title: Use of natural language programming to extract medication from unstructured electronic medical records.
abstract: The purpose of this study is to evaluate the feasibility of applying natural language processing in the automated extraction of medications information from unstructured electronic records. Sixty-two documents containing medications were subjected to both manual and automated extraction. Both were able to identify over 90% medications. The automated method identified more medications than manual review, 97% vs 92%. However, the automated extraction included a substantial percentage (17%) of non-medication items but none with manual review.
authors.affiliation: Health System Information Service,University of Alabama, Birmingham, AL, USA.
authors.forename: David
authors.initials: D
authors.lastname: Chhieng
authors.forename: Timothy
authors.initials: T
authors.lastname: Day
authors.forename: Geoff
authors.initials: G
authors.lastname: Gordon
authors.forename: Joan
authors.initials: J
authors.lastname: Hicks
mesh_terms: D000465:Algorithms; D005240:Feasibility Studies; D016247:Information Storage and Retrieval / Q000379:methods*; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D004364:Pharmaceutical Preparations
chemical_list: D004364:Pharmaceutical Preparations