title: Representing natural-language case report form terminology using Health Level 7 Common Document Architecture, LOINC, and SNOMED-CT: lessons learned.
abstract: Clinicians and biomedical research investigators ordinarily use natural language when describing biomedical concepts and constructs, even in the context of highly structured case report forms. We describe work in progress and lessons learned in translating complex natural-language concepts on case report forms into machine-readable format using the HL7 CDA, LOINC, and SNOMED-CT standards.
authors.affiliation: School of Information, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Dale
authors.initials: D
authors.lastname: Hunscher
authors.forename: Andrew
authors.initials: A
authors.lastname: Boyd
authors.forename: Lee A
authors.initials: LA
authors.lastname: Green
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Clauw
mesh_terms: D003195:Computer Communication Networks / Q000592:standards*; D019992:Databases as Topic / Q000592:standards; D006801:Humans; D039703:Logical Observation Identifiers Names and Codes; D009323:Natural Language Processing; D039061:Systematized Nomenclature of Medicine; D018511:Systems Integration