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

机译:在基于场景的模拟中将人为因素原理应用于警报设计可提高效率并减少处方错误

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摘要

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.
机译:目的:应用人为因素工程原理改进警报界面设计。我们假设将人为因素原理整合到警报中将提高可用性,减少开处方者的工作量并减少开处方错误。材料和方法:我们采用了一种基于场景的模拟研究,使用了20种退伍军人事务开处方者的平衡,交叉设计来比较原始和比较重新设计的警报。我们根据人为因素原则重新设计了药物过敏,药物相互作用以及药物疾病警报。我们评估了可用性(重新设计的易读性,效率,满意度和可用性错误),感知的工作量和处方错误。结果:尽管开处方者没有接受设计变更方面的培训,但开处方者能够更有效地解决重新设计的警报(中位数(IQR) :56(47)s)与原始警报(85(71)s; p = 0.015)进行比较。此外,开药者在几个满意度方面对重新设计的警报的评分明显高于原始警报。重新设计的警报导致工作量适度但显着减少(p = 0.042),并且与原始警报相比,每个处方者的处方错误数量(中位(范围):2(1-5))明显减少:4(1-7); p = 0.024)。讨论:重新设计的警报方面可能有助于更好地制定处方,其中包括设计修改,这些设计减少了与可用性相关的错误,提供了更接近决策点的临床数据,并以表格格式显示了警报文本。以表格格式显示警报文本可以帮助处方者快速提取信息,从而提高对警报的响应性。结论:此模拟研究提供了证据,将人为因素设计原则应用于药物警报可以改善可用性和规定结果。

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