Document ontology: supporting narrative documents in electronic health records
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Updated: Aug 7, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Jason S Shapiro1, Suzanne Bakken, Sookyung Hyun
1School of Nursing and Department of Biomedical Informatics, Columbia University, New York, USA.
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.
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