Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-10T10:45:08.029Z Has data issue: false hasContentIssue false
  • English
  • Français

Comparison of Computerized Patients versus Live Moulaged Actors for a Mass-casualty Drill

Published online by Cambridge University Press:  12 August 2015

Ilene Claudius ,
Amy Kaji ,
Genevieve Santillanes ,
Mark Cicero ,
J. Joelle Donofrio ,
Marianne Gausche-Hill ,
Saranya Srinivasan  and
Todd P. Chang
Ilene Claudius*
Affiliation:
Department of Emergency Medicine, University of Southern California, Keck School of Medicine, Los Angeles, California USA
Amy Kaji
Affiliation:
Department of Emergency Medicine, Harbor-University of California-Los Angeles Medical Center, Torrance, California USA
Genevieve Santillanes
Affiliation:
Department of Emergency Medicine, University of Southern California, Keck School of Medicine, Los Angeles, California USA
Mark Cicero
Affiliation:
Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut USA
J. Joelle Donofrio
Affiliation:
Department of Emergency Medicine, Harbor-University of California-Los Angeles Medical Center, Torrance, California USA
Marianne Gausche-Hill
Affiliation:
Department of Emergency Medicine, Harbor-University of California-Los Angeles Medical Center, Torrance, California USA
Saranya Srinivasan
Affiliation:
Department of Emergency Medicine, Children’s Hospital Los Angeles, Los Angeles, California USA
Todd P. Chang
Affiliation:
Department of Emergency Medicine, Children’s Hospital Los Angeles, Los Angeles, California USA
*
Correspondence: Ilene Claudius, MD University of Southern California Keck School of Medicine Department of Emergency Medicine 1200 North State Street, 1011 Los Angeles, California 90033 USA E-mail: iaclaudius@gmail.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Introduction

Multiple modalities for simulating mass-casualty scenarios exist; however, the ideal modality for education and drilling of mass-casualty incident (MCI) triage is not established.

Hypothesis/Problem

Medical student triage accuracy and time to triage for computer-based simulated victims and live moulaged actors using the pediatric version of the Simple Triage and Rapid Treatment (JumpSTART) mass-casualty triage tool were compared, anticipating that student performance and experience would be equivalent.

Methods

The victim scenarios were created from actual trauma records from pediatric high-mechanism trauma presenting to a participating Level 1 trauma center. The student-reported fidelity of the two modalities was also measured. Comparisons were done using nonparametric statistics and regression analysis using generalized estimating equations.

Results

Thirty-three students triaged four live patients and seven computerized patients representing a spectrum of minor, immediate, delayed, and expectant victims. Of the live simulated patients, 92.4% were given accurate triage designations versus 81.8% for the computerized scenarios (P=.005). The median time to triage of live actors was 57 seconds (IQR=45-66) versus 80 seconds (IQR=58-106) for the computerized patients (P<.0001). The moulaged actors were felt to offer a more realistic encounter by 88% of the participants, with a higher associated stress level.

Conclusion

While potentially easier and more convenient to accomplish, computerized scenarios offered less fidelity than live moulaged actors for the purposes of MCI drilling. Medical students triaged live actors more accurately and more quickly than victims shown in a computerized simulation.

ClaudiusI , KajiA , SantillanesG , CiceroM , DonofrioJJ , Gausche-HillM , SrinivasanS , ChangTP .Comparison of Computerized Patients versus Live Moulaged Actors for a Mass-casualty Drill. Prehosp Disaster Med. 2015; 30(5): 438–442.

