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Effects of a standardized distraction on caregivers’ perceptive performance with avatar-based and conventional patient monitoring: a multicenter comparative study


Pfarr, Juliane; Ganter, Michael T; Spahn, Donat R; Noethiger, Christoph B; Tscholl, David W (2019). Effects of a standardized distraction on caregivers’ perceptive performance with avatar-based and conventional patient monitoring: a multicenter comparative study. Journal of Clinical Monitoring and Computing:Epub ahead of print.

Abstract

Patient monitoring requires constant attention and may be particularly vulnerable to distractions, which frequently occur during perioperative work. In this study, we compared anesthesia providers' perceptive performance and perceived workload under distraction for conventional and avatar-based monitoring, a situation awareness-based technology that displays patient status as an animated patient model. In this prospective, multicenter study with a within-subject design, 38 participants evaluated scenarios of 3- and 10-s durations using conventional and avatar-based monitoring, under standardized distraction in the form of a simple calculation task. We quantified perceptual performance as the number of vital signs correctly remembered out of the total of 11 vital signs shown. We quantified perceived workload using the National Aeronautics and Space Administration Task Load Index score. Anesthesia providers remembered more vital signs under distraction using the avatar monitoring technology in the 3-s scenario: 6 (interquartile range [IQR] 5-7) vs. 3 (IQR 2-4), p < 0.001, mean of differences (MoD): 3 (95% confidence interval [95% CI] 1 to 4), and in the 10-s monitoring task: 6 (IQR 5-8) vs. 4 (IQR 2-7), p = 0.028, MoD: 1 (95% CI 0.2 to 3). Participants rated perceived workload lower under distraction with the avatar in the 3-s scenario: 65 (IQR 40-79) vs. 75 (IQR 51-88), p = 0.007, MoD: 9 (95% CI 3 to 15), and in the 10-s scenario: 68 (IQR 50-80) vs. 75 (IQR 65-86), p = 0.019, MoD: 10 (95% CI 2 to 18). Avatar-based monitoring improved anesthesia providers' perceptive performance under distraction and reduced perceived workload. This technology could help to improve caregivers' situation awareness, especially in high-workload situations.

Abstract

Patient monitoring requires constant attention and may be particularly vulnerable to distractions, which frequently occur during perioperative work. In this study, we compared anesthesia providers' perceptive performance and perceived workload under distraction for conventional and avatar-based monitoring, a situation awareness-based technology that displays patient status as an animated patient model. In this prospective, multicenter study with a within-subject design, 38 participants evaluated scenarios of 3- and 10-s durations using conventional and avatar-based monitoring, under standardized distraction in the form of a simple calculation task. We quantified perceptual performance as the number of vital signs correctly remembered out of the total of 11 vital signs shown. We quantified perceived workload using the National Aeronautics and Space Administration Task Load Index score. Anesthesia providers remembered more vital signs under distraction using the avatar monitoring technology in the 3-s scenario: 6 (interquartile range [IQR] 5-7) vs. 3 (IQR 2-4), p < 0.001, mean of differences (MoD): 3 (95% confidence interval [95% CI] 1 to 4), and in the 10-s monitoring task: 6 (IQR 5-8) vs. 4 (IQR 2-7), p = 0.028, MoD: 1 (95% CI 0.2 to 3). Participants rated perceived workload lower under distraction with the avatar in the 3-s scenario: 65 (IQR 40-79) vs. 75 (IQR 51-88), p = 0.007, MoD: 9 (95% CI 3 to 15), and in the 10-s scenario: 68 (IQR 50-80) vs. 75 (IQR 65-86), p = 0.019, MoD: 10 (95% CI 2 to 18). Avatar-based monitoring improved anesthesia providers' perceptive performance under distraction and reduced perceived workload. This technology could help to improve caregivers' situation awareness, especially in high-workload situations.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Institute of Anesthesiology
Dewey Decimal Classification:610 Medicine & health
Uncontrolled Keywords:Anesthesiology and Pain Medicine, Health Informatics, Critical Care and Intensive Care Medicine
Language:English
Date:25 November 2019
Deposited On:05 Dec 2019 13:44
Last Modified:06 Dec 2019 09:00
Publisher:Springer
ISSN:1387-1307
OA Status:Closed
Publisher DOI:https://doi.org/10.1007/s10877-019-00429-2
PubMed ID:31768924

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