VA San Diego Healthcare System.
University of California, San Diego.
Med Care. 2019 Oct;57(10):e60-e64. doi: 10.1097/MLR.0000000000001065.
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.
Develop and validate a strategy for ascertaining aspirin exposure, utilizing a combination of structured and unstructured data.
This is a retrospective cohort study.
In total, 1,869,439 Veterans who underwent usual care colonoscopy 1999-2014 within the Department of Veterans Affairs.
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.
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%).
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.
阿司匹林会影响癌症、心血管疾病和胃肠道出血等重要结局的风险。然而，确定可通过处方和非处方途径获得的药物（如阿司匹林）的暴露情况，以用于研究和质量改进目的，是一项挑战。
开发并验证一种利用结构化和非结构化数据组合来确定阿司匹林暴露情况的策略。
这是一项回顾性队列研究。
共有 1869439 名退伍军人在退伍军人事务部接受了 1999 年至 2014 年的常规结肠镜检查。
阿司匹林暴露情况和剂量是通过一种结合了电子健康记录数据库中结构化药物记录查询和从自由文本记录中提取的非结构化数据的策略获得的。估计了任何阿司匹林暴露情况和剂量特异性暴露情况的患病率。使用手动图表审查作为参考标准，使用阳性预测值和阴性预测值来评估策略的性能。
我们使用结构化和非结构化数据相结合的综合策略来确定阿司匹林暴露情况，其阳性预测值和阴性预测值分别为 99.2%和 97.5%（任何暴露），以及 92.6%和 98.3%（剂量特异性暴露）。估计任何阿司匹林暴露情况的患病率为 36.3%（95%置信区间：36.2%-36.4%），剂量特异性暴露情况的患病率为 35.4%（95%置信区间：35.3%-35.5%）。
当手动图表审查不切实际时，可以使用一种易于获取的方法，该方法结合了结构化药物记录和非结构化数据查询，以确定阿司匹林的暴露情况。
