title: Implementation of Emergency Medical Text Classifier for syndromic surveillance.
abstract: Public health officials use syndromic surveillance systems to facilitate early detection and response to infectious disease outbreaks. Emergency department clinical notes are becoming more available for surveillance but present the challenge of accurately extracting concepts from these text data. The purpose of this study was to implement a new system, Emergency Medical Text Classifier (EMT-C), into daily production for syndromic surveillance and evaluate system performance and user satisfaction. The system was designed to meet user preferences for a syndromic classifier that maximized positive predictive value and minimized false positives in order to provide a manageable workload. EMT-C performed better than the baseline system on all metrics and users were slightly more satisfied with it. It is vital to obtain user input and test new systems in the production environment.
authors.affiliation: Schools of Nursing, University of North Carolina, Chapel Hill, NC ; Medicine/Emergency Medicine, University of North Carolina, Chapel Hill, NC.
authors.forename: Debbie
authors.initials: D
authors.lastname: Travers
authors.affiliation: Information and Library Science, University of North Carolina, Chapel Hill, NC.
authors.forename: Stephanie W
authors.initials: SW
authors.lastname: Haas
authors.affiliation: Medicine/Emergency Medicine, University of North Carolina, Chapel Hill, NC.
authors.forename: Anna E
authors.initials: AE
authors.lastname: Waller
authors.affiliation: Schools of Nursing, University of North Carolina, Chapel Hill, NC ; Public Health/Biostatistics, University of North Carolina, Chapel Hill, NC.
authors.forename: Todd A
authors.initials: TA
authors.lastname: Schwartz
authors.affiliation: Information and Library Science, University of North Carolina, Chapel Hill, NC.
authors.forename: Javed
authors.initials: J
authors.lastname: Mostafa
authors.affiliation: Schools of Nursing, University of North Carolina, Chapel Hill, NC.
authors.forename: Nakia C
authors.initials: NC
authors.lastname: Best
authors.affiliation: Schools of Nursing, University of North Carolina, Chapel Hill, NC ; Medicine/Emergency Medicine, University of North Carolina, Chapel Hill, NC.
authors.forename: John
authors.initials: J
authors.lastname: Crouch
mesh_terms: D004196:Disease Outbreaks; D057286:Electronic Health Records / Q000145:classification*; D004636:Emergency Service, Hospital / Q000145:classification*; D006801:Humans; D009323:Natural Language Processing; D040442:Public Health Informatics; D062486:Public Health Surveillance / Q000379:methods*