Improving Computerized Provider Order Entry (CPOE) usability by data mining users' queries from access logs
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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
Osman B Jalloh1, Lemuel R Waitman
1Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Abstract:
This study describes and evaluates a technique for using clinicians' search preferences to reduce the time to query and select orders. A relational database was created to store user keystroke logs with the timing of each user activity. The most frequently selected orders associated with the popular query phrases were distilled from three months of data. The resulting table of popular queries and selected orders was incorporated into the order entry system so the most favored orders were placed at the top of the pick-list. A retrospective evaluation indicated the method significantly reduced orderable selection time (16.3% reduction for optimized queries using the method versus 5.7% for un-optimized queries).
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