The University of Texas Health Science Center at Houston
The growing use of Electronic Health Records (EHRs) systems has established large practice-based clinical datasets, which are emerging as valuable resources for clinical and translational research. The longitudinal nature of the data contained within EHRs makes them ideal for quantifying drug outcomes (both efficacy and toxicity). The major challenge of using EHRs for studying drug outcomes has clearly been the identification of patients’ drug exposure and outcome information from heterogeneous clinical data, including narrative reports. This presentation will describe our recent development of natural language processing (NLP) and data mining methods for extracting and modeling medication data in EHR, as well as how such informatics methods can be used to support drug outcome studies. Two EHR-based drug studies will be discussed: 1) a drug-repositioning study – to validate that metformin, a drug for diabetes, can increase cancer survival rate; and 2) a pharmacogenetic study – to replicate known genetic associations of warfarin stable dose.
Dr. Hua Xu is an associate professor at the School of Biomedical Informatics in The University of Texas Health Science Center at Houston (UTHealth). He directs the Center for Computational Biomedicine at UTHealth. Currently he is the Chair of American Medical Informatics Association (AMIA) Natural Language Processing (NLP) working group. Dr. Xu received his Ph.D. in Biomedical Informatics from Columbian University in 2008. Prior to UTHealth, he was an assistant professor of Biomedical Informatics at Vanderbilt University. Dr. Xu is an expert in biomedical text processing and data mining. His primary research interests include: 1) clinical natural language processing; 2) biomedical literature mining; and 3) healthcare data mining. He is the author of many publications on biomedical NLP and text mining, and his research on medication extraction received the Homer Warner Award from AMIA in 2009. Dr. Xu has been principal investigator on a number of grants, including R01s from National Library of Medicine (NLM), National Cancer Institute (NCI), and National Institute of General Medical Sciences (NIGMS).
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