title: MedEx: a medication information extraction system for clinical narratives.
abstract: Medication information is one of the most important types of clinical data in electronic medical records. It is critical for healthcare safety and quality, as well as for clinical research that uses electronic medical record data. However, medication data are often recorded in clinical notes as free-text. As such, they are not accessible to other computerized applications that rely on coded data. We describe a new natural language processing system (MedEx), which extracts medication information from clinical notes. MedEx was initially developed using discharge summaries. An evaluation using a data set of 50 discharge summaries showed it performed well on identifying not only drug names (F-measure 93.2%), but also signature information, such as strength, route, and frequency, with F-measures of 94.5%, 93.9%, and 96.0% respectively. We then applied MedEx unchanged to outpatient clinic visit notes. It performed similarly with F-measures over 90% on a set of 25 clinic visit notes.
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University, School of Medicine, Nashville, Tennessee 37232, USA. hua.xu@vanderbilt.edu
authors.forename: Hua
authors.initials: H
authors.lastname: Xu
authors.forename: Shane P
authors.initials: SP
authors.lastname: Stenner
authors.forename: Son
authors.initials: S
authors.lastname: Doan
authors.forename: Kevin B
authors.initials: KB
authors.lastname: Johnson
authors.forename: Lemuel R
authors.initials: LR
authors.lastname: Waitman
authors.forename: Joshua C
authors.initials: JC
authors.lastname: Denny
mesh_terms: D057225:Data Mining; D057286:Electronic Health Records; D006801:Humans; D008509:Medication Systems; D009323:Natural Language Processing; D016730:Program Development; D012985:Software Design