Triage beim Massenanfall von Verletzten (MANV)

Neidel, Tobias; Heller, Axel R.

doi:10.1055/a-0607-1895

Cited by 4 publications

(2 citation statements)

References 8 publications

(13 reference statements)

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“…Die dann verbleibenden Patienten werden überwiegend den Sichtungskategorien I und II (rot und gelb) angehören und anhand des Vorsichtungsalgorithmus behandelt. Eine Nachsichtung insbesondere der Patienten der SK III wird empfohlen, da sich darunter noch bis zu 28 % Patienten der SK I befinden können [6].…”

Section: Maßnahmen Der Ersteintreffenden Rettungskräfteunclassified

Maßnahmen der ersteintreffenden Rettungskräfte beim Massenanfall von Verletzten

Faißt

Stuhr

Kerner

2023

NOTARZT

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ZusammenfassungDie Bewältigung von Großschadensfällen stellt insbesondere für die ersteintreffenden Einsatzkräfte eine große Herausforderung dar. Es ist daher wichtig, in dieser Situation ruhig, überlegt, rasch und zielorientiert zu handeln. Neben einer ersten Lageeinschätzung, Kontaktaufnahme zur Einsatzleitung und einer ersten alarmierenden Rückmeldung stellen die (Vor-)Sichtung, Raumordnung und die Organisation der Einsatzstelle die wichtigsten Handlungsfelder dar. Neben dem Eigenschutz der Einsatzkräfte ist es das wichtigste Ziel, die schwer verletzten und am dringendsten zu behandelnden Patienten der Sichtungskategorie I schnell zu identifizieren, notfallmedizinisch zu versorgen und zu transportieren.

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Section: Maßnahmen Der Ersteintreffenden Rettungskräfteunclassified

Maßnahmen der ersteintreffenden Rettungskräfte beim Massenanfall von Verletzten

Faißt

Stuhr

Kerner

2023

NOTARZT

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“…Even though the term triage seems to have taken on a weighty meaning with the pandemic, it is still not new and triage algorithms have been used for a long time like in the emergency department or for mass casualty incidents. Triage within mass casualty incidents is about saving as many patients as possible with limited resources outside the hospital [21,37,38]. For emergency departments, the task is on classifying arriving patients due to urgency of treatment whereby scarce resources play a subordinate role [17].…”

Section: Introductionmentioning

confidence: 99%

Covid-19 triage in the emergency department 2.0: how analytics and AI transform a human-made algorithm for the prediction of clinical pathways

Bartenschlager,

Grieger,

Erber

et al. 2023

Health Care Manag Sci

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The Covid-19 pandemic has pushed many hospitals to their capacity limits. Therefore, a triage of patients has been discussed controversially primarily through an ethical perspective. The term triage contains many aspects such as urgency of treatment, severity of the disease and pre-existing conditions, access to critical care, or the classification of patients regarding subsequent clinical pathways starting from the emergency department. The determination of the pathways is important not only for patient care, but also for capacity planning in hospitals. We examine the performance of a human-made triage algorithm for clinical pathways which is considered a guideline for emergency departments in Germany based on a large multicenter dataset with over 4,000 European Covid-19 patients from the LEOSS registry. We find an accuracy of 28 percent and approximately 15 percent sensitivity for the ward class. The results serve as a benchmark for our extensions including an additional category of palliative care as a new label, analytics, AI, XAI, and interactive techniques. We find significant potential of analytics and AI in Covid-19 triage regarding accuracy, sensitivity, and other performance metrics whilst our interactive human-AI algorithm shows superior performance with approximately 73 percent accuracy and up to 76 percent sensitivity. The results are independent of the data preparation process regarding the imputation of missing values or grouping of comorbidities. In addition, we find that the consideration of an additional label palliative care does not improve the results.

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