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Human-centered visualization technologies for patient monitoring are the future: a narrative review
Medical technology innovation has improved patient monitoring in perioperative and intensive care medicine and continuous improvement in the technology is now a central focus in this field. Because data density increases with the number of parameters captured by patient-monitoring devices, its inter...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10308796/ https://www.ncbi.nlm.nih.gov/pubmed/37381008 http://dx.doi.org/10.1186/s13054-023-04544-0 |
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author | Gasciauskaite, Greta Lunkiewicz, Justyna Roche, Tadzio R. Spahn, Donat R. Nöthiger, Christoph B. Tscholl, David W. |
author_facet | Gasciauskaite, Greta Lunkiewicz, Justyna Roche, Tadzio R. Spahn, Donat R. Nöthiger, Christoph B. Tscholl, David W. |
author_sort | Gasciauskaite, Greta |
collection | PubMed |
description | Medical technology innovation has improved patient monitoring in perioperative and intensive care medicine and continuous improvement in the technology is now a central focus in this field. Because data density increases with the number of parameters captured by patient-monitoring devices, its interpretation has become more challenging. Therefore, it is necessary to support clinicians in managing information overload while improving their awareness and understanding about the patient’s health status. Patient monitoring has almost exclusively operated on the single-sensor–single-indicator principle—a technology-centered way of presenting data in which specific parameters are measured and displayed individually as separate numbers and waves. An alternative is user-centered medical visualization technology, which integrates multiple pieces of information (e.g., vital signs), derived from multiple sensors into a single indicator—an avatar-based visualization—that is a meaningful representation of the real-world situation. Data are presented as changing shapes, colors, and animation frequencies, which can be perceived, integrated, and interpreted much more efficiently than other formats (e.g., numbers). The beneficial effects of these technologies have been confirmed in computer-based simulation studies; visualization technologies improved clinicians’ situation awareness by helping them effectively perceive and verbalize the underlying medical issue, while improving diagnostic confidence and reducing workload. This review presents an overview of the scientific results and the evidence for the validity of these technologies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13054-023-04544-0. |
format | Online Article Text |
id | pubmed-10308796 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103087962023-06-30 Human-centered visualization technologies for patient monitoring are the future: a narrative review Gasciauskaite, Greta Lunkiewicz, Justyna Roche, Tadzio R. Spahn, Donat R. Nöthiger, Christoph B. Tscholl, David W. Crit Care Review Medical technology innovation has improved patient monitoring in perioperative and intensive care medicine and continuous improvement in the technology is now a central focus in this field. Because data density increases with the number of parameters captured by patient-monitoring devices, its interpretation has become more challenging. Therefore, it is necessary to support clinicians in managing information overload while improving their awareness and understanding about the patient’s health status. Patient monitoring has almost exclusively operated on the single-sensor–single-indicator principle—a technology-centered way of presenting data in which specific parameters are measured and displayed individually as separate numbers and waves. An alternative is user-centered medical visualization technology, which integrates multiple pieces of information (e.g., vital signs), derived from multiple sensors into a single indicator—an avatar-based visualization—that is a meaningful representation of the real-world situation. Data are presented as changing shapes, colors, and animation frequencies, which can be perceived, integrated, and interpreted much more efficiently than other formats (e.g., numbers). The beneficial effects of these technologies have been confirmed in computer-based simulation studies; visualization technologies improved clinicians’ situation awareness by helping them effectively perceive and verbalize the underlying medical issue, while improving diagnostic confidence and reducing workload. This review presents an overview of the scientific results and the evidence for the validity of these technologies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13054-023-04544-0. BioMed Central 2023-06-28 /pmc/articles/PMC10308796/ /pubmed/37381008 http://dx.doi.org/10.1186/s13054-023-04544-0 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Review Gasciauskaite, Greta Lunkiewicz, Justyna Roche, Tadzio R. Spahn, Donat R. Nöthiger, Christoph B. Tscholl, David W. Human-centered visualization technologies for patient monitoring are the future: a narrative review |
title | Human-centered visualization technologies for patient monitoring are the future: a narrative review |
title_full | Human-centered visualization technologies for patient monitoring are the future: a narrative review |
title_fullStr | Human-centered visualization technologies for patient monitoring are the future: a narrative review |
title_full_unstemmed | Human-centered visualization technologies for patient monitoring are the future: a narrative review |
title_short | Human-centered visualization technologies for patient monitoring are the future: a narrative review |
title_sort | human-centered visualization technologies for patient monitoring are the future: a narrative review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10308796/ https://www.ncbi.nlm.nih.gov/pubmed/37381008 http://dx.doi.org/10.1186/s13054-023-04544-0 |
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