Hostname: page-component-8448b6f56d-cfpbc Total loading time: 0 Render date: 2024-04-16T04:03:08.967Z Has data issue: false hasContentIssue false
  • English
  • Français

Disaster Metrics: A Proposed Quantitative Model for Benchmarking Prehospital Medical Response in Trauma-Related Multiple Casualty Events

Published online by Cambridge University Press:  17 May 2012

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

Abstract

Introduction

Quantitative benchmarking of trauma-related prehospital response for Multiple Casualty Events (MCE) is complicated by major difficulties due to the simultaneous occurrences of multiple prehospital activities.

Hypothesis/Problem

Attempts to quantify the various components of prehospital medical response in MCE have fallen short of a comprehensive model. The objective of this study was to model the principal parameters necessary to quantitatively benchmark the prehospital medical response in trauma-related MCE.

Methods

A two-step approach was adopted for the methodology of this study: an extensive literature search was performed, followed by prehospital system quantitative modeling. Studies on prehospital medical response to trauma injuries were used as the framework for the proposed model. The North Atlantic Treaty Organization (NATO) triage categories (T1-T4) were used for the study.

Results

Two parameters, the Injury to Patient Contact Interval (IPCI) and Injury to Hospital Interval (IHI), were identified and proposed as the principal determinants of the medical prehospital response in trauma-related MCE. IHI is the time interval from the occurrence of injury to the completion of transfer of care of critical (T1) and moderate (T2) patients. The IHI for each casualty is compared to the Maximum Time Allowed described in the literature (golden hour for T1 and Friedrich's time for T2). In addition, the medical rescue factor (R) was identified as the overall indicator for the prehospital medical performance for T1 and T2, and a numerical value of one (R = 1) was proposed to be the quantitative benchmark.

Conclusion

A new quantitative model for benchmarking prehospital response to MCE in trauma-related MCE is proposed. Prospective studies of this model are needed to validate its applicability.

Bayram J, Zuabi S. Disaster metrics: a proposed quantitative model for benchmarking prehospital medical response in trauma-related multiple casualty events. Prehosp Disaster Med. 2012;27(2):-7.

