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Tracking workflow during high-stakes resuscitation: the application of a novel clinician movement tracing tool during in situ trauma simulation
INTRODUCTION: Clinician movement and workflow analysis provides an opportunity to identify inefficiencies during trauma resuscitation care. Inefficient workflows may represent latent safety threats (LSTs), defined as unrecognised system-based elements that can negatively impact patients. In situ sim...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8936949/ https://www.ncbi.nlm.nih.gov/pubmed/35519836 http://dx.doi.org/10.1136/bmjstel-2017-000300 |
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author | Petrosoniak, Andrew Almeida, Rodrigo Pozzobon, Laura Danielle Hicks, Christopher Fan, Mark White, Kari McGowan, Melissa Trbovich, Patricia |
author_facet | Petrosoniak, Andrew Almeida, Rodrigo Pozzobon, Laura Danielle Hicks, Christopher Fan, Mark White, Kari McGowan, Melissa Trbovich, Patricia |
author_sort | Petrosoniak, Andrew |
collection | PubMed |
description | INTRODUCTION: Clinician movement and workflow analysis provides an opportunity to identify inefficiencies during trauma resuscitation care. Inefficient workflows may represent latent safety threats (LSTs), defined as unrecognised system-based elements that can negatively impact patients. In situ simulation (ISS) can be used to model resuscitation workflows without direct impact on patients. We report the pilot application of a novel, tracing tool to track clinician movement during high-fidelity ISS trauma sessions. METHODS: Twelve unannounced ISSs were conducted. An open source, Windows-based video overlay tracing tool was developed to generate a visual representation of participant movement during ISS. This tracing tool used a manual mouse tracking algorithm to produce point-by-point location information of a selected participant in a video. The tracing tool was applied to video recordings of clinicians performing a cricothyroidotomy during ISS trauma scenarios. A comparative workflow and movement analysis was completed, which included distance travelled and space utilisation. This data was visually represented with time-lapsed movement videos and heat maps. RESULTS: A fourfold difference in the relative distance travelled was observed between participants who performed a cricothyroidotomy during an ISS trauma resuscitation. Variation in each participant’s movement was attributable to three factors: (1) team role assignment and task allocation; (2) knowledge of clinical space: equipment location and path to equipment retrieval; and (3) equipment bundling. This tool facilitated LST identification related to cricothyroidotomy performance. CONCLUSION: This novel tracing tool effectively generated a visual representation of participants’ workflows and quantified movement during ISS video review. An improved understanding of human movement during ISS trauma resuscitations provides a unique opportunity to augment simulation debriefing, conduct human factor analysis of system elements (eg, tools/technology, physical environment/layout) and foster change management towards efficient workflows. |
format | Online Article Text |
id | pubmed-8936949 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-89369492022-05-04 Tracking workflow during high-stakes resuscitation: the application of a novel clinician movement tracing tool during in situ trauma simulation Petrosoniak, Andrew Almeida, Rodrigo Pozzobon, Laura Danielle Hicks, Christopher Fan, Mark White, Kari McGowan, Melissa Trbovich, Patricia BMJ Simul Technol Enhanc Learn Original Research INTRODUCTION: Clinician movement and workflow analysis provides an opportunity to identify inefficiencies during trauma resuscitation care. Inefficient workflows may represent latent safety threats (LSTs), defined as unrecognised system-based elements that can negatively impact patients. In situ simulation (ISS) can be used to model resuscitation workflows without direct impact on patients. We report the pilot application of a novel, tracing tool to track clinician movement during high-fidelity ISS trauma sessions. METHODS: Twelve unannounced ISSs were conducted. An open source, Windows-based video overlay tracing tool was developed to generate a visual representation of participant movement during ISS. This tracing tool used a manual mouse tracking algorithm to produce point-by-point location information of a selected participant in a video. The tracing tool was applied to video recordings of clinicians performing a cricothyroidotomy during ISS trauma scenarios. A comparative workflow and movement analysis was completed, which included distance travelled and space utilisation. This data was visually represented with time-lapsed movement videos and heat maps. RESULTS: A fourfold difference in the relative distance travelled was observed between participants who performed a cricothyroidotomy during an ISS trauma resuscitation. Variation in each participant’s movement was attributable to three factors: (1) team role assignment and task allocation; (2) knowledge of clinical space: equipment location and path to equipment retrieval; and (3) equipment bundling. This tool facilitated LST identification related to cricothyroidotomy performance. CONCLUSION: This novel tracing tool effectively generated a visual representation of participants’ workflows and quantified movement during ISS video review. An improved understanding of human movement during ISS trauma resuscitations provides a unique opportunity to augment simulation debriefing, conduct human factor analysis of system elements (eg, tools/technology, physical environment/layout) and foster change management towards efficient workflows. BMJ Publishing Group 2018-03-16 /pmc/articles/PMC8936949/ /pubmed/35519836 http://dx.doi.org/10.1136/bmjstel-2017-000300 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2019. All rights reserved. No commercial use is permitted unless otherwise expressly granted. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | Original Research Petrosoniak, Andrew Almeida, Rodrigo Pozzobon, Laura Danielle Hicks, Christopher Fan, Mark White, Kari McGowan, Melissa Trbovich, Patricia Tracking workflow during high-stakes resuscitation: the application of a novel clinician movement tracing tool during in situ trauma simulation |
title | Tracking workflow during high-stakes resuscitation: the application of a novel clinician movement tracing tool during in situ trauma simulation |
title_full | Tracking workflow during high-stakes resuscitation: the application of a novel clinician movement tracing tool during in situ trauma simulation |
title_fullStr | Tracking workflow during high-stakes resuscitation: the application of a novel clinician movement tracing tool during in situ trauma simulation |
title_full_unstemmed | Tracking workflow during high-stakes resuscitation: the application of a novel clinician movement tracing tool during in situ trauma simulation |
title_short | Tracking workflow during high-stakes resuscitation: the application of a novel clinician movement tracing tool during in situ trauma simulation |
title_sort | tracking workflow during high-stakes resuscitation: the application of a novel clinician movement tracing tool during in situ trauma simulation |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8936949/ https://www.ncbi.nlm.nih.gov/pubmed/35519836 http://dx.doi.org/10.1136/bmjstel-2017-000300 |
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