Avoiding alert fatigue in pulmonary embolism decision support: a new method to examine 'trigger rates'.
Avoiding alert fatigue in pulmonary embolism decision support: a new method to examine 'trigger rates'.
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DOI：
10.1136/ebmed-2016-110440
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发表时间：
2016-12-01
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影响因子：
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通讯作者：
McGinn, Thomas
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文献类型：
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作者：
Press, Anne;Khan, Sundas;McGinn, Thomas
临床决策支持系统（CDSS）集成到电子健康记录（EHR）中，使医生能够轻松使用临床决策支持（CDS）工具。然而，CDSS通常被集成到EHR中，采用率很低。其中一个原因是次要的“触发疲劳”。因此，我们开发了一个新的和创新的可用性过程，称为“敏感性和特异性触发分析”（SSTA），作为我们围绕肺栓塞决策支持工具的更大项目的一部分。通过使用正式的分析方法，SSTA将使程序员能够在将CDS工具集成到EHR之前检查最佳触发率。我们进行了回顾性病历审查。关注的结局是医生订购的CT血管造影（CTA）。表示与肺栓塞相关的常见症状的短语被评估为CDSS工具的可能触发因素。然后，我们分析了每个触发因素预测医生订购CTA的能力。我们发现，在保持高特异性的同时触发肺栓塞CDS工具的最敏感方式是将1个或多个相关症状与威尔斯标准的1个或多个要素结合。这项研究探讨了一种独特的方法，SSTA，用于限制不准确的触发CDS工具集成到EHR之前。这种方法可以应用于其他研究，旨在降低触发率和提高采用率的先前验证的CDSS工具。
A clinical decision support system (CDSS) is integrated into the electronic health record (EHR) and allows physicians to easily use a clinical decision support (CDS) tool. However, often CDSSs are integrated into the EHR with poor adoption rates. One reason for this is secondary to 'trigger fatigue'. Therefore, we developed a new and innovative usability process named 'sensitivity and specificity trigger analysis' (SSTA) as part of our larger project around a pulmonary embolism decision support tool. SSTA will enable programmers to examine optimal trigger rates prior to the integration of a CDS tool into the EHR, by using a formal method of analysis. We performed a retrospective chart review. The outcome of interest was physician ordering of a CT angiography (CTA). Phrases that signify common symptoms associated with pulmonary embolism were assessed as possible triggers for the CDSS tool. We then analysed each trigger's ability to predict physician ordering of a CTA. We found that the most sensitive way to trigger the Pulmonary Embolism CDS tool while still maintaining a high specificity was by combining 1 or more pertinent symptoms with 1 or more elements of the Wells criteria. This study explored a unique methodology, SSTA, used to limit inaccurate triggering of a CDS tool prior to integration into the EHR. This methodology can be applied to other studies aiming to decrease triggering rates and increase adoption rates of previously validated CDSS tools.