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

  • Juliane Pfarr
  • Michael T. Ganter
  • Donat R. Spahn
  • Christoph B. Noethiger
  • David W. TschollEmail author
Original Research
  • 28 Downloads

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.

Keywords

Situation awareness Patient monitoring Computer-assisted diagnosis Visual patient 

Abbreviations

CO2

Carbon dioxide

PASAT

Paced auditory serial additions test

NASA

National Aeronautics and Space Administration

TLX

Task Load Index

MoD

Mean of differences

95% CI

95% Confidence interval

IQR

Interquartile range

Notes

Author contributions

JP: helped design the study, collect the data, analyze the data, write the article and approved the final version. MTG: helped collect the data, write the article and approved the final version. DRS: helped design the study, write the article and approved the final version. CBN: helped design the study, collect the data, analyze the data, write the article and approved the final version. DWT: helped design the study, collect the data, analyze the data, write the article and approved the final version.

Funding

Institute of Anesthesiology, University, and University Hospital Zurich: institutional funding. Institute of Anesthesiology and Pain Therapy, Cantonal Hospital Winterthur: institutional funding. University of Zurich: Proof of concept funding (UZ16/288POC). University of Zurich: DWT career development grant.

Compliance with ethical standards

Conflict of interest

The University of Zurich and Koninklijke Philips N.V., Amsterdam entered a joint development and licensing agreement to develop an avatar-based product. As part of this agreement, the authors DWT and CBN may receive royalties.

Supplementary material

Supplementary material 1 (MP4 105650 kb)

10877_2019_429_MOESM2_ESM.m4v (72.5 mb)
Supplementary material 2 (M4 V 74258 kb)

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Institute of AnesthesiologyUniversity and University Hospital ZurichZurichSwitzerland
  2. 2.Institute of Anesthesiology and Pain Therapy, Cantonal Hospital WinterthurWinterthurSwitzerland

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