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

机译:使用结构化和非结构化大规模电子健康记录数据来确定阿司匹林曝光

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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.
机译:背景:阿司匹林对癌症,心血管疾病和胃肠道出血等重要结果影响风险。然而,根据阿司匹林用于研究和质量改善的诸如阿司匹林的处方和过度计量的药物,确定接触药物的接触是挑战。目标:利用结构化和非结构化数据的组合,开发和验证Aspirin曝光的策略。研究设计:这是一个回顾性的队列研究。主题:总共有1,869,439名退伍军人在退伍军人事务部1999 - 2014年接受了通常的护理结肠镜检查。措施:从电子健康记录数据库中可用的结构化药物记录的查询和从自由文本进度注释中提取的非结构化数据,获得阿司匹林接触和剂量。估计了任何阿司匹林暴露和剂量特异性暴露的患病率。阳性预测值和否定预测值用于评估战略性能,使用手动图表审查作为参考标准。结果:我们使用结构化和非结构化数据确定阿司匹林暴露的合并策略达到了阳性预测值,负面接触的阳性预测值和负预测值为99.2%和97.5%,对剂量特异性接触的92.6%和98.3%。估计任何阿司匹林暴露的患病率为36.3%(95%置信区间:36.2%-36.4%)和剂量特异性暴露35.4%(95%置信区间:35.3%-35.5%)。结论:利用结构化药物记录组合和非结构化数据查询的易于访问方法可用于在手动图表审查不切实际时确定阿司匹林暴露。

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