Medical Management of Disasters and Mass Casualties From Terrorist Bombings: How Can We Cope?

Frykberg, Eric R.

doi:10.1097/00005373-200208000-00001

Cited by 440 publications

(321 citation statements)

References 44 publications

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“…The tool must be sensitive enough to identify patients at greatest need, but at the same time must ensure the best use of available resources by delaying treatment for patients who do not require immediate attention. 17 This study has used a large dataset to evaluate the performance of five paediatric triage tools against two separate outcomes, survival (dead or alive) and injury severity (ISS ≤ 15 or ISS > 15), and has revealed clear differences in performance accuracy.…”

Section: Discussionmentioning

confidence: 99%

Performance characteristics of five triage tools for major incidents involving traumatic injuries to children

Price

Brace-McDonnell

Stallard

et al. 2016

Injury

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Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-forprofit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. Results: Of the 31,292 cases, 1,029 died (3.3%), 6,842 (21.9%) had major trauma (defined by an injury severity score > 15) and 14,711 (47%) were aged eight years or younger. There was variation in the performance accuracy of the tools to predict major trauma or death (sensitivities ranging between 36.4% and 96.2%; specificities 66.0% to 89.8%). Performance 3 characteristics varied with the age of the child. CareFlight had the best overall performance at predicting death, with the following sensitivity and specificity (95% CI) respectively: 95.3% (93.8 to 96.8) and 80.4% (80.0 to 80.9). JumpSTART was superior for the triaging of children under 8 years; sensitivity and specificity (95% CI) respectively: 86.3% (83.1 to 89.5) and 84.8% (84.2 to 85.5). The triage tools were generally better at identifying patients who would die than those with non-fatal severe injury. Conclusion:This statistical evaluation has demonstrated variability in the accuracy of triage tools at predicting outcomes for children who sustain traumatic injuries. No single tool performed consistently well across all evaluated scenarios.

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Section: Discussionmentioning

confidence: 99%

Performance characteristics of five triage tools for major incidents involving traumatic injuries to children

Price

Brace-McDonnell

Stallard

et al. 2016

Injury

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“…The impact of over-triage on mortality is less clear but may impact overall survival. [5][6][7] The magnitude of this mistriage threat remains unknown to the large number of communities in the U.S. that utilize START for disaster triage. In addition, no data exist demonstrating that START triage influences decisions regarding which patients should be transported to hospitals first.…”

Section: Importancementioning

confidence: 99%

Does START Triage Work? An Outcomes Assessment After a Disaster

Kahn

Schultz

Miller

et al. 2009

Annals of Emergency Medicine

164

134

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ObjectiveThe mass casualty triage system known as START (Simple Triage and Rapid Treatment) has been widely utilized in the United States since the 1980s. However, no outcomes assessment has been conducted after a disaster to determine whether assigned triage levels match patients' actual clinical status. Researchers hypothesized that START achieves at least 90% sensitivity and specificity for each triage level, and ensures that the most critical patients are transported first to area hospitals. MethodsThe performance of START was evaluated at a train crash disaster in 2003. Patient field triage categories and scene times were obtained from county reports. Patient medical records were then reviewed at all receiving hospitals. Victim arrival times were obtained and correct triage categories determined a priori using a combination of the modified Baxt criteria and hospital admission. Field and outcomes-based triage categories were compared, defining the appropriateness of each triage assignment. ResultsInvestigators reviewed 148 records at 14 receiving hospitals. Field triage designations comprised 22 red (immediate), 68 yellow (delayed), and 58 green (minor) patients. Outcomes-based designations found 2 red, 26 yellow, and 120 green patients. Seventynine patients were over-triaged, three were under-triaged, and 66 patients' outcomes matched their triage level. No triage level met both the 90% sensitivity and 90% specificity requirement set forth in the hypothesis, although red was 100% sensitive (95% CI 15.8-100) and green was 89.3% specific (95% CI 71.8-97.7). The Obuchowski statistic was 0.81, meaning that victims from a higher acuity outcome group had an 81% chance of assignment to a higher acuity triage category. Red patients arrived at hospitals 0.92 hours (95% CI 0.71-1.1) faster than other patients. ConclusionsThis analysis demonstrates poor agreement between triage levels assigned by START at a train crash and a priori outcomes criteria for each level. START ensured acceptable levels of under-triage (100% red sensitivity and 89% green specificity) but incorporated a significant amount of over-triage. START proved useful in prioritizing transport of the most critical patients to area hospitals first.

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“…Firstly, despite the extensive training of Ambulance Service staff, the outcome of any triage operation is subject to error, both from measurement and from bias. For example, there is a documented tendency to assign children to triage states of higher severity than is actually warranted (Frykberg, 2002). When providing decision support based on triage information, the effect of such errors should be monitored closely.…”

Section: Casualty Health In Mcismentioning

confidence: 99%

Modeling Uncertain and Dynamic Casualty Health in Optimization-Based Decision Support for Mass Casualty Incident Response

Wilson

Hawe

Coates

et al. 2015

Healthcare Administration

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Further information on publisher's website:http://dx.doi.org/10. 4018/jiscrm.2013040103 Publisher's copyright statement:Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details.

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Medical Management of Disasters and Mass Casualties From Terrorist Bombings: How Can We Cope?

Cited by 440 publications

References 44 publications

Performance characteristics of five triage tools for major incidents involving traumatic injuries to children

Performance characteristics of five triage tools for major incidents involving traumatic injuries to children

Does START Triage Work? An Outcomes Assessment After a Disaster

Modeling Uncertain and Dynamic Casualty Health in Optimization-Based Decision Support for Mass Casualty Incident Response

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