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Russ AL, Chen S, Melton BL, Johnson EG, Spina JR, Weiner M, Zillich AJ. A Novel Design for Drug-Drug Interaction Alerts Improves Prescribing Efficiency. Joint Commission Journal on Quality and Patient Safety. 2015 Sep 1; 41(9):396-405.
BACKGROUND: Drug-drug interactions (DDIs) are common in clinical care and pose serious risks for patients. Electronic health records display DDI alerts that can influence prescribers, but the interface design of DDI alerts has largely been unstudied. In this study, the objective was to apply human factors engineering principles to alert design. It was hypothesized that redesigned DDI alerts would significantly improve prescribers' efficiency and reduce prescribing errors. METHODS: In a counterbalanced, crossover study with prescribers, two DDI alert designs were evaluated. Department of Veterans Affairs (VA) prescribers were video recorded as they completed fictitious patient scenarios, which included DDI alerts of varying severity. Efficiency was measured from time-stamped recordings. Prescribing errors were evaluated against predefined criteria. Efficiency and prescribing errors were analyzed with the Wilcoxon signed-rank test. Other usability data were collected on the adequacy of alert content, prescribers' use of the DDI monograph, and alert navigation. RESULTS: Twenty prescribers completed patient scenarios for both designs. Prescribers resolved redesigned alerts in about half the time (redesign: 52 seconds versus original design: 97 seconds; p < .001). Prescribing errors were not significantly different between the two designs. Usability results indicate that DDI alerts might be enhanced by facilitating easier access to laboratory data and dosing information and by allowing prescribers to cancel either interacting medication directly from the alert. Results also suggest that neither design provided adequate information for decision making via the primary interface. CONCLUSION: Applying human factors principles to DDI alerts improved overall efficiency. Aspects of DDI alert design that could be further enhanced prior to implementation were also identified.