Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-28T02:20:06.516Z Has data issue: false hasContentIssue false
  • English
  • Français

Disaster Metrics: Quantitative Estimation of the Number of Ambulances Required in Trauma-Related Multiple Casualty Events

Published online by Cambridge University Press:  21 August 2012

Jamil D. Bayram ,
Shawki Zuabi  and
Mazen J. El Sayed
Jamil D. Bayram*
Affiliation:
Department of Emergency Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland USA
Shawki Zuabi
Affiliation:
Orange Coast Memorial Medical Center, Department of Emergency Medicine, Fountain Valley, California USA
Mazen J. El Sayed
Affiliation:
Department of Emergency Medicine, American University of Beirut Medical Center, Beirut, Lebanon
*
Correspondence: Jamil D. Bayram, MD, MPH, EMDM, MEd Johns Hopkins School of Medicine 5801 Smith Avenue Davis Building, Suite 3220 Baltimore, MD 21209 USA E-mail: jbayram1@jhmi.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Introduction

Estimating the number of ambulances needed in trauma-related Multiple Casualty Events (MCEs) is a challenging task.

Hypothesis/Problem

Emergency medical services (EMS) regions in the United States have varying “best practices” for the required number of ambulances in MCE, none of which is based on metric criteria. The objective of this study was to estimate the number of ambulances required to respond to the scene of trauma-related MCE in order to initiate treatment and complete the transport of critical (T1) and moderate (T2) patients. The proposed model takes into consideration the different transport times and capacities of receiving hospitals, the time interval from injury occurrence, the number of patients per ambulance, and the pre-designated time frame allowed from injury until the transfer care of T1 and T2 patients.

Methods

The main theoretical framework for this model was based on prehospital time intervals described in the literature and used by EMS systems to evaluate operational and patient care issues. The North Atlantic Treaty Organization (NATO) triage categories (T1-T4) were used for simplicity.

Results

The minimum number of ambulances required to respond to the scene of an MCE was modeled as being primarily dependent on the number of critical patients (T1) present at the scene any particular time. A robust quantitative model was also proposed to dynamically estimate the number of ambulances needed at any time during an MCE to treat, transport and transfer the care of T1 and T2 patients.

Conclusion

A new quantitative model for estimation of the number of ambulances needed during the prehospital response in trauma-related multiple casualty events has been proposed. Prospective studies of this model are needed to examine its validity and applicability.

BayramJD, ZuabiS, El SayedMJ. Disaster Metrics: Quantitative Estimation of the Number of Ambulances Required in Trauma-Related Multiple Casualty Events. Prehosp Disaster Med.2012;27(5):1-7.

Keywords

ambulancedisasterdisaster metricsdisaster responseemergency medical servicesmultiple casualty event
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 27 , Issue 5 , October 2012 , pp. 445 - 451
Copyright
Copyright © World Association for Disaster and Emergency Medicine 2012

