Division of Clinical Informatics, Nationwide Children's Hospital, Columbus, Ohio, United States.
Department of Pediatrics, The Ohio State University College of Medicine, Columbus, Ohio, United States.
Appl Clin Inform. 2020 Jan;11(1):46-58. doi: 10.1055/s-0039-3402757. Epub 2020 Jan 15.
Increased adoption of electronic health records (EHR) with integrated clinical decision support (CDS) systems has reduced some sources of error but has led to unintended consequences including alert fatigue. The "pop-up" or interruptive alert is often employed as it requires providers to acknowledge receipt of an alert by taking an action despite the potential negative effects of workflow interruption. We noted a persistent upward trend of interruptive alerts at our institution and increasing requests for new interruptive alerts.
Using Institute for Healthcare Improvement (IHI) quality improvement (QI) methodology, the primary objective was to reduce the total volume of interruptive alerts received by providers.
We created an interactive dashboard for baseline alert data and to monitor frequency and outcomes of alerts as well as to prioritize interventions. A key driver diagram was developed with a specific aim to decrease the number of interruptive alerts from a baseline of 7,250 to 4,700 per week (35%) over 6 months. Interventions focused on the following key drivers: appropriate alert display within workflow, clear alert content, alert governance and standardization, user feedback regarding overrides, and respect for user knowledge.
A total of 25 unique alerts accounted for 90% of the total interruptive alert volume. By focusing on these 25 alerts, we reduced interruptive alerts from 7,250 to 4,400 per week.
Systematic and structured improvements to interruptive alerts can lead to overall reduced interruptive alert burden. Using QI methods to prioritize our interventions allowed us to maximize our impact. Further evaluation should be done on the effects of reduced interruptive alerts on patient care outcomes, usability heuristics on cognitive burden, and direct feedback mechanisms on alert utility.
电子健康记录（EHR）与集成临床决策支持（CDS）系统的广泛采用减少了一些错误源，但也带来了意想不到的后果，包括警报疲劳。“弹出”或中断式警报通常被采用，因为它要求提供者采取行动来确认收到警报，尽管这可能会中断工作流程，但也会产生潜在的负面影响。我们注意到我们机构的中断式警报呈持续上升趋势，并且对新的中断式警报的需求不断增加。
使用医疗保健改善研究所（IHI）质量改进（QI）方法，主要目标是减少提供者收到的中断式警报总数。
我们创建了一个交互式仪表板，用于显示基线警报数据，并监控警报的频率和结果，以及确定干预措施的优先级。制定了一个关键驱动图，具体目标是在 6 个月内将中断式警报的数量从基线的 7250 个减少到 4700 个/周（减少 35%）。干预措施侧重于以下关键驱动因素：在工作流程中适当显示警报、清晰的警报内容、警报治理和标准化、用户对覆盖的反馈，以及尊重用户知识。
共有 25 个独特的警报占总中断式警报量的 90%。通过关注这 25 个警报，我们将中断式警报从 7250 个减少到每周 4400 个。
对中断式警报进行系统和结构化的改进可以总体减少中断式警报的负担。使用 QI 方法确定干预措施的优先级可以最大限度地提高我们的影响力。应进一步评估减少中断式警报对患者护理结果的影响、认知负担的可用性启发式以及对警报效用的直接反馈机制。
