iods. Provider ordering behavior was monitored, focusing on the number of medication orders not completed and the number of rule-associated laboratory test orders initiated after alert display. The investigators found that the rule processed 16,291 times during the study period on all possible medication orders: 7,017 during the pre-intervention period (prescribing doctors did not receive alerts) and 9,274 during the post-intervention period (prescribing doctors received alerts). During the post-intervention period, an alert was displayed for 11.8% (1,093 out of 9,274) of the times the rule processed, with 5.6% of alerts being for “missing laboratory values,?6.0% for “abnormal rule-associated laboratory?values, and 0.2% for both types of problems.
Providers did pay attention to the alerts; they increased ordering of the rule-associated laboratory test when an alert was displayed (39% at baseline versus 51% post-intervention, p < 0.001), thus showing that the rules had a significant ability to change the ordering behavior of the provider, said the authors. The strongest effect occurred when providers where alerted to “missing?laboratory results (42% increase), the investigators noted. There was less of an effect on ordering behavior when the alert informed the provider of the existence of an abnormal laboratory value (23% increase), which may imply that the cutoff values for the “abnormal?trigger were set too low, suggested the authors. However, there was only a modest effect on halting the ordering of medications, and this was limited to occasions in which the alert presented an abnormal laboratory value in which case there was almost a doubling in order cessation.
There are limitations to the study. For example, the intervention focused on a specific group of drug–laboratory interactions and thus the results may not be generalizable to other types of interventions. In addition, the setting was a single primary-care clinic outpatient setting within aPage: 1 2 3 Related biology news :1
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