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Prätherapeutische Ablaufanalyse bei einem Massenanfall von Verletzten

Vergleich von zwei Traumazentren der höchsten Versorgungsstufe

Pretreatment mass casualty incident workflow analysis

Comparison of two level 1 trauma centers

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Zusammenfassung

Hintergrund

Ein Massenanfall von Verletzten (MANV) stellt besonders hohe Anforderungen an die Versorgungsprozesse, tritt aber im Krankenhausalltag nur selten auf. Daher ist es üblich Simulationen für das Training des Personals und für die institutionelle Ablaufoptimierung einzusetzen.

Ziel der Arbeit

Ziel der Arbeit war ein Vergleich von zwei unterschiedlich aufgebauten Traumazentren der höchsten Versorgungsstufe hinsichtlich der prätherapeutischen Versorgungsabläufe im Falle eines simulierten MANV-Ereignisses.

Material und Methoden

Ein MANV mit 70 Verletzten wurde mit Schauspielpatienten so realistisch wie möglich simuliert. Die Triage am Unfallort wies 7 Patienten dem Traumazentrum A mit relativ langen internen Versorgungswegen sowie 4 Patienten dem Traumazentrum B mit kürzeren solchen Wegen zu. Die benötigten Versorgungszeiten wurden an definierten Punkten erfasst und mit dem Mann-Whitney-U-Test verglichen.

Ergebnisse

Die Patientenverteilungsmatrix war insofern effektiv als kein gleichzeitiges Eintreffen mehrerer Patienten erfolgte. A benötigte mehr Zeit (Minuten) von der Aufnahme bis zu den Endpunkten (A: 31,85 ± 7,99; B: 21,62 ± 4,76; p = 0,059). Dabei waren insbesondere der Aufenthalt im Schockraum (A: 8,46 ± 3,02; B: 2,73 ± 0,78, p < 0,01) als auch die Transferzeit zum Computertomographie- (CT-)Raum (A: 1,81 ± 0,62; B: 0,06 ± 0,03, p < 0,01) verlängert. Ein kürzerer Aufenthalt im CT-Raum konnte dies nicht kompensieren (A: 8,87 ± 1,84; B: 10,40 ± 2,89, p = 0,571). An beiden Standorten war die Bildberechnung und Verteilung relativ zeitaufwändig (17,36 ± 3,05).

Diskussion

Wenngleich kurze interne Wege die prätherapeutischen Behandlungsprozesse erheblich beschleunigten, blieben alle beiden Standorte deutlich innerhalb der „golden hour“. Der größte potenzielle Engpass war die Zeit, bis Bilder an den Endpunkten verfügbar waren.

Abstract

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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Literatur

  1. Abir M, Choi H, Cooke CR et al (2012) Effect of a mass casualty incident: clinical outcomes and hospital charges for casualty patients versus concurrent inpatients. Acad Emerg Med 19:280–286

    Article  PubMed  Google Scholar 

  2. Bail HJ, Kleber C, Haas NP et al (2009) Distribution planning of injured persons in mass disasters or catastrophes. Structuring of hospital capacities exemplified by the catastrophe network of the German Society for Trauma Surgery (DGU). Unfallchirurg 112:870–877

    Article  CAS  PubMed  Google Scholar 

  3. Fu CY, Wang SY, Hsu YP et al (2013) The diminishing role of pelvic x‑rays in the management of patients with major torso injuries. Am J Emerg Med 32(1):18–23

    Article  PubMed  Google Scholar 

  4. Geijer M, El-Khoury GY (2006) MDCT in the evaluation of skeletal trauma: principles, protocols, and clinical applications. Emerg Radiol 13:7–18

    Article  PubMed  Google Scholar 

  5. Geyer LL, Koerner M, Wirth S et al (2013) Polytrauma: optimal imaging and evaluation algorithm. Semin Musculoskelet Radiol 17:371–379

