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Cognitive engineering and health informatics: Applications and intersections.

A Zachary Hettinger1, Emilie M Roth2, Ann M Bisantz3

  • 1Department of Emergency Medicine, Georgetown University School of Medicine, Washington, DC, United States; National Center for Human Factors in Healthcare, MedStar Health, Washington, DC, United States.

Journal of Biomedical Informatics
|January 28, 2017
PubMed
Summary
This summary is machine-generated.

Cognitive engineering offers structured methods for analyzing complex work, improving human-automation interaction and decision support. Integrating informatics data can enhance these analyses for better system design.

Keywords:
Cognitive engineeringCognitive informaticsEmergency medicineHealth information technologyReview

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Area of Science:

  • Cognitive engineering, drawing from cognitive science and engineering.
  • Application in high-risk domains: nuclear power, transportation, defense.
  • Intersection with Cognitive Informatics methods.

Background:

  • Cognitive engineering supports design of information displays, decision support, and human-automation interaction.
  • Methods identify performance challenges and expert strategies in complex domains.
  • Provides novel representations of work domain complexity and links to design requirements.

Purpose of the Study:

  • To provide an overview of cognitive engineering methods.
  • To illustrate applications in health information technology (HIT) system design.
  • To discuss integrating informatics data into cognitive engineering analyses.

Main Methods:

  • Structured, analytic methods for data collection and analysis.
  • Discovery of performance challenges and expert knowledge, skills, and strategies.
  • Development of novel representations linking analysis to design requirements.

Main Results:

  • Cognitive engineering methods have been applied to design HIT systems.
  • Existing applications show the utility of cognitive engineering in user-centered informatics.
  • Identified a gap in the typical incorporation of informatics methods into cognitive engineering.

Conclusions:

  • Cognitive engineering provides valuable tools for understanding and designing complex systems.
  • Health information technology (HIT) design benefits from cognitive engineering approaches.
  • Data-rich informatics methods offer potential to enhance cognitive engineering analyses.