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The case for expressing nursing theories using ontologies.

Elizabeth E Umberfield^1,2, Patricia A Ball Dunlap^3,4, Marcelline R Harris^5,6

¹Division of Nursing Research, Department of Nursing, Mayo Clinic, Rochester, Minnesota, USA.

Journal of the American Medical Informatics Association : JAMIA

|June 12, 2023

Summary

Nursing informatics can leverage structured knowledge representations, like formal ontologies, to make nursing knowledge machine-interpretable. This facilitates advanced technologies and interdisciplinary collaboration for better data utilization.

Keywords:

artificial intelligence nursing theory ontologies semantics terminology systems

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Area of Science:

Nursing Informatics
Knowledge Representation
Ontology Engineering

Background:

Nursing and informatics both utilize structured representations of concepts and their relationships.
Machine-interpretable nursing knowledge is crucial for advancing healthcare technologies.
Current technologies can benefit from formally represented nursing theories.

Purpose of the Study:

To highlight the importance of representing nursing knowledge in machine-interpretable formats.
To advocate for the use of formal ontologies in nursing.
To emphasize the potential benefits for nursing and other domains.

Main Methods:

Conceptual analysis of shared strengths between nursing and informatics.
Discussion of the necessity for formalizing nursing theories into ontologies.
Highlighting collaborative opportunities among nurse informaticists, scientists, and theorists.

Main Results:

Nursing knowledge can be accurately represented in machine-interpretable formats using ontologies.
Formal ontologies enable knowledge sharing across disciplines and enhance AI applications.
The representation of nursing theories in ontologies supports evidence-based practice and technological advancement.

Conclusions:

Formal ontologies are essential for integrating nursing knowledge with advanced technologies.
Collaborative efforts in nursing informatics can drive the development and application of these ontologies.
This approach will enhance the use of real-world data and evidence in healthcare.