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Int J Med Inform ; 97: 59-67, 2017 01.
Article in English | MEDLINE | ID: mdl-27919396

ABSTRACT

OBJECTIVES: Pharmacologic interaction alerting offers the potential for safer medication prescribing, but research reveals persistent concerns regarding alert fatigue. Research studies have tried various strategies to resolve this problem, with low overall success. We examined the effects of targeted alert reduction on clinician behavior in a resource constrained hospital. METHODS: A physician and a pharmacy informaticist reduced alert levels of several drug-drug interactions (DDI) that clinicians almost always overrode with approval from and knowledge of the medical staff. This study evaluated the behavioral changes in prescribers and non-prescribers as measured by "think time", a new metric for evaluating the resolution time for an alert, before and after suppression of selected DDI alerts. RESULTS: The user-seen DDI alert rate decreased from 9.98% of all orders to 9.20% (p=0.0001) with an overall volume reduction of 10.3%. There was no statistical difference in the reduction of cancelled (-10.00%) vs. proceed orders (-11.07%). Think time decreased overall by 0.61s (p<0.0001). Think time unexpectedly increased for cancelled orders 1.00s which while not statistically significant (p=0.28) is generally thought to be clinically noteworthy. For overrides, think time decreased 0.67s which was significant (p<0.0001). Think time lowered for both prescribers and non-prescribers. Targeted specialists had shorter think times initially, which shortened more than non-targeted specialists. CONCLUSIONS: Targeted DDI alert reductions reduce alert burden overall, and increase net efficiency as measured by think time for all prescribers better than for non-prescribers. Think time may increase when cancelling or changing orders in response to DDI alerts vs. a decision to override an alert.


Subject(s)
Alert Fatigue, Health Personnel , Decision Support Systems, Clinical , Drug Interactions , Medical Order Entry Systems , Humans , Medication Errors/prevention & control , Physicians , Practice Patterns, Physicians' , Specialization , Thinking
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