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Prehospital Disaster Triage Does Not Predict Pediatric Outcomes: Comparing the Criteria Outcomes Tool to Three Mass-Casualty Incident Triage Algorithms

Published online by Cambridge University Press:  16 August 2021

Mark X. Cicero
Affiliation:
Yale School of Medicine, New Haven, ConnecticutUSA
Genevieve R. Santillanes
Affiliation:
Keck School of Medicine, University of Southern California, Los Angeles, CaliforniaUSA
Keith P. Cross*
Affiliation:
University at Buffalo Jacobs School of Medicine, Buffalo, New YorkUSA
Amy H. Kaji
Affiliation:
Harbor-UCLA Medical Center, Torrance, CaliforniaUSA
J. Joelle Donofrio
Affiliation:
Rady Children’s Hospital of San Diego and University of California at San Diego, San Diego, CaliforniaUSA
*
Correspondence: Keith P. Cross, MD 285 Middlesex Rd Buffalo, New York14216USA E-mail: kcross@upa.chob.edu

Abstract

Introduction:

It remains unclear which mass-casualty incident (MCI) triage tool best predicts outcomes for child disaster victims.

Study Objectives:

The primary objective of this study was to compare triage outcomes of Simple Triage and Rapid Treatment (START), modified START, and CareFlight in pediatric patients to an outcomes-based gold standard using the Criteria Outcomes Tool (COT). The secondary outcomes were sensitivity, specificity, under-triage, over-triage, and overall accuracy at each level for each MCI triage algorithm.

Methods:

Singleton trauma patients under 16 years of age with complete prehospital, emergency department (ED), and in-patient data were identified in the 2007-2009 National Trauma Data Bank (NTDB). The COT outcomes and procedures were translated into ICD-9 procedure codes with added timing criteria. Gold standard triage levels were assigned using the COT based on outcomes, including mortality, injury type, admission to the hospital, and surgical procedures. Comparison triage levels were determined based on algorithmic depictions of the three MCI triage tools.

Results:

A total of 31,093 patients with complete data were identified from the NTDB. The COT was applied to these patients, and the breakdown of gold standard triage levels, based on their actual clinical outcomes, was: 17,333 (55.7%) GREEN; 11,587 (37.3%) YELLOW; 1,572 (5.1%) RED; and 601 (1.9%) BLACK. CareFlight had the best sensitivity for predicting COT outcomes for BLACK (83% [95% confidence interval, 80%-86%]) and GREEN patients (79% [95% CI, 79%-80%]) and the best specificity for RED patients (89% [95% CI, 89%-90%]).

Conclusion:

Among three prehospital MCI triage tools, CareFlight had the best performance for correlating with outcomes in the COT. Overall, none of three tools had good test characteristics for predicting pediatric patient needs for surgical procedures or hospital admission.

Type
Original Research
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the World Association for Disaster and Emergency Medicine

