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

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. OBJECTIVE...

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Autores principales: Bustamante, Ranier, Earles, Ashley, Murphy, James D., Bryant, Alex K., Patterson, Olga V., Gawron, Andrew J., Kaltenbach, Tonya, Whooley, Mary A., Fisher, Deborah A., Saini, Sameer D., Gupta, Samir, Liu, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6703965/
https://www.ncbi.nlm.nih.gov/pubmed/30807451
http://dx.doi.org/10.1097/MLR.0000000000001065
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author Bustamante, Ranier
Earles, Ashley
Murphy, James D.
Bryant, Alex K.
Patterson, Olga V.
Gawron, Andrew J.
Kaltenbach, Tonya
Whooley, Mary A.
Fisher, Deborah A.
Saini, Sameer D.
Gupta, Samir
Liu, Lin
author_facet Bustamante, Ranier
Earles, Ashley
Murphy, James D.
Bryant, Alex K.
Patterson, Olga V.
Gawron, Andrew J.
Kaltenbach, Tonya
Whooley, Mary A.
Fisher, Deborah A.
Saini, Sameer D.
Gupta, Samir
Liu, Lin
author_sort Bustamante, Ranier
collection PubMed
description 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.
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spelling pubmed-67039652019-10-07 Ascertainment of Aspirin Exposure Using Structured and Unstructured Large-scale Electronic Health Record Data Bustamante, Ranier Earles, Ashley Murphy, James D. Bryant, Alex K. Patterson, Olga V. Gawron, Andrew J. Kaltenbach, Tonya Whooley, Mary A. Fisher, Deborah A. Saini, Sameer D. Gupta, Samir Liu, Lin Med Care Online Article: Applied Methods 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. Lippincott Williams & Wilkins 2019-10 2019-02-20 /pmc/articles/PMC6703965/ /pubmed/30807451 http://dx.doi.org/10.1097/MLR.0000000000001065 Text en Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does notextend to the contributions of employees of the Federal Government.
spellingShingle Online Article: Applied Methods
Bustamante, Ranier
Earles, Ashley
Murphy, James D.
Bryant, Alex K.
Patterson, Olga V.
Gawron, Andrew J.
Kaltenbach, Tonya
Whooley, Mary A.
Fisher, Deborah A.
Saini, Sameer D.
Gupta, Samir
Liu, Lin
Ascertainment of Aspirin Exposure Using Structured and Unstructured Large-scale Electronic Health Record Data
title Ascertainment of Aspirin Exposure Using Structured and Unstructured Large-scale Electronic Health Record Data
title_full Ascertainment of Aspirin Exposure Using Structured and Unstructured Large-scale Electronic Health Record Data
title_fullStr Ascertainment of Aspirin Exposure Using Structured and Unstructured Large-scale Electronic Health Record Data
title_full_unstemmed Ascertainment of Aspirin Exposure Using Structured and Unstructured Large-scale Electronic Health Record Data
title_short Ascertainment of Aspirin Exposure Using Structured and Unstructured Large-scale Electronic Health Record Data
title_sort ascertainment of aspirin exposure using structured and unstructured large-scale electronic health record data
topic Online Article: Applied Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6703965/
https://www.ncbi.nlm.nih.gov/pubmed/30807451
http://dx.doi.org/10.1097/MLR.0000000000001065
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