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Area of Science:

  • Emergency Medicine
  • Disaster Preparedness
  • Healthcare Management

Background:

  • Effective disaster response hinges on accurately predicting immediate burn bed availability.
  • Burn centers (BCs) can adapt to surge needs, but initial bed capacity is a critical planning challenge.
  • Existing methods for assessing real-time bed availability are often limited.

Purpose of the Study:

  • To analyze historical burn bed census data to predict immediate bed availability during disaster surge events.
  • To provide a data-driven model for disaster planners to estimate initial burn bed capacity.
  • To improve decision-making regarding patient allocation in mass casualty incidents.

Main Methods:

  • Retrospective analysis of 86 Burn Bed Census (BBC) reports over an 8-year period (January 2009 - December 2016).
  • Data collected from a consortium of 27 northeastern burn centers via telephone bed census.
  • Statistical analysis included calculating mean, standard deviation (SD), and linear trends of available ICU and step-down beds.

Main Results:

  • The mean number of immediately available burn beds across the 27 centers was 72.
  • Monthly averages ranged from 62 beds in January to 78 beds in November.
  • Monthly standard deviations varied, with lower variability in July (SD=6) and higher in November (SD=17).

Conclusions:

  • A mean of 72 immediately available beds provides a predictable baseline for disaster planning in the region.
  • Understanding monthly variations and standard deviations allows for more nuanced predictions of surge capacity.
  • This predictive model enhances the ability of planners and clinicians to make informed decisions on initial patient placement during mass casualty events.