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Related Experiment Videos

Patterns of usage for a Web-based clinical information system.

Elizabeth S Chen1, James J Cimino

  • 1Department of Biomedical Informatics, Columbia University, 622 W. 168th Street, Vanderbilt Clinic 5th Floor, New York, NY 10032, USA. liz.chen@dbmi.columbia.edu

Studies in Health Technology and Informatics
|September 14, 2004
PubMed
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Analyzing system logs reveals frequent clinical information system feature usage and user navigation patterns. These insights inform system design enhancements and user experience improvements for better clinical workflows.

Area of Science:

  • Clinical Informatics
  • Human-Computer Interaction
  • Software Engineering

Background:

  • Understanding clinician interaction with clinical information systems is crucial for effective system design and development.
  • System log files offer valuable data for monitoring user engagement and identifying areas for enhancement.
  • Web-based clinical information systems (WebCIS) are integral to modern healthcare delivery.

Purpose of the Study:

  • To analyze WebCIS log files to understand clinician usage patterns.
  • To identify frequently used features and user navigation pathways within the WebCIS.
  • To provide data-driven recommendations for customizing WebCIS functionalities.

Main Methods:

  • Analysis of system log files from a Web-based clinical information system (WebCIS).

Related Experiment Videos

  • Extraction of usage statistics to determine feature frequency.
  • Identification of user traversal patterns within the system interface.

    • Main Results:

    • Quantification of frequently accessed WebCIS features.
    • Characterization of common user navigation pathways through the system.
    • Identification of specific areas within WebCIS that could benefit from optimization.

    Conclusions:

    • Log file analysis provides actionable insights into clinical information system usage.
    • Understanding usage patterns enables targeted system customization for improved efficiency.
    • Findings can guide the enhancement of menus, shortcut lists, and patient reports in WebCIS and similar systems.