title: Document ontology: supporting narrative documents in electronic health records.
abstract: Electronic health records (EHRs) are beginning to manage an increasing volume of narrative data, such as clinical notes pertaining to admission, patient progress, shift change, follow-up, consultation, procedures, etc. These documents fall into a wide variety of classes, based on who is writing them, for what purpose, and in which location, suggesting the need for a document ontology (DO) to model our knowledge of health care documents and their properties. This paper focuses on one aspect of the Health Level 7 (HL7)/ Logical Observation Identifiers, Names, and Codes (LOINC) DO, the Subject Matter Domain (SMD). We created a new polyhierarchical structure for the SMD that combines the current value lists from the LOINC database with another value list from the American Board of Medical Specialties (ABMS). We refined and evaluated the new structure through expert review of the ontology, a survey of medical specialty boards, and specification of SMDs for a corpus of clinical notes.
authors.affiliation: School of Nursing and Department of Biomedical Informatics, Columbia University, New York, USA.
authors.forename: Jason S
authors.initials: JS
authors.lastname: Shapiro
authors.forename: Suzanne
authors.initials: S
authors.lastname: Bakken
authors.forename: Sookyung
authors.initials: S
authors.lastname: Hyun
authors.forename: Genevieve B
authors.initials: GB
authors.lastname: Melton
authors.forename: Cara
authors.initials: C
authors.lastname: Schlegel
authors.forename: Stephen B
authors.initials: SB
authors.lastname: Johnson
mesh_terms: D001291:Attitude of Health Personnel; D006801:Humans; D039703:Logical Observation Identifiers Names and Codes; D016347:Medical Records Systems, Computerized / Q000458:organization & administration*; D008511:Medicine; D013038:Specialization; D018875:Vocabulary, Controlled