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A dynamic classification approach for nursing.

Nicholas R Hardiker¹, Tae Youn Kim, Amy M Coenen

¹University of Salford, School of Nursing & Midwifery, Greater Manchester, UK.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|December 24, 2011

Summary

This summary is machine-generated.

This study introduces a novel ontology-based approach for nursing classification, enhancing the International Classification for Nursing Practice (ICNP) with flexible, computer-driven structures for improved healthcare quality.

Related Experiment Videos

Area of Science:

Nursing Informatics
Health Information Science
Knowledge Representation

Background:

Nursing classification systems have a 150-year history, with computerization driving standardization.
Current nursing classifications, while updated, possess static underlying structures.
Existing systems face challenges in adapting flexibly to user needs.

Purpose of the Study:

To present a new ontology-based approach for nursing classification.
To develop a more flexible and user-centered classification structure.
To propose an enhanced structure for the International Classification for Nursing Practice (ICNP).

Main Methods:

Utilizing formal Web Ontology Language (OWL) definitions for classes.
Employing computer-based reasoning for automated classification structure generation.
Deriving a new classification structure for the ICNP.

Main Results:

Demonstrated an approach for creating dynamic nursing classification structures.
Generated a proposed classification structure for the ICNP.
Highlighted the potential for improved quality improvement processes.

Conclusions:

Ontology-based reasoning offers a flexible alternative to static nursing classification structures.
The proposed ICNP structure provides a new perspective for future releases.
This approach can significantly contribute to nursing knowledge management and quality improvement.