    Article  PubMed  Google Scholar 

  6. Halpern P, Goldberg SA, Keng JG et al (2012) Principles of emergency department facility design for optimal management of mass-casualty incidents. Prehosp Disaster Med 27:204–212

    Article  PubMed  Google Scholar 

  7. Hick JL, Christian MD, Sprung CL (2010) Chapter 2. Surge capacity and infrastructure considerations for mass critical care. Recommendations and standard operating procedures for intensive care unit and hospital preparations for an influenza epidemic or mass disaster. Intensive Care Med 36(Suppl 1):11–20

    Article  Google Scholar 

  8. Hornburger P, Schuster S, Schmöller G et al (2006) Das Münchener Wellenmodell – Verteilungsmatrix für Patienten bei einem Massenanfall von Verletzten. Brandschutz 60:380–386

    Google Scholar 

  9. Huber-Wagner S, Lefering R, Kay MV et al (2009) Duration and predictors of emergency surgical operations – basis for medical management of mass casualty incidents. Eur J Med Res 14:532–540

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Huber-Wagner S, Lefering R, Qvick LM et al (2009) Effect of whole-body CT during trauma resuscitation on survival: a retrospective, multicentre study. Lancet 373:1455–1461

    Article  PubMed  Google Scholar 

  11. Johnson PT, Scott WW, Gayler BW et al (2014) The CT scout view: does it need to be routinely reviewed as part of the CT interpretation? AJR Am J Roentgenol 202:1256–1263

    Article  PubMed  Google Scholar 

  12. Kanz KG, Huber-Wagner S, Lefering R et al (2006) Estimation of surgical treatment capacity for managing mass casualty incidents based on time needed for life-saving emergency operations. Unfallchirurg 109:278–284

    Article  PubMed  Google Scholar 

  13. Kimura A, Tanaka N (2013) Whole-body computed tomography is associated with decreased mortality in blunt trauma patients with moderate-to-severe consciousness disturbance: a multicenter, retrospective study. J Trauma Acute Care Surg 75:202–206

    Article  PubMed  Google Scholar 

  14. Kleber C, Cwojdzinski D, Strehl M et al (2013) Results of in-hospital triage in 17 mass casualty trainings: underestimation of life-threatening injuries and need for re-triage. Am J Disaster Med 8:5–11

    Article  PubMed  Google Scholar 

  15. Korner M, Geyer LL, Wirth S et al (2011) 64-MDCT in mass casualty incidents: volume image reading boosts radiological workflow. AJR Am J Roentgenol 197:W399–404

    Article  PubMed  Google Scholar 

  16. Korner M, Krotz M, Kanz KG et al (2006) Development of an accelerated MSCT protocol (Triage MSCT) for mass casualty incidents: comparison to MSCT for single-trauma patients. Emerg Radiol 12:203–209

    Article  CAS  PubMed  Google Scholar 

  17. Korner M, Krotz MM, Degenhart C et al (2008) Current role of emergency US in patients with major trauma. Radiographics 28:225–242

    Article  PubMed  Google Scholar 

  18. Korner M, Krotz MM, Wirth S et al (2009) Evaluation of a CT triage protocol for mass casualty incidents: results from two large-scale exercises. Eur Radiol 19:1867–1874

    Article  PubMed  Google Scholar 

  19. Korner M, Reiser M, Linsenmaier U (2009) Imaging of trauma with multi-detector computed tomography. Radiologe 49:510–515

    Article  CAS  PubMed  Google Scholar 

  20. Markogiannakis H, Sanidas E, Messaris E et al (2008) Predictors of in-hospital mortality of trauma patients injured in vehicle accidents. Ulus Travma Acil Cerrahi Derg 14:125–131

    PubMed  Google Scholar 

  21. Mccoy CE, Chakravarthy B, Lotfipour S (2013) Guidelines for field triage of injured patients: in conjunction with the morbidity and mortality weekly. Report published by the center for disease control and prevention. West J Emerg Med 14:69–76

