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Visual Blood, a 3D Animated Computer Model to Optimize the Interpretation of Blood Gas Analysis
Acid–base homeostasis is crucial for all physiological processes in the body and is evaluated using arterial blood gas (ABG) analysis. Screens or printouts of ABG results require the interpretation of many textual elements and numbers, which may delay intuitive comprehension. To optimise the present...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10045057/ https://www.ncbi.nlm.nih.gov/pubmed/36978684 http://dx.doi.org/10.3390/bioengineering10030293 |
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author | Schweiger, Giovanna Malorgio, Amos Henckert, David Braun, Julia Meybohm, Patrick Hottenrott, Sebastian Froehlich, Corinna Zacharowski, Kai Raimann, Florian J. Piekarski, Florian Noethiger, Christoph B. Spahn, Donat R. Tscholl, David W. Roche, Tadzio R. |
author_facet | Schweiger, Giovanna Malorgio, Amos Henckert, David Braun, Julia Meybohm, Patrick Hottenrott, Sebastian Froehlich, Corinna Zacharowski, Kai Raimann, Florian J. Piekarski, Florian Noethiger, Christoph B. Spahn, Donat R. Tscholl, David W. Roche, Tadzio R. |
author_sort | Schweiger, Giovanna |
collection | PubMed |
description | Acid–base homeostasis is crucial for all physiological processes in the body and is evaluated using arterial blood gas (ABG) analysis. Screens or printouts of ABG results require the interpretation of many textual elements and numbers, which may delay intuitive comprehension. To optimise the presentation of the results for the specific strengths of human perception, we developed Visual Blood, an animated virtual model of ABG results. In this study, we compared its performance with a conventional result printout. Seventy physicians from three European university hospitals participated in a computer-based simulation study. Initially, after an educational video, we tested the participants’ ability to assign individual Visual Blood visualisations to their corresponding ABG parameters. As the primary outcome, we tested caregivers’ ability to correctly diagnose simulated clinical ABG scenarios with Visual Blood or conventional ABG printouts. For user feedback, participants rated their agreement with statements at the end of the study. Physicians correctly assigned 90% of the individual Visual Blood visualisations. Regarding the primary outcome, the participants made the correct diagnosis 86% of the time when using Visual Blood, compared to 68% when using the conventional ABG printout. A mixed logistic regression model showed an odds ratio for correct diagnosis of 3.4 (95%CI 2.00–5.79, p < 0.001) and an odds ratio for perceived diagnostic confidence of 1.88 (95%CI 1.67–2.11, p < 0.001) in favour of Visual Blood. A linear mixed model showed a coefficient for perceived workload of −3.2 (95%CI −3.77 to −2.64) in favour of Visual Blood. Fifty-one of seventy (73%) participants agreed or strongly agreed that Visual Blood was easy to use, and fifty-five of seventy (79%) agreed that it was fun to use. In conclusion, Visual Blood improved physicians’ ability to diagnose ABG results. It also increased perceived diagnostic confidence and reduced perceived workload. This study adds to the growing body of research showing that decision-support tools developed around human cognitive abilities can streamline caregivers’ decision-making and may improve patient care. |
format | Online Article Text |
id | pubmed-10045057 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100450572023-03-29 Visual Blood, a 3D Animated Computer Model to Optimize the Interpretation of Blood Gas Analysis Schweiger, Giovanna Malorgio, Amos Henckert, David Braun, Julia Meybohm, Patrick Hottenrott, Sebastian Froehlich, Corinna Zacharowski, Kai Raimann, Florian J. Piekarski, Florian Noethiger, Christoph B. Spahn, Donat R. Tscholl, David W. Roche, Tadzio R. Bioengineering (Basel) Article Acid–base homeostasis is crucial for all physiological processes in the body and is evaluated using arterial blood gas (ABG) analysis. Screens or printouts of ABG results require the interpretation of many textual elements and numbers, which may delay intuitive comprehension. To optimise the presentation of the results for the specific strengths of human perception, we developed Visual Blood, an animated virtual model of ABG results. In this study, we compared its performance with a conventional result printout. Seventy physicians from three European university hospitals participated in a computer-based simulation study. Initially, after an educational video, we tested the participants’ ability to assign individual Visual Blood visualisations to their corresponding ABG parameters. As the primary outcome, we tested caregivers’ ability to correctly diagnose simulated clinical ABG scenarios with Visual Blood or conventional ABG printouts. For user feedback, participants rated their agreement with statements at the end of the study. Physicians correctly assigned 90% of the individual Visual Blood visualisations. Regarding the primary outcome, the participants made the correct diagnosis 86% of the time when using Visual Blood, compared to 68% when using the conventional ABG printout. A mixed logistic regression model showed an odds ratio for correct diagnosis of 3.4 (95%CI 2.00–5.79, p < 0.001) and an odds ratio for perceived diagnostic confidence of 1.88 (95%CI 1.67–2.11, p < 0.001) in favour of Visual Blood. A linear mixed model showed a coefficient for perceived workload of −3.2 (95%CI −3.77 to −2.64) in favour of Visual Blood. Fifty-one of seventy (73%) participants agreed or strongly agreed that Visual Blood was easy to use, and fifty-five of seventy (79%) agreed that it was fun to use. In conclusion, Visual Blood improved physicians’ ability to diagnose ABG results. It also increased perceived diagnostic confidence and reduced perceived workload. This study adds to the growing body of research showing that decision-support tools developed around human cognitive abilities can streamline caregivers’ decision-making and may improve patient care. MDPI 2023-02-25 /pmc/articles/PMC10045057/ /pubmed/36978684 http://dx.doi.org/10.3390/bioengineering10030293 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Schweiger, Giovanna Malorgio, Amos Henckert, David Braun, Julia Meybohm, Patrick Hottenrott, Sebastian Froehlich, Corinna Zacharowski, Kai Raimann, Florian J. Piekarski, Florian Noethiger, Christoph B. Spahn, Donat R. Tscholl, David W. Roche, Tadzio R. Visual Blood, a 3D Animated Computer Model to Optimize the Interpretation of Blood Gas Analysis |
title | Visual Blood, a 3D Animated Computer Model to Optimize the Interpretation of Blood Gas Analysis |
title_full | Visual Blood, a 3D Animated Computer Model to Optimize the Interpretation of Blood Gas Analysis |
title_fullStr | Visual Blood, a 3D Animated Computer Model to Optimize the Interpretation of Blood Gas Analysis |
title_full_unstemmed | Visual Blood, a 3D Animated Computer Model to Optimize the Interpretation of Blood Gas Analysis |
title_short | Visual Blood, a 3D Animated Computer Model to Optimize the Interpretation of Blood Gas Analysis |
title_sort | visual blood, a 3d animated computer model to optimize the interpretation of blood gas analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10045057/ https://www.ncbi.nlm.nih.gov/pubmed/36978684 http://dx.doi.org/10.3390/bioengineering10030293 |
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