将人为因素应用于改善临床决策支持的可用性以用于诊断决策：基于场景的模拟研究。
Application of human factors to improve usability of clinical decision support for diagnostic decision-making: a scenario-based simulation study.
机构信息
Department of Industrial and Systems Engineering, Wisconsin Institute for Healthcare Systems Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
Center for Quality and Productivity Improvement, University of Wisconsin-Madison, Madison, Wisconsin, USA.
出版信息
BMJ Qual Saf. 2020 Apr;29(4):329-340. doi: 10.1136/bmjqs-2019-009857. Epub 2019 Nov 27.
OBJECTIVE
In this study, we used human factors (HF) methods and principles to design a clinical decision support (CDS) that provides cognitive support to the pulmonary embolism (PE) diagnostic decision-making process in the emergency department. We hypothesised that the application of HF methods and principles will produce a more usable CDS that improves PE diagnostic decision-making, in particular decision about appropriate clinical pathway.
MATERIALS AND METHODS
We conducted a scenario-based simulation study to compare a HF-based CDS (the so-called CDS for PE diagnosis (PE-Dx CDS)) with a web-based CDS (MDCalc); 32 emergency physicians performed various tasks using both CDS. PE-Dx integrated HF design principles such as automating information acquisition and analysis, and minimising workload. We assessed all three dimensions of usability using both objective and subjective measures: effectiveness (eg, appropriate decision regarding the PE diagnostic pathway), efficiency (eg, time spent, perceived workload) and satisfaction (perceived usability of CDS).
RESULTS
Emergency physicians made more appropriate diagnostic decisions (94% with PE-Dx; 84% with web-based CDS; p<0.01) and performed experimental tasks faster with the PE-Dx CDS (on average 96 s per scenario with PE-Dx; 117 s with web-based CDS; p<0.001). They also reported lower workload (p<0.001) and higher satisfaction (p<0.001) with PE-Dx.
CONCLUSIONS
This simulation study shows that HF methods and principles can improve usability of CDS and diagnostic decision-making. Aspects of the HF-based CDS that provided cognitive support to emergency physicians and improved diagnostic performance included automation of information acquisition (eg, auto-populating risk scoring algorithms), minimisation of workload and support of decision selection (eg, recommending a clinical pathway). These HF design principles can be applied to the design of other CDS technologies to improve diagnostic safety.
目的
本研究运用人因工程学（HF）方法和原则，设计一种临床决策支持（CDS），为急诊科的肺栓塞（PE）诊断决策过程提供认知支持。我们假设应用 HF 方法和原则将产生更便于使用的 CDS，从而改善 PE 诊断决策，特别是关于适当临床路径的决策。
材料和方法
我们进行了一项基于场景的模拟研究，比较了一种基于 HF 的 CDS（所谓的 PE 诊断 CDS（PE-Dx CDS））与基于网络的 CDS（MDCalc）；32 名急诊医师使用这两种 CDS 执行各种任务。PE-Dx 集成了 HF 设计原则，例如自动获取和分析信息，以及最小化工作量。我们使用客观和主观测量方法评估了可用性的所有三个维度：效果（例如，关于 PE 诊断途径的适当决策）、效率（例如，花费的时间，感知的工作量）和满意度（对 CDS 的感知可用性）。
结果
急诊医师做出了更恰当的诊断决策（PE-Dx 为 94%；基于网络的 CDS 为 84%；p<0.01），并且使用 PE-Dx CDS 完成实验任务更快（PE-Dx 平均每个场景 96 秒；基于网络的 CDS 为 117 秒；p<0.001）。他们还报告说，使用 PE-Dx 的工作量（p<0.001）和满意度（p<0.001）较低。
结论
这项模拟研究表明，HF 方法和原则可以提高 CDS 的可用性和诊断决策质量。HF 为急诊医师提供认知支持并改善诊断性能的 CDS 方面包括信息采集自动化（例如，自动填充风险评分算法）、工作量最小化和决策选择支持（例如，推荐临床路径）。这些 HF 设计原则可以应用于其他 CDS 技术的设计，以提高诊断安全性。
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