VisCoMET: Visually Analyzing Team Collaboration in Medical Emergency Trainings

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dc.contributor.authorLiebers, Carinaen_US
dc.contributor.authorAgarwal, Shivamen_US
dc.contributor.authorKrug, Maximilianen_US
dc.contributor.authorPitsch, Karolaen_US
dc.contributor.authorBeck, Fabianen_US
dc.contributor.editorBujack, Roxanaen_US
dc.contributor.editorArchambault, Danielen_US
dc.contributor.editorSchreck, Tobiasen_US
dc.date.accessioned2023-06-10T06:16:35Z
dc.date.available2023-06-10T06:16:35Z
dc.date.issued2023
dc.description.abstractHandling emergencies requires efficient and effective collaboration of medical professionals. To analyze their performance, in an application study, we have developed VisCoMET, a visual analytics approach displaying interactions of healthcare personnel in a triage training of a mass casualty incident. The application scenario stems from social interaction research, where the collaboration of teams is studied from different perspectives. We integrate recorded annotations from multiple sources, such as recorded videos of the sessions, transcribed communication, and eye-tracking information. For each session, an informationrich timeline visualizes events across these different channels, specifically highlighting interactions between the team members. We provide algorithmic support to identify frequent event patterns and to search for user-defined event sequences. Comparing different teams, an overview visualization aggregates each training session in a visual glyph as a node, connected to similar sessions through edges. An application example shows the usage of the approach in the comparative analysis of triage training sessions, where multiple teams encountered the same scene, and highlights discovered insights. The approach was evaluated through feedback from visualization and social interaction experts. The results show that the approach supports reflecting on teams' performance by exploratory analysis of collaboration behavior while particularly enabling the comparison of triage training sessions.en_US
dc.description.number3
dc.description.sectionheadersVisualization Techniques I: Sequences and High-dimensional Data
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14819
dc.identifier.issn1467-8659
dc.identifier.pages149-160
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14819
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14819
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectCCS Concepts: Human-centered computing -> Visualization techniques; Information visualization
dc.subjectHuman centered computing
dc.subjectVisualization techniques
dc.subjectInformation visualization
dc.titleVisCoMET: Visually Analyzing Team Collaboration in Medical Emergency Trainingsen_US
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