Comparison of Unmanned Aerial Vehicle Technology Versus Standard Practice in Identification of Hazards at a Mass Casualty Incident Scenario by Primary Care Paramedic Students

2018 ◽  
Vol 12 (5) ◽  
pp. 631-634 ◽  
Author(s):  
Trevor Jain ◽  
Aaron Sibley ◽  
Henrik Stryhn ◽  
Ives Hubloue
Keyword(s):  
Situational Awareness ◽  
Permutation Test ◽  
Mass Casualty Incident ◽  
Mass Casualty ◽  
Hazard Identification ◽  
Identification Accuracy ◽  
Standard Practice ◽  
Ground Station ◽  
Aerial Vehicle ◽  
Observational Cohort

AbstractIntroductionThe proliferation of unmanned aerial vehicles (UAV) has the potential to change the situational awareness of incident commanders allowing greater scene safety. The aim of this study was to compare UAV technology to standard practice (SP) in hazard identification during a simulated multi-vehicle motor collision (MVC) in terms of time to identification, accuracy and the order of hazard identification.MethodsA prospective observational cohort study was conducted with 21 students randomized into UAV or SP group, based on a MVC with 7 hazards. The UAV group remained at the UAV ground station while the SP group approached the scene. After identifying hazards the time and order was recorded.ResultsThe mean time (SD, range) to identify the hazards were 3 minutes 41 seconds (1 minute 37 seconds, 1 minute 48 seconds-6 minutes 51 seconds) and 2 minutes 43 seconds (55 seconds, 1 minute 43 seconds-4 minutes 38 seconds) in UAV and SP groups corresponding to a mean difference of 58 seconds (P=0.11). A non-parametric permutation test showed a significant (P=0.04) difference in identification order.ConclusionBoth groups had 100% accuracy in hazard identification with no statistical difference in time for hazard identification. A difference was found in the identification order of hazards. (Disaster Med Public Health Preparedness. 2018;12:631–634)

Comparison of Unmanned Aerial Vehicle Technology-Assisted Triage versus Standard Practice in Triaging Casualties by Paramedic Students in a Mass-Casualty Incident Scenario

2018 ◽  
Vol 33 (4) ◽  
pp. 375-380 ◽  
Author(s):  
Trevor Jain ◽  
Aaron Sibley ◽  
Henrik Stryhn ◽  
Ives Hubloue
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Prince Edward Island ◽  
Motor Vehicle ◽  
Mass Casualty Incident ◽  
Mass Casualty ◽  
Evacuation Time ◽  
Standard Practice ◽  
Time To Completion ◽  
Significant Difference ◽  
Aerial Vehicle

AbstractIntroductionThe proliferation of unmanned aerial vehicle (UAV) technology has the potential to change the way medical incident commanders (ICs) respond to mass-casualty incidents (MCIs) in triaging victims. The aim of this study was to compare UAV technology to standard practice (SP) in triaging casualties at an MCI.MethodsA randomized comparison study was conducted with 40 paramedic students from the Holland College Paramedicine Program (Charlottetown, Prince Edward Island, Canada). Using a simulated motor vehicle collision (MVC) with moulaged casualties, iterations of 20 students were used for both a day and a night trial. Students were randomized to a UAV or a SP group. After a brief narrative, participants either entered the study environment or used UAV technology where total time to triage completion, GREEN casualty evacuation, time on scene, triage order, and accuracy were recorded.ResultsA statistical difference in the time to completion of 3.63 minutes (95% CI, 2.45 min-4.85 min; P=.002) during the day iteration and a difference of 3.49 minutes (95% CI, 2.08 min-6.06 min; P=.002) for the night trial with UAV groups was noted. There was no difference found in time to GREEN casualty evacuation, time on scene, or triage order. One-hundred-percent accuracy was noted between both groups.Conclusion:This study demonstrated the feasibility of using a UAV at an MCI. A non-clinical significant difference was noted in total time to completion between both groups. There was no increase in time on scene by using the UAV while demonstrating the feasibility of remotely triaging GREEN casualties prior to first responder arrival.Jain T, Sibley A, Stryhn H, Hubloue I.Comparison of unmanned aerial vehicle technologyassisted triage versus standard practice in triaging casualties by paramedic students in a mass-casualty incident scenario. Prehosp Disaster Med. 2018;33(4):375–380

scholarly journals P074: Comparison of unmanned aerial vehicle technology versus standard practice in triaging casualties by paramedic students in a mass casualty incident scenario

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S83-S83 ◽  
Author(s):  
T. Jain ◽  
A. Sibley ◽  
H. Stryhn ◽  
I. Hubloue
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Motor Vehicle ◽  
Mass Casualty Incident ◽  
Mass Casualty ◽  
Evacuation Time ◽  
Standard Practice ◽  
Vehicle Collision ◽  
Significant Difference ◽  
Aerial Vehicle ◽  
Percent Accuracy

Introduction: The proliferation of unmanned aerial vehicle (UAV) technology has the potential to change the way medical incident commanders respond to mass casualty incidents (MCI) in triaging victims. The aim of this study was to compare UAV technology to standard practice (SP) in triaging casualties at a MCI Methods: A randomized comparison study was conducted with forty paramedic students from the Holland College Paramedicine Program. Using a simulated motor vehicle collision with moulaged casualties, iterations of twenty students were used for both a day and a night trial. Students were randomized to an UAV or a SP group. After a brief narrative participants either entered the study environment or used UAV technology where total time to triage completion, green casualty evacuation, time on scene, triage order and accuracy was recorded Results: A statistical difference in the time to completing of 3.63 minutes (95% CI: 2.45, 4.85, p=0.002) during the day iteration and a difference of 3.49 minutes (95% CI: 2.08,6.06, p=0.002) for the night trial with UAV groups was noted. There was no difference found in time to green casualty evacuation, time on scene or triage order. One hundred percent accuracy was noted between both groups. Conclusion: This study demonstrated the feasibility of using an UAV at a MCI. A non clinical significant difference was noted in total time to completion between both groups. There was no increase in time on scene by using the UAV while demonstrating the feasibility of remotely triaging green casualties prior to first responder arrival.

