
| Zdroj: | Medical Care |
| ISSN: | 0025-7079 |
| Popis: | Supplemental Digital Content is available in the text. 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. |
| Databáze: | OpenAIRE |
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