Viautour Julie, Naegeli Lukas, Braun Julia, Bergauer Lisa, Roche Tadzio R, Tscholl David W, Akbas Samira
Institute of Anesthesiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland.
Master Program in Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland.
Diagnostics (Basel). 2023 Nov 12;13(22):3432. doi: 10.3390/diagnostics13223432.
Patient monitoring is crucial in critical care medicine. Perceiving and interpreting multiple vital signs requires a high workload that can lead to decreased situation awareness and consequently inattentional blindness, defined as impaired perception of unexpectedly changing data. To facilitate information transfer, we developed and validated the Visual-Patient avatar. Generated by numerical data, the animation displays the status of vital signs and patient installations according to a user-centered design to improve situation awareness. As a surrogate parameter for information transfer in patient monitoring, we recorded visual attention using eye-tracking data. In this computer-based study, we compared the correlation of visually perceived and correctly interpreted vital signs between a Visual-Patient-avatar ICU and conventional patient monitoring. A total of 50 recruited study participants (25 nurses, 25 physicians) from five European study centers completed five randomized scenarios in both modalities. Using a stationary eye tracker as the primary endpoint, we recorded how long different areas of interest of the two monitoring modalities were viewed. In addition, we tested for a possible association between the length of time an area of interest was viewed and the correctness of the corresponding question. With the conventional monitor, participants looked at the installation site the longest (median 2.13-2.51 s). With the Visual-Patient-avatar ICU, gaze distribution was balanced; no area of interest was viewed for particularly long. For both modalities, the longer an area was viewed, the more likely the associated question was answered incorrectly (OR 0.97, 95% CI 0.95-0.99, = 0.008). The Visual-Patient-avatar ICU facilitates and improves information transfer through its visualizations, especially with written information. The longer an area of interest was viewed, the more likely the associated question was answered incorrectly.
患者监测在重症医学中至关重要。感知和解读多个生命体征需要大量精力，这可能导致态势感知能力下降，进而引发疏忽性盲视，即对意外变化的数据感知受损。为促进信息传递，我们开发并验证了可视化患者化身。该动画由数值数据生成，根据以用户为中心的设计展示生命体征和患者设备的状态，以提高态势感知。作为患者监测中信息传递的替代参数，我们使用眼动追踪数据记录视觉注意力。在这项基于计算机的研究中，我们比较了可视化患者化身重症监护病房（ICU）与传统患者监测中视觉感知和正确解读的生命体征之间的相关性。来自五个欧洲研究中心的50名招募的研究参与者（25名护士、25名医生）在两种模式下完成了五个随机场景。以固定眼动仪作为主要终点，我们记录了两种监测模式下不同感兴趣区域被注视的时长。此外，我们测试了注视感兴趣区域的时长与相应问题的正确性之间可能存在的关联。使用传统监测器时，参与者注视设备部位的时间最长（中位数为2.13 - 2.51秒）。使用可视化患者化身ICU时，注视分布较为均衡；没有哪个感兴趣区域被注视的时间特别长。对于两种模式，注视某个区域的时间越长，与之相关的问题被答错的可能性就越大（比值比0.97，95%置信区间0.95 - 0.99，P = 0.008）。可视化患者化身ICU通过其可视化手段促进并改善了信息传递，尤其是对于书面信息。注视感兴趣区域的时间越长，与之相关的问题被答错的可能性就越大。
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