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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Document ontology: supporting narrative documents in electronic health records
Jason S Shapiro1, Suzanne Bakken, Sookyung Hyun
1School of Nursing and Department of Biomedical Informatics, Columbia University, New York, USA.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|June 17, 2006
Summary
Researchers developed a new polyhierarchical structure for Subject Matter Domains (SMD) within healthcare document ontologies. This improves the organization and classification of clinical notes in electronic health records (EHRs).
Area of Science:
- Health Informatics
- Medical Ontology
- Natural Language Processing in Healthcare
Background:
- Electronic Health Records (EHRs) increasingly contain unstructured narrative data.
- Classifying diverse clinical documents (notes, reports) is challenging.
- A standardized document ontology (DO) is needed to model healthcare documents.
Purpose of the Study:
- To develop an improved Subject Matter Domain (SMD) structure for the Health Level 7 (HL7)/Logical Observation Identifiers, Names, and Codes (LOINC) Document Ontology (DO).
- To enhance the classification and management of clinical narrative data within EHR systems.
Main Methods:
- Created a novel polyhierarchical structure for SMDs by integrating LOINC and American Board of Medical Specialties (ABMS) value lists.
- Refined the structure through expert review of the ontology.
- Evaluated the structure via a survey of medical specialty boards and by applying it to a corpus of clinical notes.
Main Results:
- A new, combined polyhierarchical SMD structure was successfully developed.
- Expert review and survey data supported the refined structure's validity.
- The structure demonstrated utility in specifying SMDs for clinical notes.
Conclusions:
- The proposed polyhierarchical SMD structure offers a more robust model for classifying healthcare documents.
- This advancement can improve the organization and retrieval of narrative data in EHRs.
- Further integration of such ontologies is crucial for advancing health informatics.
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