Detecting Signals of Interactions Between Warfarin and Dietary Supplements in Electronic Health Records
Drug and supplement interactions (DSIs) have drawn widespread attention due to their potential to affect therapeutic response and adverse event risk. Electronic health records provide a valuable source where the signals of DSIs can be identified and characterized. We detected signals of interactions between warfarin and seven dietary supplements, viz., alfalfa, garlic, ginger, ginkgo, ginseng, St. Johns Wort, and Vitamin E by analyzing structured clinical data and unstructured clinical notes from the University of Minnesota Clinical Data Repository. A machine learning-based natural language processing module was further developed to classify supplement use status and applied to filter out irrelevant clinical notes. Cox proportional hazards models were fitted, controlling for a set of confounding factors: age, gender, and Charlson Index of Comorbidity. There was a statistically significant association of warfarin concurrently used with supplements which can potentially increase the risk of adverse events, such as gastrointestinal bleeding.
Electronic Health Records Natural Language Processing Warfarin
Yadan Fan Terrence J.Adam Reed McEwan Serguei V.Pakhomov Genevieve B.Melton Rui Zhang
Institute for Health Informatics Institute for Health Informatics;College of Pharmacy Academic Health Center-Information Systems Institute for Health Informatics;Department of Surgery,University of Minnesota,Minneapolis,MN,USA
国际会议
第十六届世界医药健康信息学大会((MEDINFO2017)、第二届世界医药健康信息学华语论坛(WCHIS 2017)、第15届全国医药信息学大会(CMIA 2017)
苏州
英文
370-374
2017-08-21（万方平台首次上网日期，不代表论文的发表时间）