    Article  PubMed  PubMed Central  Google Scholar 

  22. Russo A (2009) Negative and positive prognostic factors in polytrauma, especially referring to “golden hour”. Ann Ital Chir 80:337–349

    PubMed  Google Scholar 

  23. Salhanick SD, Sheahan W, Bazarian JJ (2003) Use and analysis of field triage criteria for mass gatherings. Prehosp Disaster Med 18:347–352

    PubMed  Google Scholar 

  24. Saltzherr TP, Bakker FC, Beenen LF et al (2012) Randomized clinical trial comparing the effect of computed tomography in the trauma room versus the radiology department on injury outcomes. Br J Surg 99(Suppl 1):105–113

    Article  PubMed  Google Scholar 

  25. Sasser SM, Hunt RC, Faul M et al. (2012) Guidelines for field triage of injured patients: recommendations of the National Expert Panel on Field Triage, 2011. MMWR. Recommendations and reports: Morbidity and mortality weekly report. Recommendations and reports/Centers for Disease Control 61:1–20

  26. Sefrin P, Kuhnigk H (2008) The role of patient flow and surge capacity for in-hospital response in mass casualty events. Anasthesiol Intensivmed Notfallmed Schmerzther 43:232–235

    Article  PubMed  Google Scholar 

  27. Sprung CL, Zimmerman JL, Christian MD et al (2010) Recommendations for intensive care unit and hospital preparations for an influenza epidemic or mass disaster: summary report of the European Society of Intensive Care Medicine’s Task Force for intensive care unit triage during an influenza epidemic or mass disaster. Intensive Care Med 36:428–443

    Article  PubMed  Google Scholar 

  28. Turris SA, Lund A, Bowles RR (2014) An analysis of mass casualty incidents in the setting of mass gatherings and special events. Disaster Med Public Health Prep (Epub ahead of print). doi:10.1017/dmp.2014.24

    PubMed  Google Scholar 

  29. Unfallchirurgie DGF (2011) S3 – Leitlinie Polytrauma/Schwerverletzten-Behandlung. In: AWMF Berlin

  30. Wolf S, Partenheimer A, Voigt C et al (2009) Primary care hospital for a mass disaster MANV IV. Experience from a mock disaster exercise. Unfallchirurg 112:565–574

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Institut für Klinische Radiologie, Klinikum der Ludwig-Maximilians-Universität München, Nußbaumstr. 20, 80336, München, Deutschland

    F. Mück, K. Wirth, M. Muggenthaler, D. Maxien & S. Wirth

  2. Klinik und Poliklinik für Unfallchirurgie, Klinikum rechts der Isar, Technische Universität München, Ismaningerstr. 22, 81675, München, Deutschland

    K. G. Kanz

  3. Klinik für Anästhesiologie, Klinikum der Ludwig-Maximilians-Universität München, Nußbaumstr. 20, 80336, München, Deutschland

    U. Kreimeier

  4. Institut für Interventionelle und Diagnostische Radiologie, HELIOS Klinikum München West, Steinerweg 5, 81241, München, Deutschland

    U. Linsenmeier

  5. Klinik für Allgemeine, Unfall-, Hand- und Plastische Chirurgie, Ludwig-Maximilians-Universität München, Nußbaumstr. 20, 80336, München, Deutschland

    W. Mutschler

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Correspondence to F. Mück.

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Interessenkonflikt

F. Mück, K. Wirth, M. Muggenthaler, K.G. Kanz, U. Kreimeier, D. Maxien, U. Linsenmeier, W. Mutschler und S. Wirth geben an, dass kein Interessenkonflikt besteht.

Dieser Beitrag beinhaltet keine von den Autoren durchgeführten Studien an Menschen oder Tieren.

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W. Mutschler, München

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Mück, F., Wirth, K., Muggenthaler, M. et al. Prätherapeutische Ablaufanalyse bei einem Massenanfall von Verletzten. Unfallchirurg 119, 632–641 (2016). https://doi.org/10.1007/s00113-016-0200-6

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