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References

SALT mass casualty triage: concept endorsed by the American College of Emergency Physicians, American College of Surgeons Committee on Trauma, American Trauma Society, National Association of EMS Physicians, National Disaster Life Support Education Consortium, and State and Territorial Injury Prevention Directors Association. Disaster Med Public Health Prep. 2008;2(4):245-246.CrossRefGoogle Scholar
Romig, L. Pediatric triage. A system to JumpSTART your triage of young patients at MCIs. JEMS. 2002;27(7):5258, 60-53.Google ScholarPubMed
Sacco, W, Navin, D, Waddell, Rn, Fiedler, K, Long, W, Buckman, RJ. A new resource-constrained triage method applied to victims of penetrating injury. J Trauma. 2007;63(2):316325.Google ScholarPubMed
Cone, DC, Serra, J, Kurland, L. Comparison of the SALT and Smart triage systems using a virtual reality simulator with paramedic students. Eur J Emerg Med. 2011;18(6):314321.CrossRefGoogle ScholarPubMed
Arshad, FH, Williams, A, Asaeda, G, et al. A modified simple triage and rapid treatment algorithm from the New York City (USA) Fire Department. Prehosp Disaster Med. 2015;30(2):199204.CrossRefGoogle ScholarPubMed
Jenkins, J, McCarthy, M, Sauer, L, et al. Mass-casualty triage: time for an evidence-based approach. Prehosp Disaster Med. 2008;23(1):38.CrossRefGoogle ScholarPubMed
Lerner, EB, Cone, DC, Weinstein, ES, et al. Mass casualty triage: an evaluation of the science and refinement of a national guideline. Disaster Med Public Health Prep. 2011;5(2):129137.CrossRefGoogle ScholarPubMed
Cross, KP, Cicero, MX. Independent application of the Sacco Disaster Triage Method to pediatric trauma patients. Prehosp Disaster Med. 2012;27(4):306311.CrossRefGoogle ScholarPubMed
Cross, KP, Cicero, MX. Head-to-head comparison of disaster triage methods in pediatric, adult, and geriatric patients. Ann Emerg Med. 2013;61(6):668-676.e667.CrossRefGoogle ScholarPubMed
Baxt, WG, Upenieks, V. The lack of full correlation between the Injury Severity Score and the resource needs of injured patients. Ann Emerg Med. 1990;19(12):13961400.CrossRefGoogle ScholarPubMed
Garner, A, Lee, A, Harrison, K, Schultz, CH. Comparative analysis of multiple-casualty incident triage algorithms. Ann Emerg Med. 2001;38(5):541548.CrossRefGoogle ScholarPubMed
Wallis, LA, Carley, S. Comparison of pediatric major incident primary triage tools. Emerg Med J. 2006;23(6):475478.CrossRefGoogle ScholarPubMed
Wallis, LA, Carley, S. Validation of the pediatric triage tape. Emerg Med J. 2006;23(1):4750.CrossRefGoogle ScholarPubMed
Donofrio, JJ, Kaji, AH, Claudius, IA, et al. Development of a pediatric mass casualty triage algorithm validation tool. Prehosp Emerg Care. 2016;20(3):343353.CrossRefGoogle ScholarPubMed
Lerner, EB, McKee, CH, Cady, CE, et al. A consensus-based gold standard for the evaluation of mass casualty triage systems. Prehosp Emerg Care. 2015;19(2):267271.CrossRefGoogle ScholarPubMed
Cicero, MX, Overly, F, Brown, L, et al. Comparing the accuracy of three pediatric disaster triage strategies: a simulation-based investigation. Disaster Med Public Health Prep. 2016;10(2):253260.CrossRefGoogle ScholarPubMed
Fantus, RJ, Fildes, J. NTDB data points. How national is the trauma data bank? Bull Am Coll Surg. 2003;88(5):37.Google ScholarPubMed
Cross, KP, Petry, MJ, Cicero, MX. A better START for low-acuity victims: data-driven refinement of mass casualty triage. Prehosp Emerg Care. 2015;19(2):272278.CrossRefGoogle ScholarPubMed
Challen, K, Walter, D. Major incident triage: comparative validation using data from 7th July bombings. Injury. 2013;44(5):629633.CrossRefGoogle ScholarPubMed
Kahn, C, Schultz, C, Miller, K, Anderson, C. Does START triage work? An outcomes assessment after a disaster. Ann Emerg Med. 2009;54(3):424430, 430.e421.CrossRefGoogle Scholar
American Academy of Pediatrics; American College of Emergency Physicians; American College of Surgeons - Committee on Trauma; et al. Model uniform core criteria for mass casualty triage. Disaster Med Public Health Prep. 2011;5(2):125128.CrossRefGoogle Scholar
Remick, K, Kaji, AH, Olson, L, et al. Pediatric readiness and facility verification. Ann Emerg Med. 2016;67(3):320328.e321.CrossRefGoogle ScholarPubMed
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Prehospital Disaster Triage Does Not Predict Pediatric Outcomes: Comparing the Criteria Outcomes Tool to Three Mass-Casualty Incident Triage Algorithms
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