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[Pretreatment mass casualty incident workflow analysis : Comparison of two level 1 trauma centers]
F Mück1, K Wirth2, M Muggenthaler2
1Institut für Klinische Radiologie, Klinikum der Ludwig-Maximilians-Universität München, Nußbaumstr. 20, 80336, München, Deutschland. fabian.mueck@med.uni-muenchen.de.
Background:
Mass casualty incidents (MCI) have particularly high demands on patient care processes but occur rather rarely in daily hospital routine. Therefore, it is common to use simulations to train staff and to optimize institutional processes.
Objectives:
Aim of study was to compare the pre-therapeutic in-house workflow of two differently structured level 1 trauma sites in the case of a simulated mass casualty incident (MCI).
Materials And Methods:
A MCI of 70 patients was simulated by actors in a manner that was as realistic as possible. The on-site triage assigned 7 cases to trauma site A with relatively long in-house distances and 4 patients to an independent trauma site B in which these distances were relatively short. During in-house treatment, time intervals for reaching milestones were measured and compared using the Mann-Whitney U test.
Results:
As no simultaneous patient arrival occurred, the Patient Distribution Matrix proved to be effective. Site A needed more time (minutes) from admission to endpoints (A: 31.85 ± 7.99; B: 21.62 ± 4.76; p = 0.059). In detail, the time intervals were particularly longer for both patient stay in trauma room (A: 8.46 ± 3.02; B: 2.73 ± 0.78, p < 0.01) and transfer time to the CT room (A: 1.81 ± 0.62; B: 0.06 ± 0.03, p < 0.01). A shorter stay in the CT room did not compensate these effects (A: 8.86 ± 1.84; B: 10.40 ± 2.89, p = 0.571). For both sites, image calculation and distribution were relatively time consuming (17.36 ± 3.05).
Conclusions:
Although short in-house distances accelerated pretherapeutic treatment processes significantly, both sites remained clearly within the "golden hour". The strongest potential bottleneck was the time interval until images were available at the endpoints.
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