Keywords

emergency departmentmass-casualty incidenttriage
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 30 , Issue 5 , October 2015 , pp. 438 - 442
Copyright
© World Association for Disaster and Emergency Medicine 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Gillet, B, Peckler, B, Sinert, R, et al. Simulation in a disaster drill: comparison of high-fidelity simulators versus trained actors. Acad Emerg Med. 2008;15(11):1144-1151.CrossRefGoogle Scholar
2. Schultz, CM, Skrzypczak, M, Raith, S, et al. High-fidelity human patient simulators compared with human actors in an unannounced mass-casualty exercise. Prehosp Disaster Med. 2014;29(2):176-182.CrossRefGoogle Scholar
3. Wallace, D, Gillet, B, Wright, B, et al. Randomized controlled trial of high fidelity patient simulators compared to actor patients in a pandemic influenza drill scenario. Resuscitation. 2010;81(7):872-876.CrossRefGoogle Scholar
4. Andreatta, PB, Maslowski, E, Petty, S. Virtual reality triage training provides a viable solution for disaster-preparedness. Acad Emerg Med. 2010;17(8):870-876.CrossRefGoogle ScholarPubMed
5. Ingrassia, PL, Ragazzoni, L, Carenzo, L, et al. Virtual reality and live simulation: a comparison between two simulation tools for assessing mass-casualty triage skills. Eur J Emerg Med. 2015;22(2):121-127.CrossRefGoogle Scholar
6. Wilkerson, W, Avstreih, D, Gruppen, L, et al. Using immersive simulation for training first responders for mass-casualty incidents. Acad Emerg Med. 2008;15(11):1152-1159.CrossRefGoogle ScholarPubMed
7. Vincent, DS, Sherstyuk, A, Byrgess, L, et al. Teaching mass-casualty triage skills sing immersive three-dimensional virtual reality. Acad Emerg Med. 2008;15(11):1160-1165.CrossRefGoogle Scholar
8. Leaming, JM, Adoff, S, Terndrup, TE. Computerized simulation as a tool for assessing decision making in pandemic influenza response training. West J Emerg Med. 2013;14(3):236-242.CrossRefGoogle Scholar
9. Scheulen, JJ, Thanner, MH, Hsu, EB, et al. Electronic mass-casualty assessment and planning scenarios: development and application of computer modeling to selected national planning scenarios for high-consequence events. Ann Emerg Med. 2009;53(2):226-232.CrossRefGoogle ScholarPubMed
10. Youngblood, P, Harter, P, Srivasta, S, et al. Design, development, and evaluation of an inline virtual emergency department for training trauma teams. Simul Healthcare. 2008;3(3):146-153.CrossRefGoogle Scholar
11. Heinrichs, WL, Youngblood, P, Harter, P, et al. Training health care personnel for mass-casualty incidents in a virtual emergency department: VED II. Prehosp Disaster Med. 2010;25(5):424-432.CrossRefGoogle Scholar
12. Roy, ML, Sticha, D, Kraus, PL, et al. Simulation and virtual reality in medical education and therapy: a protocol. Cyberpsychol Behav. 2006;9(2):245-247.CrossRefGoogle ScholarPubMed
13. Yu, X, Ganz, A. MiRTE: mixed reality triage and evacuation game for mass-casualty information systems design, testing, and training. Conf Proc IEEE Eng Med Biol Soc. 2011: 8199-8202.Google ScholarPubMed
14. Romig, LE. Pediatric triage. A system to JumpSTART your triage of young patients at MCIs. JEMS. 2002;27(7):52-58; 60-63.Google ScholarPubMed
15. Jones, N, White, ML, Tofil, N, et al. Randomized trial comparing two mass-casualty triage systems (JumpSTART versus SALT) in a pediatric simulated mass-casualty event. Prehosp Emerg Care. 2014;18(3):417-423.CrossRefGoogle Scholar
16. Cicero, MX, Auerbach, MA, Zigmont, J, et al. Simulation training with structured debriefing improves residents’ pediatric disaster triage performance. Prehosp Disaster Med. 2012;27(3):239-244.CrossRefGoogle ScholarPubMed
17. Sanddal, TL, Loyacono, T, Sanddal, ND. Effect of JumpSTART training on immediate and short-term pediatric triage performance. PEC. 2004;20(11):749-753.Google ScholarPubMed
18. Wallis, LA, Carley, S. Comparison of pediatric major incident primary triage tools. EMJ. 2006;23(6):475-478.CrossRefGoogle ScholarPubMed
19. Norman, G, Dore, K, Grierson, L. The minimal relationship between simulation fidelity and transfer of learning. Med Educ. 2012;46(7):636-647.CrossRefGoogle ScholarPubMed
20. Curtis, MT, Diaz-Granados, D, Feldman, M. Judicious use of simulation technology in continuing medical education. J Contin Educ Health Prof. 2012;32(4):255-260.CrossRefGoogle ScholarPubMed
21. Dieckmann, P, Gaba, D, Rall, M. Deepening the theoretical foundations of patient simulation as social practice. Simul Healthc. 2007;2(3):183-193.CrossRefGoogle ScholarPubMed
22. Rudolph, J, Simon, R, Raemer, DB. Which reality matters? Questions on the path to high engagement in health care simulation. Simul Healthc. 2007;2(3):161-163.CrossRefGoogle Scholar