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Related Experiment Videos

Improving Computerized Provider Order Entry (CPOE) usability by data mining users' queries from access logs.

Osman B Jalloh1, Lemuel R Waitman

  • 1Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|January 24, 2007
PubMed
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This study optimized order entry by using clinician search data to prioritize frequently chosen orders. This significantly reduced the time clinicians spend searching for and selecting orders in electronic health records.

Area of Science:

  • Health Informatics
  • Clinical Decision Support
  • Human-Computer Interaction

Background:

  • Efficient order entry is crucial in healthcare settings.
  • Clinician time is valuable and reducing administrative burden is a priority.
  • Current order entry systems may not always reflect clinician preferences effectively.

Purpose of the Study:

  • To develop and evaluate a method for optimizing order entry by personalizing pick-lists based on clinician search behavior.
  • To reduce the time required for clinicians to query and select medical orders.

Main Methods:

  • A relational database was used to log clinician keystrokes and activity timing.
  • Analysis of three months of data identified popular query phrases and associated order selections.

Related Experiment Videos

  • A table of frequent queries and orders was integrated into the order entry system to pre-populate preferred options.

    • Main Results:

    • The implemented method significantly reduced orderable selection time.
    • Optimized queries using the new method showed a 16.3% reduction in selection time.
    • Un-optimized queries showed a smaller 5.7% reduction, highlighting the method's effectiveness.

    Conclusions:

    • Personalizing order entry systems based on clinician search preferences is an effective strategy.
    • This approach demonstrably improves efficiency by reducing the time needed for order selection.
    • The findings support the integration of user behavior analytics into clinical information systems for enhanced usability.