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Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study
Patient monitoring is the foundation of intensive care medicine. High workload and information overload can impair situation awareness of staff, thus leading to loss of important information about patients’ conditions. To facilitate mental processing of patient monitoring data, we developed the Visu...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10088750/ https://www.ncbi.nlm.nih.gov/pubmed/37041316 http://dx.doi.org/10.1038/s41598-023-33027-z |
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author | Bergauer, Lisa Braun, Julia Roche, Tadzio Raoul Meybohm, Patrick Hottenrott, Sebastian Zacharowski, Kai Raimann, Florian Jürgen Rivas, Eva López-Baamonde, Manuel Ganter, Michael Thomas Nöthiger, Christoph Beat Spahn, Donat R. Tscholl, David Werner Akbas, Samira |
author_facet | Bergauer, Lisa Braun, Julia Roche, Tadzio Raoul Meybohm, Patrick Hottenrott, Sebastian Zacharowski, Kai Raimann, Florian Jürgen Rivas, Eva López-Baamonde, Manuel Ganter, Michael Thomas Nöthiger, Christoph Beat Spahn, Donat R. Tscholl, David Werner Akbas, Samira |
author_sort | Bergauer, Lisa |
collection | PubMed |
description | Patient monitoring is the foundation of intensive care medicine. High workload and information overload can impair situation awareness of staff, thus leading to loss of important information about patients’ conditions. To facilitate mental processing of patient monitoring data, we developed the Visual-Patient-avatar Intensive Care Unit (ICU), a virtual patient model animated from vital signs and patient installation data. It incorporates user-centred design principles to foster situation awareness. This study investigated the avatar’s effects on information transfer measured by performance, diagnostic confidence and perceived workload. This computer-based study compared Visual-Patient-avatar ICU and conventional monitor modality for the first time. We recruited 25 nurses and 25 physicians from five centres. The participants completed an equal number of scenarios in both modalities. Information transfer, as the primary outcome, was defined as correctly assessing vital signs and installations. Secondary outcomes included diagnostic confidence and perceived workload. For analysis, we used mixed models and matched odds ratios. Comparing 250 within-subject cases revealed that Visual-Patient-avatar ICU led to a higher rate of correctly assessed vital signs and installations [rate ratio (RR) 1.25; 95% CI 1.19–1.31; P < 0.001], strengthened diagnostic confidence [odds ratio (OR) 3.32; 95% CI 2.15–5.11, P < 0.001] and lowered perceived workload (coefficient − 7.62; 95% CI − 9.17 to − 6.07; P < 0.001) than conventional modality. Using Visual-Patient-avatar ICU, participants retrieved more information with higher diagnostic confidence and lower perceived workload compared to the current industry standard monitor. |
format | Online Article Text |
id | pubmed-10088750 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100887502023-04-12 Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study Bergauer, Lisa Braun, Julia Roche, Tadzio Raoul Meybohm, Patrick Hottenrott, Sebastian Zacharowski, Kai Raimann, Florian Jürgen Rivas, Eva López-Baamonde, Manuel Ganter, Michael Thomas Nöthiger, Christoph Beat Spahn, Donat R. Tscholl, David Werner Akbas, Samira Sci Rep Article Patient monitoring is the foundation of intensive care medicine. High workload and information overload can impair situation awareness of staff, thus leading to loss of important information about patients’ conditions. To facilitate mental processing of patient monitoring data, we developed the Visual-Patient-avatar Intensive Care Unit (ICU), a virtual patient model animated from vital signs and patient installation data. It incorporates user-centred design principles to foster situation awareness. This study investigated the avatar’s effects on information transfer measured by performance, diagnostic confidence and perceived workload. This computer-based study compared Visual-Patient-avatar ICU and conventional monitor modality for the first time. We recruited 25 nurses and 25 physicians from five centres. The participants completed an equal number of scenarios in both modalities. Information transfer, as the primary outcome, was defined as correctly assessing vital signs and installations. Secondary outcomes included diagnostic confidence and perceived workload. For analysis, we used mixed models and matched odds ratios. Comparing 250 within-subject cases revealed that Visual-Patient-avatar ICU led to a higher rate of correctly assessed vital signs and installations [rate ratio (RR) 1.25; 95% CI 1.19–1.31; P < 0.001], strengthened diagnostic confidence [odds ratio (OR) 3.32; 95% CI 2.15–5.11, P < 0.001] and lowered perceived workload (coefficient − 7.62; 95% CI − 9.17 to − 6.07; P < 0.001) than conventional modality. Using Visual-Patient-avatar ICU, participants retrieved more information with higher diagnostic confidence and lower perceived workload compared to the current industry standard monitor. Nature Publishing Group UK 2023-04-11 /pmc/articles/PMC10088750/ /pubmed/37041316 http://dx.doi.org/10.1038/s41598-023-33027-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Bergauer, Lisa Braun, Julia Roche, Tadzio Raoul Meybohm, Patrick Hottenrott, Sebastian Zacharowski, Kai Raimann, Florian Jürgen Rivas, Eva López-Baamonde, Manuel Ganter, Michael Thomas Nöthiger, Christoph Beat Spahn, Donat R. Tscholl, David Werner Akbas, Samira Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study |
title | Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study |
title_full | Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study |
title_fullStr | Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study |
title_full_unstemmed | Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study |
title_short | Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study |
title_sort | avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10088750/ https://www.ncbi.nlm.nih.gov/pubmed/37041316 http://dx.doi.org/10.1038/s41598-023-33027-z |
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