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Healthc Inform Res > Volume 12(3); 2006 > Article
Journal of Korean Society of Medical Informatics 2006;12(3):261-271.
DOI: https://doi.org/10.4258/jksmi.2006.12.3.261    Published online September 30, 2006.
How to Deal with Medical Narratives based on Controlled Natural Language Operated by an Ontology
Byung Hyun Ha, Hong Gee Kim, Jae Il Lee, Myeng Ki Kim
1Department of Industrial Engineering, College of Engineering, Pusan National University, Korea.
2Department of Dental Care and Information Technology, School of Dentistry, Seoul National University, Korea.
3Department of Oral Pathology, School of Dentistry, Seoul National University, Korea.
4
Abstract

OBJECTIVE: Medical narratives entry is a major issue to be solved in developing an electronic medical record system operating in practice, as they are, in large part, described in a free-text format. The issue can be dealt with in three aspects: to improve the reusability by structuring medical narratives, to support clinical pragmatics in medical fields, and to reduce the burden of data entry. With the aspects having in mind, this paper purports to present an ontological method for better way of medical narratives entry.

METHODS: We developed an ontology for which medical knowledge is structurally represented. Then we can enter medical narrative texts with commands of the controlled natural language operable on the ontology model.

RESULTS: Many theoretical studies on free-text entry were reviewed, based on which an authoring and editing tool for natural language description operable on the ontology model has been developed and tested. The performance of the tool is satisfactory within the limit of the domain models we developed here.

CONCLUSION: The results of this paper are contributive for clinicians to make an easy entry of medical narratives as far as the ontology model covers their knowledge domain. It is also expected that the cost in recording medical narratives might be considerably reduced and data quality can be improved.

Key Words: EMR, Medical Narrative, Controlled Natural Language, Ontology, User Interface
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