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Mapping nursing concepts to ontologies for evidence-based nursing.
Kourosh Ravvaz1, Patricia Senk, Timothy B Patrick
1University of Wisconsin-Milwaukee, WI, USA.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|November 13, 2008
Summary
This project maps nursing terms from research to standard terminologies like ICNP and SNOMED-CT. This supports evidence-based nursing by organizing knowledge for better data use.
Area of Science:
- Nursing Informatics
- Medical Terminology
- Knowledge Representation
Background:
- Evidence-based nursing requires standardized terminologies for knowledge synthesis.
- Current nursing knowledge syntheses contain natural language expressions that are difficult to process computationally.
- Bridging the gap between natural language and formal ontologies is crucial for advancing nursing science.
Purpose of the Study:
- To describe a project that maps natural language nursing concepts to standard ontologies.
- To support an evidence-based nursing initiative through improved knowledge organization.
- To facilitate the integration of nursing knowledge into computational systems.
Main Methods:
- Identifying natural language concept expressions from nursing knowledge syntheses.
- Mapping these expressions to established nursing terminologies, specifically ICNP and SNOMED-CT.
- Developing a methodology for concept mapping in the nursing domain.
Main Results:
- A successful mapping of nursing-related natural language expressions to ICNP and SNOMED-CT.
- Demonstration of a feasible approach for standardizing nursing terminology.
- Foundation laid for computational processing of nursing knowledge.
Conclusions:
- Mapping natural language nursing concepts to standard ontologies is achievable.
- This process enhances the utility of nursing knowledge for evidence-based practice.
- The project contributes to the standardization and computational accessibility of nursing information.
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