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Assessment of hospital surge capacity using the MACSIM simulation system: a pilot study

Overview of attention for article published in European Journal of Trauma and Emergency Surgery, June 2016
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Title
Assessment of hospital surge capacity using the MACSIM simulation system: a pilot study
Published in
European Journal of Trauma and Emergency Surgery, June 2016
DOI 10.1007/s00068-016-0686-1
Pubmed ID
Authors

K. Lennquist Montán, L. Riddez, S. Lennquist, A. C. Olsberg, H. Lindberg, D. Gryth, P. Örtenwall

Abstract

The aim of this study was to use a simulation model developed for the scientific evaluation of methodology in disaster medicine to test surge capacity (SC) in a major hospital responding to a simulated major incident with a scenario copied from a real incident. The tested hospital was illustrated on a system of magnetic boards, where available resources, staff, and patients treated in the hospital at the time of the test were illustrated. Casualties were illustrated with simulation cards supplying all data required to determine procedures for diagnosis and treatment, which all were connected to real consumption of time and resources. The first capacity-limiting factor was the number of resuscitation teams that could work parallel in the emergency department (ED). This made it necessary to refer severely injured to other hospitals. At this time, surgery (OR) and intensive care (ICU) had considerable remaining capacity. Thus, the reception of casualties could be restarted when the ED had been cleared. The next limiting factor was lack of ventilators in the ICU, which permanently set the limit for SC. At this time, there was still residual OR capacity. With access to more ventilators, the full surgical capacity of the hospital could have been utilized. The tested model was evaluated as an accurate tool to determine SC. The results illustrate that SC cannot be determined by testing one single function in the hospital, since all functions interact with each other and different functions can be identified as limiting factors at different times during the response.

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Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 13%
Researcher 7 11%
Student > Master 7 11%
Student > Doctoral Student 5 8%
Student > Postgraduate 5 8%
Other 14 22%
Unknown 18 28%
Readers by discipline Count As %
Medicine and Dentistry 19 30%
Nursing and Health Professions 8 13%
Engineering 5 8%
Social Sciences 3 5%
Agricultural and Biological Sciences 2 3%
Other 9 14%
Unknown 18 28%