Improving Computerized Provider Order Entry (CPOE) usability by data mining users' queries from access logs.
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).
Jalloh
Osman B
OB
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Waitman
Lemuel R
LR
D000465:Algorithms; D019992:Databases as Topic; D006801:Humans; D016247:Information Storage and Retrieval / Q000706:statistics & numerical data*; D050316:Medical Order Entry Systems / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D018709:Statistics, Nonparametric; D013997:Time Factors; D013996:Time and Motion Studies; D014584:User-Computer Interface