A Novel Design for Drug-Drug Interaction Alerts Improves Prescribing Efficiency.

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.

Applying human factors principles to alert design increases efficiency and reduces prescribing errors in a scenario-based simulation.

OBJECTIVE: To apply human factors engineering principles to improve alert interface design. We hypothesized that incorporating human factors principles into alerts would improve usability, reduce workload for prescribers, and reduce prescribing errors. MATERIALS AND METHODS: We performed a scenario-based simulation study using a counterbalanced, crossover design with 20 Veterans Affairs prescribers to compare original versus redesigned alerts. We redesigned drug-allergy, drug-drug interaction, and drug-disease alerts based upon human factors principles. We assessed usability (learnability of redesign, efficiency, satisfaction, and usability errors), perceived workload, and prescribing errors. RESULTS: Although prescribers received no training on the design changes, prescribers were able to resolve redesigned alerts more efficiently (median (IQR): 56 (47) s) compared to the original alerts (85 (71) s; p=0.015). In addition, prescribers rated redesigned alerts significantly higher than original alerts across several dimensions of satisfaction. Redesigned alerts led to a modest but significant reduction in workload (p=0.042) and significantly reduced the number of prescribing errors per prescriber (median (range): 2 (1-5) compared to original alerts: 4 (1-7); p=0.024). DISCUSSION: Aspects of the redesigned alerts that likely contributed to better prescribing include design modifications that reduced usability-related errors, providing clinical data closer to the point of decision, and displaying alert text in a tabular format. Displaying alert text in a tabular format may help prescribers extract information quickly and thereby increase responsiveness to alerts. CONCLUSIONS: This simulation study provides evidence that applying human factors design principles to medication alerts can improve usability and prescribing outcomes.