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. Committee on the Future of Emergency Care in the United States Health System Board on Health Care Services. Emergency Medical Services at the Crossroads. Washington, DC: National Academies Press; 2006.Google Scholar
2. Hogan, DE, Waeckerle, JF, Dire, DJ, Lillibridge, SR. Emergency department impact of the Oklahoma City terrorist bombing. Ann Emerg Med. 1999;34(2):160-167.CrossRefGoogle ScholarPubMed
3. Auf der Heide, E. The importance of evidenced based disaster planning. Ann Emerg Med. 2006;47(1):34-49.CrossRefGoogle Scholar
4. Emergency Medical Services (EMS) Surge Planning Template and Toolbox for Mass Casualty Incidents (MCI) in Virginia. http://www.vdh.state.va.us/OEMS/Files_page/EmergencyOperations/EMSSurgeTemplate.pdf. Accessed December 25, 2011.Google Scholar
5. Multiple Casualty Incident (MCI) Response Plan - Monterey County, California. http://www.mcftoa.org/wp-content/uploads/2011/05/Multiple-Casualty-Incident-MCI-Response-Plan1.pdf. Accessed December 24, 2011.Google Scholar
6. Multiple Casualty Incident Transportation Management - Los Angeles County, California. http://ems.lacounty.gov/Policies/Ref1100/1126.pdf. Accessed December 25, 2011.Google Scholar
7. Medical Incident Response Plan - Davis County, Utah. http://www.co.davis.ut.us/sheriff/divisions/emergency_services/emergency_management/documents/Major%20Incident%20Response%20Plan/MCI%20Plan.pdf. Accessed December 24, 2011.Google Scholar
8. de Boer, J. An attempt at more accurate estimation of the number of ambulances needed at disasters in The Netherlands. Prehosp Disaster Med. 1996;11(2):125-129.CrossRefGoogle Scholar
9. de Boer, J. Order in chaos: modeling medical management in disasters. Eur J Emerg Med. 1999;6(2):141-148.CrossRefGoogle ScholarPubMed
10. Spaite, DW, Valenzuela, TD, Meislin, HW, et al. Prospective validation of a new model for evaluating emergency medical services systems by in-field observation of specific time intervals in prehospital care. Ann Emerg Med. 1993;22(4):638-645.CrossRefGoogle ScholarPubMed
11. Carr, BG, Caplan, JM, Pryor, JP, et al. A meta-analysis prehospital care times for trauma. Prehosp Emerg Care. 2006;10:198-206.CrossRefGoogle ScholarPubMed
12. Bayram JD, Zuabi Shawki. Disaster metrics: a proposed quantitative model for benchmarking prehospital medical response in trauma-related multiple casualty events. Prehosp Disaster Med. 2012;27(2):123-129.CrossRefGoogle Scholar
13. Baxt, WG. Trauma - The First Hour. East Norwalk, Connecticut: Appleton-Century-Crofts; 1985.Google Scholar
14. Cowley, RA. The resuscitation and stabilization of major multiple trauma patients in a trauma center environment. Clin Med. 1976;83(14):16-22.Google Scholar
15. Newgard, CD, Schmicker, RH, Hedges, JR, et al. Emergency medical services intervals and survival in trauma: assessment of the “golden hour” in a North American prospective cohort. Ann Emerg Med. 2010;55(3):235-246. e4.CrossRefGoogle Scholar
16. Lerner, EB, Billittier, AJ, Dorn, JM, et al. Is total out-of-hospital time a significant predictor of trauma patient mortality? Acad Emerg Med. 2003;10(9):949-954.Google Scholar
17. Báez, AA, Lane, PL, Sorondo, B, Giráldez, EM. Predictive effect of out-of-hospital time in outcomes of severely injured young adult and elderly patients. Prehosp Disaster Med. 2006;21(6):427-430.CrossRefGoogle ScholarPubMed
18. Osterwalder, JJ. Can the “golden hour of shock” safely be extended in blunt polytrauma patients? Prehosp Disaster Med. 2002;17(2):75-80.CrossRefGoogle Scholar
19. Pons, PT, Markovchick, VJ. Eight minutes or less: does the ambulance response time guideline impact trauma patient outcome? J Emerg Med. 2002;23(1):43-48.CrossRefGoogle ScholarPubMed
20. Lerner, EB, Moscati, RM. The golden hour: scientific fact or medical “urban legend”? Acad Emerg Med. 2001;8(7):758-760.CrossRefGoogle ScholarPubMed
21. Petri, RW, Dyer, A, Lumpkin, J. The effect of prehospital transport time on the mortality from traumatic injury. Prehosp Disaster Med. 1995;10(1):24-29.CrossRefGoogle ScholarPubMed
22. Pepe, PE, Wyatt, CH, Bickell, WH, et al. The relationship between total prehospital time and outcome in hypotensive victims of penetrating injuries. Ann Emerg Med. 1987;16(3):293-297.CrossRefGoogle ScholarPubMed
23. McNabney, WK. Vietnam in context. Ann Emerg Med. 1981;10(12):659-661.CrossRefGoogle ScholarPubMed
24. West, JG, Trunkey, DD, Lim, RC. Systems of trauma care. Arch Surg. 1979;114(4):455-460.CrossRefGoogle ScholarPubMed
25. Stiell, IG, Nesbitt, LP, Pickett, W, et al. The OPALS major trauma outcome study: impact of advanced life-support on survival and morbidity. CMAJ. 2008;178(9):1141-1152.CrossRefGoogle ScholarPubMed
26. Di Bartolomeo, S, Valent, F, Rosolen, V, et al. Are prehospital time and emergency department disposition time useful process indicators for trauma care in Italy? Injury. 2007;38(3):305-311.CrossRefGoogle ScholarPubMed
27. Bayram, JD, Zuabi, S, Subbarao, I. Disaster metrics: quantitative benchmarking of trauma-related hospital surge capacity in multiple casualty events. Disaster Med Public Health Prep. 2011;5(2):117-124.CrossRefGoogle ScholarPubMed
28. Heightman, AJ. 20 tips for MCI management. JEMS. 2000;25:30-40.Google Scholar
29. Cone, DC, Serra, J, Burns, K, MacMillan, DS, Kurland, L, Van Gelder, C. Pilot test of the SALT Mass Casualty Triage System. Prehosp Emerg Care. 2009;13(4):536-540.CrossRefGoogle ScholarPubMed
30. Iserson, KV, Moskop, JC. Triage in medicine, part I: concept, history, and types. Ann Emerg Med. 2007;49(3):275-281.CrossRefGoogle Scholar
31. North Atlantic Treaty Organization. Emergency War Surgery. Washington, DC: US Government Printing Office; 1958:168.Google Scholar
32. Kennedy, K, Aghababian, RV, Gans, L, Lewis, CP. Triage: techniques and applications in decision making. Ann Emerg Med. 1996;28(2):136-144.CrossRefGoogle Scholar
33. Kahn, CA, Schultz, CH, Miller, KT, Anderson, CL. Does START triage work? An outcomes assessment after a disaster. Ann Emerg Med. 2009;54(3):424-430.CrossRefGoogle Scholar
34. Lerner, EB, Schwartz, RB, Coule, PL, et al. Mass casualty triage: an evaluation of the data and development of a proposed national guideline. Disaster Med Public Health Prep. 2008;2(Suppl 1):S25-S34.CrossRefGoogle ScholarPubMed
35. Lerner, EB, Schwartz, RB, Coule, PL, Pirrallo, RG. Use of SALT triage in a simulated mass-casualty incident. Prehosp Emerg Care. 2010;14(1):21-25.CrossRefGoogle Scholar
36. Lerner, EB, Cone, DC, Weinstein, ES, Schwartz, RB, Coule, PL, et al. Mass casualty triage: an evaluation of the science and refinement of a national guideline. Disaster Med Public Health Prep. 2011;5(2):129-137.CrossRefGoogle ScholarPubMed
Supplementary material: Image

Bayram supplementary material

Bayram supplementary material

Download Bayram supplementary material(Image)
Image 382.4 KB