Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-25T07:14:22.024Z Has data issue: false hasContentIssue false
  • English
  • Français

Comparison of Outcome Tools Used to Test Mass-Casualty Algorithms in the Pediatric Population

Published online by Cambridge University Press:  06 October 2021

J. Joelle Donofrio ,
Alaa Shaban ,
Amy H. Kaji ,
Genevieve Santillanes ,
Mark X. Cicero ,
Todd P. Chang Open the ORCID record for Todd P. Chang [Opens in a new window] ,
Marianne Gausche-Hill  and
Ilene A. Claudius Open the ORCID record for Ilene A. Claudius [Opens in a new window]
J. Joelle Donofrio
Affiliation:
University of California San Diego Departments of Pediatrics and Emergency Medicine, San Diego, CaliforniaUSA Rady Children’s Hospital of San Diego, San Diego, CaliforniaUSA
Alaa Shaban
Affiliation:
California Community Health Centers, Santa Maria, CaliforniaUSA
Amy H. Kaji
Affiliation:
Harbor-UCLA Medical Center, Torrance, CaliforniaUSA; David Geffen School of Medicine at UCLA, Los Angeles, CaliforniaUSA
Genevieve Santillanes
Affiliation:
Keck School of Medicine of University of Southern California, Los Angeles, CaliforniaUSA
Mark X. Cicero
Affiliation:
Yale University School of Medicine, New Haven, ConnecticutUSA
Todd P. Chang
Affiliation:
Children’s Hospital Los Angeles, Los Angeles, CaliforniaUSA
Marianne Gausche-Hill
Affiliation:
Harbor-UCLA Medical Center, Torrance, CaliforniaUSA; David Geffen School of Medicine at UCLA, Los Angeles, CaliforniaUSA Los Angeles County Emergency Medical Services Agency, Los Angeles, CaliforniaUSA
Ilene A. Claudius*
Affiliation:
Harbor-UCLA Medical Center, Torrance, CaliforniaUSA; David Geffen School of Medicine at UCLA, Los Angeles, CaliforniaUSA
*
Correspondence: Ilene Claudius, MD 1000 W. Carson, Department of Emergency Medicine D9 Torrance, California90509USA E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Introduction:

Mass-casualty incident (MCI) algorithms are used to sort large numbers of patients rapidly into four basic categories based on severity. To date, there is no consensus on the best method to test the accuracy of an MCI algorithm in the pediatric population, nor on the agreement between different tools designed for this purpose.

Study Objective:

This study is to compare agreement between the Criteria Outcomes Tool (COT) to previously published outcomes tools in assessing the triage category applied to a simulated set of pediatric MCI patients.

Methods:

An MCI triage category (black, red, yellow, and green) was applied to patients from a pre-collected retrospective cohort of pediatric patients under 14 years of age brought in as a trauma activation to a Level I trauma center from July 2010 through November 2013 using each of the following outcome measures: COT, modified Baxt score, modified Baxt combined with mortality and/or length-of-stay (LOS), ambulatory status, mortality alone, and Injury Severity Score (ISS). Descriptive statistics were applied to determine agreement between tools.

Results:

A total of 247 patients were included, ranging from 25 days to 13 years of age. The outcome of mortality had 100% agreement with the COT black. The “modified Baxt positive and alive” outcome had the highest agreement with COT red (65%). All yellow outcomes had 47%-53% agreement with COT yellow. “Modified Baxt negative and <24 hours LOS” had the highest agreement with the COT green at 89%.

Conclusions:

Assessment of algorithms for triaging pediatric MCI patients is complicated by the lack of a gold standard outcome tool and variability between existing measures.

Keywords

mass-casualty incidentoutcomestriage
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 36 , Issue 6 , December 2021 , pp. 719 - 723
Check for updates
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the World Association for Disaster and Emergency Medicine

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

Garner, A, Lee, A, Harrison, K, Schultz, CH. Comparative analysis of multiple-casualty incident triage algorithms. Ann Emerg Med. 2001;38(5):541–548.CrossRefGoogle ScholarPubMed
Baxt, WG, Upenieks, V. The lack of full correlation between the Injury Severity Score and the resource needs of injured patients. YMEM. 1990;19(12):1396–1400.Google ScholarPubMed
Challen, K, Walter, D. Major incident triage: comparative validation using data from 7th July bombings. Injury. 2013;44(5):629–633.CrossRefGoogle ScholarPubMed
Wallis, LA, Carley, S. Validation of the pediatric triage tape. Emerg Med J. 2006;23(1):47–50.CrossRefGoogle ScholarPubMed
Wallis, LA. Comparison of pediatric major incident primary triage tools. Emerg Med J. 2006;23(6):475–478.CrossRefGoogle ScholarPubMed
Kahn, CA, Schultz, CH, Miller, KT, Anderson, CL. Does START triage work? An outcomes assessment after a disaster. YMEM. 2009;54(3):424–430.Google Scholar
Price, CL, Brace-McDonnell, SJ, Stallard, N, Bleetman, A, Maconochie, I, Perkins, GD. Performance characteristics of five triage tools for major incidents involving traumatic injuries to children. Injury. 2016;47(5):988–992.CrossRefGoogle ScholarPubMed
Cross, KP, Cicero, MX. Head-to-head comparison of disaster triage methods in pediatric, adult, and geriatric patients. YMEM. 2013;61(6):668–676.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. 2014;19(2):272–278.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):343–353.CrossRefGoogle ScholarPubMed
Supplementary material: File

Donofrio et al. supplementary material

Donofrio et al. supplementary material

Download Donofrio et al. supplementary material(File)
File 16.8 KB