Toward a cognitive taxonomy of medical errors

Area of Science:

• Cognitive Psychology
• Medical Informatics
• Human Factors Engineering

Background:

• Human errors pose significant challenges in healthcare, necessitating systematic approaches for their resolution.
• Existing frameworks for error analysis often lack a cognitive dimension, limiting their predictive and intervention capabilities.

Purpose of the Study:

• To develop and validate a preliminary action-based cognitive taxonomy of human errors in medicine.
• To establish a framework for categorizing errors, linking them to cognitive mechanisms, predicting occurrence, and generating interventions.

Main Methods:

• The study integrates Reason's (1992) definition of human errors with Norman's (1986) cognitive theory of human action.
• A preliminary taxonomy was developed based on cognitive dimensions and action-based principles within the medical domain.

Main Results:

• A preliminary action-based cognitive taxonomy of medical errors was developed, satisfying key criteria for categorization, mechanism association, prediction, and intervention generation.
• The taxonomy provides a foundation for developing advanced medical error reporting systems.

Conclusions:

• The developed cognitive taxonomy offers a structured approach to understanding and mitigating human errors in medicine.
• Application of this taxonomy can enhance medical error reporting systems, leading to improved patient safety and healthcare quality.