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

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S40-S40
Author(s):  
A. K. Sibley ◽  
T. Jain ◽  
B. Nicholson ◽  
M. Butler ◽  
S. David ◽  
...  
Keyword(s):  
Situational Awareness ◽  
Optimal Strategies ◽  
Mass Casualty Incident ◽  
Mass Casualty ◽  
Treatment Area ◽  
Incident Command ◽  
Emergency Responders ◽  
Video Footage ◽  
Scene Management ◽  
Patient Localization

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.

scholarly journals Requirement Analysis for an Aerial Relay in Emergency Response Missions

2020 ◽  
Vol 6 (3) ◽  
pp. 16-19
Author(s):  
Jonas Gruner ◽  
Albrecht Bloße ◽  
Max Rockstroh ◽  
Thomas Neumuth ◽  
Philipp Rostalski
Keyword(s):  
Situational Awareness ◽  
Point Of Care ◽  
Data Communication ◽  
Mass Casualty ◽  
Use Cases ◽  
Publicly Funded ◽  
Mobile Wireless ◽  
Aerial Vehicle ◽  
Flow Of Information ◽  
Safety And Stability

AbstractFirst aid of patients at the scene of an emergency requires an adequate flow of information. The publicly funded research project MOMENTUM aims at seamlessly connecting the point of care to the hospital. An unmanned aerial vehicle serving as a network relay may help in cases of limited or no mobile wireless connection, e.g. due to topographical circumstances. The aerial system may also provide situational awareness in cases of mass casualty incidents. For these two defined use-cases, safety and stability considerations are discussed, and required flight times and payloads are defined. The relay can be connected to the ground via a cable or wireless connection. It is concluded that the use-cases can be realized best when using a multicopter-either combined with a cable for independent flight times and reliable data communication or a wireless solution to mitigate the risk from the increased payload while limiting flight time. For the first option, the payload of the aircraft should be adjusted to ensure the power consumption in hover matches the power limitation of the cable.

Remote Scene Size-up Using an Unmanned Aerial Vehicle in a Simulated Mass Casualty Incident

2018 ◽  
Vol 23 (3) ◽  
pp. 332-339 ◽  
Author(s):  
Aaron K. Sibley ◽  
Trevor N. Jain ◽  
Michael Butler ◽  
Brent Nicholson ◽  
David Sibley ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Mass Casualty Incident ◽  
Mass Casualty ◽  
Aerial Vehicle

scholarly journals Big Data Analytics for Mass Casualty Incident (MCI) Situational Awareness

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Catherine Ordun ◽  
Timothy Davis ◽  
Brante Goode ◽  
Dean Ross ◽  
Mike Hopmeier
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Information Needs ◽  
Situational Awareness ◽  
Big Data Analytics ◽  
Disease Outbreaks ◽  
Mass Casualty Incident ◽  
Mass Casualty ◽  
Department Of Health ◽  
Park Service

An expert panel will share insights from the National Disaster Medical System, Vermont Department of Health, the National Park Service, and Department of Defense, regarding the application of big data analytics on situational awareness of Mass Casualty Incidents (MCIs). Moderated by Booz Allen Hamilton, the panel will share examples from their agencies about the information/data challenges of responding to MCIs, and suggest how analytic methods used to detect disease outbreaks, for example, could be applied. Booz Allen will present 10 situational awareness information-needs criteria identified in a survey of federal experts that could be used to build an analytics tool.

scholarly journals Prehospital Triage by Lay Person First Responders: A Scoping Review and Proposal for a new Prehospital Triage Tool

2021 ◽  
pp. 1-11
Author(s):  
Wesley D Jetten ◽  
Jeroen Seesink ◽  
Markus Klimek
Keyword(s):  
Scoping Review ◽  
Life Support ◽  
First Responders ◽  
Mass Casualty Incident ◽  
Mass Casualty ◽  
Mass Casualty Incidents ◽  
Lay People ◽  
Online Databases ◽  
Healthcare Experience ◽  
Prehospital Triage

Abstract Objective: The primary aim of this study is to review the available tools for prehospital triage in case of mass casualty incidents and secondly, to develop a tool which enables lay person first responders (LPFRs) to perform triage and start basic life support in mass casualty incidents. Methods: In July 2019, online databases were consulted. Studies addressing prehospital triage methods for lay people were analyzed. Secondly, a new prehospital triage tool for LPFRs was developed. Therefore, a search for prehospital triage models available in literature was conducted and triage actions were extracted. Results: The search resulted in 6188 articles, and after screening, a scoping review of 4 articles was conducted. All articles stated that there is great potential to provide accurate prehospital triage by people with no healthcare experience. Based on these findings, and combined with the pre-existing prehospital triage tools, we developed a, not-yet validated, prehospital triage tool for lay people, which may improve disaster awareness and preparedness and might positively contribute to community resilience. Conclusion: The prehospital triage tool for lay person first responders may be useful and may help professional medical first responders to determine faster, which casualties most urgently need help in a mass casualty incident.

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