Jungk A, Thull B, Hoeft A, Rau G
Helmholtz-Institute for Biomedical Engineering at the Aachen University of Technology, Aachen, Germany.
J Clin Monit Comput. 2000;16(4):243-58. doi: 10.1023/a:1011462726040.
Currently, vital parameters are commonly displayed as trends along a timeline. However, clinical decisions are more often based upon concepts, such as the depth of anesthesia, that are derived by combining parameter relationships and additional context information. The current displays do not visualize such concepts and therefore do not optimally support the decision process. A new display should present an ecological interface (EI). The principle of EI design is to visualize all of the information necessary for decision making in one single display.
In the first approach, we developed an EI that visualizes 35 relevant parameters for anesthesia monitoring. All of the parameters are generated by an anesthesia software simulator. Sixteen anesthetists had to administer two simulated general anesthetics: in one setting working only with the simulator's monitors ("Sim Only"), and in another setting working with the simulator's monitors in combination with the EI ("Combi1"). During each experiment, one unexpected critical incident (either blood loss or a cuff leakage) had to be identified. The control and monitoring behavior was analyzed by recording the subjects' eye movements and think-aloud protocol. With the help of the eye-tracking results, we re-designed the EI. The new EI was then tested with no eye tracking ("Combi2") on eight anesthetists under analogous conditions as in "Combi1."
Cuff leakage was identified significantly quicker in "Combi1" (7 of 8 cases; time (T): 65 s +/- 73 s) than in "SimOnly" (6 of 8 cases; T: 222 s +/- 187 s). Blood loss was identified in 5 of 8 cases (T: 215 s +/- 76 s) in "Combi1" as quickly as in "SimOnly" (all cases; T: 217 s +/- 72 s). In "Combi1," the EI was used as the main source of information (in 43 +/- 19% of time) and was frequently favored when identifying an evolving critical incident. In "Combi2," cuff leakage was identified in 7 of 8 cases (T: 70 s +/- 111 s) as quickly as in "Combi1." Blood loss was identified significantly quicker in all cases (T: 147 s +/- 62 s) in "Combi2" than in "Combi1" and in "SimOnly."
The results have shown that appropriately designed EIs may improve the anesthetist's decision making and focus attention on specific problems. Now, the findings have to be tested in future studies by widening the scope using other simulated scenarios and being closer to reality under real conditions in the OR. Eye tracking proved to be a useful method to analyze the anesthetists' decision making and appropriately re-design interfaces.
目前，生命体征参数通常沿时间轴以趋势形式显示。然而，临床决策更多地基于诸如麻醉深度等概念，这些概念是通过结合参数关系和其他背景信息得出的。当前的显示方式并未将此类概念可视化，因此无法最佳地支持决策过程。一种新的显示方式应呈现生态界面（EI）。EI设计的原则是在单一显示中可视化决策所需的所有信息。
在第一种方法中，我们开发了一种EI，可将35个与麻醉监测相关的参数可视化。所有参数均由麻醉软件模拟器生成。16名麻醉师必须实施两种模拟全身麻醉：一种情况是仅使用模拟器的监视器工作（“仅模拟器”），另一种情况是将模拟器的监视器与EI结合使用（“组合1”）。在每个实验过程中，必须识别出一个意外的关键事件（失血或袖带漏气）。通过记录受试者的眼动和出声思维协议来分析控制和监测行为。借助眼动追踪结果，我们重新设计了EI。然后在与“组合1”类似的条件下，对8名麻醉师进行无眼动追踪测试（“组合2”）。
在“组合1”中识别袖带漏气的速度明显快于“仅模拟器”（8例中有7例；时间（T）：65秒±73秒）（8例中有6例；T：222秒±187秒）。在“组合1”中，8例中有5例（T：215秒±76秒）识别出失血情况，与“仅模拟器”（所有病例；T：217秒±72秒）一样快。在“组合1”中，EI被用作主要信息来源（占43±19%的时间）且在识别正在发展的关键事件时经常受到青睐。在“组合2”中，8例中有7例（T：70秒±111秒）识别出袖带漏气，与“组合1”一样快。在“组合2”中，所有病例识别失血情况的速度均明显快于“组合1”和“仅模拟器”（T：147秒±62秒）。
结果表明，设计得当的EI可能会改善麻醉师的决策，并将注意力集中在特定问题上。现在，这些发现必须在未来的研究中通过扩大范围，使用其他模拟场景并在手术室的实际条件下更接近现实来进行测试。眼动追踪被证明是分析麻醉师决策并适当重新设计界面的有用方法。
