title: Whole record surveillance is superior to chief complaint surveillance for predicting influenza.
abstract: Matched records of positive and negative influenza cases were parsed with a Natural Language Processor, the Multi-threaded Clinical Vocabulary Server (MCVS). Output was coded into SNOMED-CT reference terminology and compared to the SNOMED case definition of influenza. Odds ratios for each element of the influenza case definition by each section of the record were used to generate ROC curves. C-statistics showed that whole record surveillance was superior to chief complaint surveillance for predicting influenza.
authors.forename: Gail
authors.initials: G
authors.lastname: Welsh
authors.forename: Dietlind
authors.initials: D
authors.lastname: Wahner-Roedler
authors.forename: David Arthur
authors.initials: DA
authors.lastname: Froehling
authors.forename: Brett
authors.initials: B
authors.lastname: Trusko
authors.forename: Peter
authors.initials: P
authors.lastname: Elkin
mesh_terms: D001185:Artificial Intelligence; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D018563:Disease Notification; D006801:Humans; D007251:Influenza, Human / Q000175:diagnosis*; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D011159:Population Surveillance / Q000379:methods*