title: Adaptation of the NegEx algorithm to Veterans Affairs electronic text notes for detection of influenza-like illness (ILI).
abstract: We tested automated detection of influenza-like illness (ILI) from free-text clinician notes extracted from the VA electronic medical record using a simple negation algorithm coupled with string matching for relevant ILI symptoms mapped to UMLS concepts. Additionally, we documented negation problems encountered and adaptations made to the negation algorithm when applied to the full texts of a diverse array of VA note types and templates.
authors.affiliation: V A Salt Lake City Health Care system and the Department of Medicine, University of Utah, School of Medicine, Salt Lake City, UT, USA.
authors.forename: Brett R
authors.initials: BR
authors.lastname: South
authors.forename: Shobha
authors.initials: S
authors.lastname: Phansalkar
authors.forename: Ashwin Deepak
authors.initials: AD
authors.lastname: Swaminathan
authors.forename: Sylvain
authors.initials: S
authors.lastname: Delisle
authors.forename: Trish
authors.initials: T
authors.lastname: Perl
authors.forename: Matthew H
authors.initials: MH
authors.lastname: Samore
mesh_terms: D000465:Algorithms; D006787:Hospitals, Veterans; D006801:Humans; D007251:Influenza, Human / Q000175:diagnosis*; D016347:Medical Records Systems, Computerized; D011159:Population Surveillance / Q000379:methods*; D012680:Sensitivity and Specificity; D017432:Unified Medical Language System; D014481:United States