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

Published online by Cambridge University Press:  13 July 2018

Trevor Jain ,
Aaron Sibley ,
Henrik Stryhn  and
Ives Hubloue
Trevor Jain*
Affiliation:
Division of Paramedicine, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada
Aaron Sibley
Affiliation:
Division of Paramedicine, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada
Henrik Stryhn
Affiliation:
Department of Health Management, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada
Ives Hubloue
Affiliation:
Department of Emergency Medicine, Universitair Ziekenhuis Brussel, Research Group in Emergency and Disaster Medicine, Vrije Universiteit Brussel, Jette, Belgium
*
Correspondence: Trevor Jain, OMM, MSM, CD, MD, MSc University of Prince Edward Island Division of Paramedicine Duffy Science Centre #430 550 University Ave Charlottetown, Prince Edward Island, C1A 4P3 Canada E-mail: Tjain@upei.ca
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Abstract

Introduction

The 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.

Methods

A 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.

Results

A 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

Keywords

disaster medicineEMSMCItechnologyUAV
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 33 , Issue 4 , August 2018 , pp. 375 - 380
Copyright
© World Association for Disaster and Emergency Medicine 2018 

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Footnotes

Conflicts of interest/funding: This work was completed using funding from the Research Arm of the Holland College Paramedicine Program (Charlottetown, Prince Edward Island, Canada). No conflicts of interest are declared.

References

1. Abrahamsen, HB. A remotely piloted aircraft system in major incident management: concept and pilot, feasibility study. BMC Emerg Med. 2015;15(1):12.Google Scholar
2. Lichtman, A, Nair, M. Humanitarian uses of drones and satellite imagery analysis: the promises and perils. AMA J Ethics. 2015;17(10):931.Google Scholar
3. Jain, T, Sibley, A, Stryhn, H, Hubloue, I. Comparison of unmanned aerial vehicle technology versus standard practice in identification of hazards at a mass casualty incident scenario by primary care paramedic students. Disaster Med Public Health Prep. In press.Google Scholar
4. Leduc, TJ. Drones for EMS: 5 ways to use a UAV today. www.EMS1.com/technology/articles/40860048-Drones-for-EMS-5-ways-to-use-a-uav-today/. Accessed February 24, 2017.Google Scholar
5. Mardell, J, Witkowski, M, Spence, R. A comparison of image inspection modes for a visual search and rescue task. Behaviour & Information Technology. 2014;33(9):905-918.Google Scholar
6. www.emsteam.org/drones. Castle Rock Fire and Rescue Department, South Metro Fire Rescue Authority plan to sue UAVs this fall. Accessed February 24, 2017.Google Scholar
7. The Cobber, William Carey University. Medical college develops fully equipped telemedical drone. JEMS. October 16, 2015.Google Scholar
8. Wen, T, Zhang, Z, Wong, KK. Multi-objective algorithm for blood supply via unmanned aerial vehicles to the wounded in an emergency situation. PloS One. 2016;11(5):e0155176.Google Scholar
9. Boccardo, P, Chiabrando, F, Dutto, F, Tonolo, FG, Lingua, A. UAV deployment exercise for mapping purposes: evaluation of emergency response applications. Sensors (Basel). 2015;15(7):15717-15737.Google Scholar
10. Thiels, CA, Aho, JM, Zietlow, SP, Jenkins, DH. Use of unmanned aerial vehicles for medical product transport. Air Med J. 2015;34(2):104-108.Google Scholar
11. Fornace, KM, Drakeley, CJ, William, T, Espino, F, Cox, J. Mapping infectious disease landscapes: unmanned aerial vehicles and epidemiology. Trends Parasitol. 2014;30(11):514-519.Google Scholar
12. Pulver, A, Wei, R, Mann, C. Locating AED enabled medical drones to enhance cardiac arrest response times. Prehosp Emerg Care. 2016;20(3):378-389.Google Scholar
13. Kurvinen, K, Smolander, P, Pöllänen, R, Kuukankorpi, S, Kettunen, M, Lyytinen, J. Design of a radiation surveillance unit for an unmanned aerial vehicle. J Environ Radioact. 2005;81(1):1-10.Google Scholar
14. www.ems1.com. How drones can provide eyes in the sky for EMS. April 15, 2013. Accessed February 24, 2017.Google Scholar
15. Claesson, A, Fredman, D, Svensson, L, et al. Unmanned aerial vehicles (drones) in out-of-hospital-cardiac-arrest. Scand J Trauma Resusc Emerg Med. 2016;24(1):124.Google Scholar
16. Cook, Z, Zhao, L, Lee, J, Yim, W. Unmanned aerial system for first responders. In: Ubiquitous Robots and Ambient Intelligence (URAI). 12th International Conference on October 28, 2015. Piscataway, New Jersey USA: Institute of Electrical and Electronics Engineers (IEEE); 306-310.Google Scholar
17. Wesson, K, Humphreys, T. Hacking drones. Sci Am. 2013;309(5):54-59.Google Scholar
18. Rodriguez, PA, Geckle, WJ, Barton, JD, et al. An emergency response UAV surveillance system. In: AMIA Annual Symposium Proceedings 2006. Bethesda, Maryland USA: American Medical Informatics Association (AMIA); 1078.Google Scholar