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Expert system development in nursing: implications for critical care nursing practice

M E Fonteyn¹, S J Grobe

¹University of San Francisco, School of Nursing, CA 94117-1080.

Heart & Lung : the Journal of Critical Care

|January 1, 1994

Summary

Highly experienced critical care nurses

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Area of Science:

Nursing Science
Artificial Intelligence
Clinical Decision Support

Background:

Critical care nursing involves complex decision-making for unstable patients.
Expertise in critical care is often tacit and difficult to transfer.
Developing computational models of expert reasoning is a key challenge.

Purpose of the Study:

To investigate the reasoning processes of expert critical care nurses.
To identify knowledge structures and decision-making strategies.
To assess the utility of this information for developing expert systems.

Main Methods:

Descriptive study utilizing the think-aloud technique.
Protocol analysis of nurse reasoning during a simulated critical patient scenario.
Laboratory-based simulation of a deteriorating patient.

Main Results:

Identified specific information used by nurses and its organization for care planning.
Extracted "if-then" rules from nurse reasoning processes.
Demonstrated the feasibility of capturing expert knowledge for system design.

Conclusions:

Expert reasoning processes can be modeled for expert system development.
Such systems can preserve and disseminate critical care nursing expertise.
Aiding less experienced nurses in improving reasoning skills and strategies.

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