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MP01: Use of an unmanned aerial vehicle to provide situational awareness in a simulated mass casualty incident

Published online by Cambridge University Press:  11 May 2018

A. K. Sibley*
Affiliation:
Department of Emergency Medicine, Dalhousie University, Stratford, PI
T. Jain
Affiliation:
Department of Emergency Medicine, Dalhousie University, Stratford, PI
B. Nicholson
Affiliation:
Department of Emergency Medicine, Dalhousie University, Stratford, PI
M. Butler
Affiliation:
Department of Emergency Medicine, Dalhousie University, Stratford, PI
S. David
Affiliation:
Department of Emergency Medicine, Dalhousie University, Stratford, PI
D. Smith
Affiliation:
Department of Emergency Medicine, Dalhousie University, Stratford, PI
P. Atkinson
Affiliation:
Department of Emergency Medicine, Dalhousie University, Stratford, PI
*
*Corresponding author

Abstract

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Introduction: Situational awareness (SA) is essential for maintenance of scene safety and effective resource allocation in mass casualty incidents (MCI). Unmanned aerial vehicles (UAV) can potentially enhance SA with real-time visual feedback during chaotic and evolving or inaccessible events. The purpose of this study was to test the ability of paramedics to use UAV video from a simulated MCI to identify scene hazards, initiate patient triage, and designate key operational locations. Methods: A simulated MCI, including fifteen patients of varying acuity (blast type injuries), plus four hazards, was created on a college campus. The scene was surveyed by UAV capturing video of all patients, hazards, surrounding buildings and streets. Attendees of a provincial paramedic meeting were invited to participate. Participants received a lecture on SALT Triage and the principles of MCI scene management. Next, they watched the UAV video footage. Participants were directed to sort patients according to SALT Triage step one, identify injuries, and localize the patients within the campus. Additionally, they were asked to select a start point for SALT Triage step two, identify and locate hazards, and designate locations for an Incident Command Post, Treatment Area, Transport Area and Access/Egress routes. Summary statistics were performed and a linear regression model was used to assess relationships between demographic variables and both patient triage and localization. Results: Ninety-six individuals participated. Mean age was 35 years (SD 11), 46% (44) were female, and 49% (47) were Primary Care Paramedics. Most participants (80 (84%)) correctly sorted at least 12 of 15 patients. Increased age was associated with decreased triage accuracy [-0.04(-0.07,-0.01);p=0.031]. Fifty-two (54%) were able to localize 12 or more of the 15 patients to a 27x 20m grid area. Advanced paramedic certification, and local residency were associated with improved patient localization [2.47(0.23,4.72);p=0.031], [-3.36(-5.61,-1.1);p=0.004]. The majority of participants (78 (81%)) chose an acceptable location to start SALT triage step two and 84% (80) identified at least three of four hazards. Approximately half (53 (55%)) of participants designated four or more of five key operational areas in appropriate locations. Conclusion: This study demonstrates the potential of UAV technology to remotely provide emergency responders with SA in a MCI. Additional research is required to further investigate optimal strategies to deploy UAVs in this context.

Type
Moderated Posters Presentations
Copyright
Copyright © Canadian Association of Emergency Physicians 2018