Keywords

benchmarkdisaster metricsdisaster responseemergency medical servicesmultiple casualtyprehospital response
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 27 , Issue 2 , April 2012 , pp. 123 - 129
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. Blackwell, TH, Kaufman, JS. Response time effectiveness: comparison of response time and survival in an urban EMS system. Acad Emerg Med. 2002;9:288-295.CrossRefGoogle Scholar
2. Newgard, CD, Sears, GK, Rea, TD, et al. . The Resuscitation Outcomes Consortium Epistry-Trauma: design, development, and implementation of a North American epidemiologic out-of-hospital trauma registry. Resuscitation. 2008;78:170-178.CrossRefGoogle Scholar
3. Pons, PT, Haukoos, JS, Bludworth, W, et al. . Paramedic response time: does is affect patient survival? Acad Emerg Med. 2005;12:594-600.CrossRefGoogle ScholarPubMed
4. Grossman, DC, Kim, A, MacDonald, SC, et al. . Urban-rural differences in prehospital care of major trauma. J Trauma. 1997;42:723-729.CrossRefGoogle ScholarPubMed
5. Feero, S, Hedges, JR, Simmons, E, et al. . Does out-of-hospital EMS time affect trauma survival? Am J Emerg Med. 1995;13(2):133-135.CrossRefGoogle ScholarPubMed
6. Esposito, TJ, Maier, RV, Rivara, FP, et al. . The impact of variation in trauma care times: urban versus rural. Prehosp Disaster Med. 1995;10(3):161-166.CrossRefGoogle ScholarPubMed
7. Mullins, RJ, Veum-Stone, J, Helfand, M, et al. . Outcome of hospitalized injured patients after institution of a trauma system in an urban area. JAMA. 1994;271:1919-1924.CrossRefGoogle Scholar
8. Samplais, JS, Lavoie, A, Williams, JI, et al. . Impact of on-site care, prehospital time, and level of in-hospital care on survival in severely injured patients. J Trauma. 1993;34:252-261.CrossRefGoogle Scholar
9. Spaite, DW, Tse, DJ, Valenzuela, TD, et al. . The impact of injury severity and prehospital procedures on scene time in victims of major trauma. Ann Emerg Med. 1991;20:1299-1305.CrossRefGoogle ScholarPubMed
10. Clevenger, FW, Yarbrough, DR, Reines, HD. Resuscitative thoracotomy: the effect of field time on outcome. J Trauma. 1988;28(4):441-445.CrossRefGoogle ScholarPubMed
11. Ivatury, RR, Nallathambi, MN, Roberge, RJ, et al. . Penetrating thoracic injuries: in-field stabilization versus prompt transport. J Trauma. 1987;27:1066-1072.CrossRefGoogle Scholar
12. Gervin, AS, Fischer, RP. The importance of prompt transport in salvage of patients with penetrating heart wounds. J Trauma. 1982;22:443-446.CrossRefGoogle ScholarPubMed
13. 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
14. Farmer, JC, Carlton, PK Jr. Providing critical care during a disaster: the interface between disaster response agencies and hospitals. Crit Care Med. 2006;34(3 Suppl):S56-59.CrossRefGoogle ScholarPubMed
15. Smiley, DR, Loboda, A, Starling, C, et al. . Transformation from planning to operations: emergency medical services in disaster response. Ann Disaster Med. 2004;3:11-12.Google Scholar
16. Pons, PT, Cantrill, SV. Mass casualty management: a coordinated response. Crit Decisions Emerg Med. 2003;17:7-11.Google Scholar
17. Doyle, CJ. Mass casualty incident: integration with prehospital care. Emerg Med Clin North Am. 1990;8(1):163-175.CrossRefGoogle ScholarPubMed
18. Quarantelli, EL. Delivery of Emergency Medical Care in Disasters: Assumptions and Realities. New York, NY: Irvington Publishers Inc; 1983.Google Scholar
19. 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
20. 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;55:235-246, e4.CrossRefGoogle Scholar
21. 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;10:949-954.Google Scholar
22. 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
23. 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
24. Pons, PT, Markovchick, VJ. Eight minutes or less: does the ambulance response time guideline impact trauma patient outcome? J Emerg Med. 2002;23:43-48.CrossRefGoogle ScholarPubMed
25. Lerner, EB, Moscati, RM. The golden hour: scientific fact or medical “urban legend”? Acad Emerg Med. 2001;8:758-760.CrossRefGoogle ScholarPubMed
26. 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
27. 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
28. Baxt, WG. Trauma—The First Hour. East Norwalk, Connecticut, USA: Appleton-Century-Crofts; 1985.Google Scholar
29. Cowley, RA. The resuscitation and stabilization of major multiple trauma patients in a trauma center environment. Clin Med. 1976;83:16-22.Google Scholar
30. de Boer, J. Order in chaos: modeling medical management in disasters. Eur J Emerg Med. 1999, Jun;6(2):141-148.CrossRefGoogle ScholarPubMed
31. Trunkey, DD. Trauma. Sci Am. 1983;249:28-35.CrossRefGoogle ScholarPubMed
32. de Boer, J, van Remmen, J. Handbook of Disaster Medicine. Utrecht: Van der Wees; 2000.Google Scholar
33. de Boer, J, Brismar, B, Eldar, R, et al. . The medical severity index of disasters. J Emerg Med. 1989;7:269-273.CrossRefGoogle ScholarPubMed
34. Feliciano, DV, Anderson, GV, Rozycki, GS, et al. . Management of casualties from the bombing at the Centennial Olympics. Am J Surg. 1998;176(6):538-543.CrossRefGoogle ScholarPubMed
35. Bayram, JD, Zuabi, S, Subbarao, I. Disaster metrics: quantitative benchmarking of hospital surge capacity in trauma-related multiple casualty events. Disaster Med Public Health Prep. 2011;5(2):117-124.CrossRefGoogle ScholarPubMed
36. Hirshberg, A, Scott, BG, Granchi, T, Wall, MJ Jr, Mattox, KL, Stein, M. How does casualty load affect trauma care in urban bombing incidents? A quantitative analysis. J Trauma. 2005;58(4):686-693; discussion 694-695.CrossRefGoogle ScholarPubMed