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Monitoring and Visualisation Support for Management of Medical Resources in Mass-Casualty Incidents
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
Visuell Systemteknik i Linköping AB Storskiftesgatan 29 SE-583 34 Linköping, Sweden.
Department of Military Technology National Defence College PO Box 27805, SE-115 93 Stockholm, Sweden.
(English)Manuscript (Other (popular science, discussion, etc.))
Abstract [en]

Improving command and control of rescue operations requires methods to elucidate the dynamic interaction between different teams in a rescue force in a stressful situation. To this end, we present a method to monitor and visualise the utilisation of medical resources in mass-casualty incidents. The flow of casualties is monitored at specific checkpoints where each individual is assigned a time stamp. This process generates a timeline for each casualty which shows, in great detail, how he or she was transferred through the chain of medical attendance. These timelines can be combined to model the flow of casualties from the location of the incident, through various aid stations and assembly areas, to hospitals. The resulting flow model can be visualised using a software tool. We have applied the method to training exercises where we used it both to support debriefing after the exercise and to facilitate subsequent, in-depth analysis. We conclude by exploring ways to use time-stamped checkpoints as a means of supporting the management of medical resources in real emergency operations.

Keyword [en]
Rimed checkpoints, timelines, utilisation of medical resources, flow of casualties, emergency response training, mission training, exercise analysis and evaluation
National Category
Computer Science
URN: urn:nbn:se:liu:diva-15616OAI: diva2:126768
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2010-01-14Bibliographically approved
In thesis
1. Using Observers for Model Based Data Collection in Distributed Tactical Operations
Open this publication in new window or tab >>Using Observers for Model Based Data Collection in Distributed Tactical Operations
2008 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Modern information technology increases the use of computers in training systems as well as in command-and-control systems in military services and public-safety organizations. This computerization combined with new threats present a challenging complexity. Situational awareness in evolving distributed operations and follow-up in training systems depends on humans in the field reporting observations of events. The use of this observer-reported information can be largely improved by implementation of models supporting both reporting and computer representation of objects and phenomena in operations.

This thesis characterises and describes observer model-based data collection in distributed tactical operations, where multiple, dispersed units work to achieve common goals. Reconstruction and exploration of multimedia representations of operations is becoming an established means for supporting taskforce training. We explore how modelling of operational processes and entities can support observer data collection and increase information content in mission histories. We use realistic exercises for testing developed models, methods and tools for observer data collection and transfer results to live operations.

The main contribution of this thesis is the systematic description of the model-based approach to using observers for data collection. Methodological aspects in using humans to collect data to be used in information systems, and also modelling aspects for phenomena occurring in emergency response and communication areas contribute to the body of research. We describe a general methodology for using human observers to collect adequate data for use in information systems. In addition, we describe methods and tools to collect data on the chain of medical attendance in emergency response exercises, and on command-and-control processes in several domains.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2008. 75 p.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1386
Observers, model-based data collection, distributed tactical operations, taskforce training, communication analysis, reconstruction & exploration, extended link analysis, timed checkpoints, network based observer tool
National Category
Computer Science
urn:nbn:se:liu:diva-15620 (URN)LiU-Tek-Lic-2008:44 (Local ID)978-91-7393-751-1 (ISBN)LiU-Tek-Lic-2008:44 (Archive number)LiU-Tek-Lic-2008:44 (OAI)
2008-12-18, Alan Turing, hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (Swedish)
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2009-05-15Bibliographically approved

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Morin, Magnus
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