title: Using chief complaints for syndromic surveillance: a review of chief complaint based classifiers in North America.
abstract: A major goal of Natural Language Processing in the public health informatics domain is the automatic extraction and encoding of data stored in free text patient records. This extracted data can then be utilized by computerized systems to perform syndromic surveillance. In particular, the chief complaint--a short string that describes a patient's symptoms--has come to be a vital resource for syndromic surveillance in the North American context due to its near ubiquity. This paper reviews fifteen systems in North America--at the city, county, state and federal level--that use chief complaints for syndromic surveillance.
authors.affiliation: Division of Biomedical Informatics, University of California, San Diego, 9500 Gilman Dr. MC 0505 La Jolla, California 92093, USA. mconway@ucsd.edu
authors.forename: Mike
authors.initials: M
authors.lastname: Conway
authors.forename: John N
authors.initials: JN
authors.lastname: Dowling
authors.forename: Wendy W
authors.initials: WW
authors.lastname: Chapman
mesh_terms: D006801:Humans; D009656:North America; D011159:Population Surveillance; D013577:Syndrome
keywords: Chief complaints; Medical language processing; Natural language processing; Syndromic surveillance