Patient distribution in a mass casualty event of an airplane crash

Postma, I.L.E.; Weel, Hanneke; Heetveld, Martin J.; Zande, Ineke van der; Bijlsma, Taco S.; Bloemers, Frank W.; Goslings, J. Carel

doi:10.1016/j.injury.2013.04.027

Cited by 14 publications

(10 citation statements)

References 13 publications

(18 reference statements)

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“…In a Dutch study, under-triage occurred in 10.9% (95% CI, 7.4 to 15.7) of cases with over-triage being 39.5% (95% CI, 36.9 to 42.1) 11 . While in a retrospective study of the Turkish Airline crash, of the 135 victims triaged by ambulance teams, there was an over-triage rate of 89.0% and under-triage rate of 12.0% 12 13 …”

Section: Discussionmentioning

confidence: 95%

“…Over-triage seems to occur more frequently than under-triage with rates documented between 40.0% and 89.0% compared to less than 15.0% of the time. [11][12][13] An important reason for triage errors is the lack of adherence to the triage algorithm, occurring up to 26.0% of the time. 11,14,15 Fitzharris, et al found variations in triage performance across different training levels of prehospital personnel where the highest adherence rates (77.0%) occurred among the lowest-level trained personnel.…”

Section: Introductionmentioning

confidence: 99%

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A Comparison Between Differently Skilled Prehospital Emergency Care Providers in Major-Incident Triage in South Africa

Alenyo

Smith

McCaul

et al. 2018

Prehosp. Disaster med.

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Accuracy of major-incident triage across all levels of prehospital providers in South Africa is less than optimal with non-significant differences post-major-incident training. Prior major-incident training played a significant role in triage accuracy indicating that training should be an ongoing process. Although ALS providers were the quickest to complete triage, this difference was not clinically significant. The BLS and ILS providers with major-incident training can thus be utilized for primary major-incident triage allowing ALS providers to focus on more clinical roles.Alenyo AN, Smith WP, McCaul M, Van Hoving DJ. A comparison between differently skilled prehospital emergency care providers in major-incident triage in South Africa.

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Section: Discussionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

A Comparison Between Differently Skilled Prehospital Emergency Care Providers in Major-Incident Triage in South Africa

Alenyo

Smith

McCaul

et al. 2018

Prehosp. Disaster med.

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“…The problem can amplify, if the distribution of casualties between the medical facilities is not properly organized (Mulyasari et al 2013). There can be significant load disparities among the casualty receiving medical facilities involved in the MCI response (Hirshberg et al 1999;van Vugt 2001;Frykberg 2002Frykberg , 2004Postma et al 2013), with a tendency of overloading the nearest hospital in the system (Feliciano et al 1998;Gutierrez de Ceballos et al 2005). Establishing dedicated MCI hospitals can alleviate the excessive load at regular medical facilities in the wake of an MCI; however, this is an expensive and rarely employed option (Haverkort et al 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

“…For most urban centers the issue remains to reduce the strain on the system, and the mortality rate, through better utilization of the routine emergency medical facilities through the efficient distribution of the MCI casualties. However, the efficient distribution of MCI casualties has been an issue even in developed countries with advanced emergency services (Klein and Weigelt 1991;Frykberg 2002;Postma et al 2013). Equal distribution of patients across regional hospitals is often unsuccessful because of the dysfunctional use of distribution plans or lack thereof (Haverkort et al 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Mass-Casualty Distribution for Emergency Healthcare: A Simulation Analysis

Jat

Rafique

2020

Int J Disaster Risk Sci

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This study focuses on the casualty-load distribution problem that arises when a mass casualty incident (MCI) necessitates the engagement of multiple medical facilities. Employing discrete event simulations, the study analyzed different MCI response regimes in Lahore, Pakistan, that vary in terms of the level of casualty-load distribution and the required coordination between the incident site and the responding hospitals. Past terrorist attacks in this major metropolitan area were considered to set up experiments for comparing delays in treatment under the modeled regimes. The analysis highlights that the number of casualties that are allowed to queue up at the nearest hospital before diverting the casualty traffic to an alternate hospital can be an important factor in reducing the overall treatment delays. Prematurely diverting the casualty traffic from the incident site to an alternate hospital can increase the travel time, while a delay in diversion can overload the nearest hospital, which can lead to overall longer waiting times in the queue. The casualty distribution mechanisms based only on the responding hospitals' available capacity and current load can perform inefficiently because they overlook the trade-off between the times casualties spend in traveling and in queues.

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“…They assure optimal patient distribution with respect to the surrounding trauma centres and resources such as disposability of CT being one of those. 13,14 focused assessment with sonography for trauma (FAST) ultrasound is established to quickly screen for those life-threatening injuries which imply inevitable surgery without further diagnostics. 15 The power, accuracy and high availability of modern multislice-CTs drive on-going replacement of conventional X-ray examinations in initial polytrauma handling.…”

Section: Introductionmentioning

confidence: 99%