Evidence map›Paper›PMID 30807451›Full record

ArticleMedical care2019

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

Ranier Bustamante, Ashley Earles, James D Murphy, Alex K Bryant, Olga V Patterson, Andrew J Gawron, Tonya Kaltenbach, Mary A Whooley, Deborah A Fisher, Sameer D Saini and 2 more

Abstract read
In one paragraph

Article in Medical care, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
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  7. Evaluation of Warfarin Use in Patients With Mental Health Conditions in a Rural Community Health Center System.The Journal of pharmacy technology : jPT : official publication of the Association of Pharmacy Technicians · 2021
    Article
  8. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Ranier BustamanteVA San Diego Healthcare System.
Ashley EarlesVA San Diego Healthcare System.
James D MurphyUniversity of California, San Diego.
Alex K BryantUniversity of California, San Diego.
Olga V PattersonVA Salt Lake City Health Care System.
Andrew J GawronVA Salt Lake City Health Care System.
Tonya KaltenbachSan Francisco VA Medical Center.
Mary A WhooleySan Francisco VA Medical Center.
Deborah A FisherDurham VA Medical Center.
Sameer D SainiVA Ann Arbor Healthcare System.
Samir GuptaVA San Diego Healthcare System.
Lin LiuVA San Diego Healthcare System.

Funding

Post-polypectomy Surveillance for Reducing Colon Cancer Incidence and MortalityR37CA222866 · NCI · VETERANS MEDICAL RESEARCH FDN/SAN DIEGO · PI GUPTA, SAMIR · 2018 to 2023
$3.3M
Optimizing Colorectal Cancer and Polyp Surveillance after Colorectal PolypectomyI01HX001574 · VA · VA SAN DIEGO HEALTHCARE SYSTEM · PI GUPTA, SAMIR · 2015 to 2019
–
HSRD VA I01 HX001574HSRD VA IP1 HX002002NCI NIH HHS R37 CA222866
6 · The paper itself

Abstract

backgroundAspirin 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.

objectivesDevelop and validate a strategy for ascertaining aspirin exposure, utilizing a combination of structured and unstructured data. RESEARCH

designThis 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.

resultsOur 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%).

conclusionsA 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.

Indexed as

AdultAgedAspirinColonoscopyDatabases, FactualData CollectionDrug PrescriptionsDrug-Related Side Effects and Adverse ReactionsElectronic Health RecordsFemaleHumansMaleMiddle AgedNonprescription DrugsRetrospective StudiesSensitivity and SpecificityAspirinNonprescription Drugs

Identifiers

PMID30807451
PMCPMC6703965

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.