title: Linguistic analysis: terms and phrases used by patients in e-mail messages to nurses.
abstract: While some researchers are focusing on mapping free-text within health care fields into controlled vocabularies and classifications, many researchers are focusing on consumers' vocabularies. Using natural language processing (NLP) tools, such as MetaMap, to extract and map into terms in a controlled vocabulary is one way of understanding the pattern of terms used by lay people. Before an NLP tool can be effectively and efficiently used to extract concepts and create machine-understandable interpretations of the data, the appropriateness of the tool needs to be determined. This study aims were to determine the appropriateness of linguistic meaning captured for terms and phrases used by patients in electronic mail messages to nurses, using nursing-specific MetaMap output. Twenty messages were randomly selected from the 241 messages data set. Results indicated that four out of six nursing classification systems captured more than 50 % of the parsed word's linguistic meaning. This study demonstrates that it is possible to automatically extract and capture the linguistic meaning of the terms patients use in their electronic mail messages.
authors.affiliation: H6/296 Clinical Scence Center, School of Nursing, University of Wisconsin, 600 Highland Avenue, Madison, WI 53792, USA. yichuanhsieh@wisc.edu
authors.forename: Yichuan
authors.initials: Y
authors.lastname: Hsieh
authors.forename: Gudrun Audur
authors.initials: GA
authors.lastname: Hardardottir
authors.forename: Patricia Flatley
authors.initials: PF
authors.lastname: Brennan
mesh_terms: D034742:Electronic Mail; D006801:Humans; D008037:Linguistics; D009323:Natural Language Processing; D009723:Nurse-Patient Relations; D009726:Nurses; D009729:Nursing / Q000145:classification*; D010361:Patients; D017432:Unified Medical Language System; D014825:Vocabulary; D018875:Vocabulary, Controlled