Abstract

Capabilities for daily operations at medical facilities are determined by routine staffing levels and bed availability. Although all health care facilities must be prepared for mass casualty events, there are few tools or metrics to estimate nursing requirements, medical hold surge capacity, and critical failure points for high-volume events. We sought to create a modifiable and customizable toolkit for producing reliable capability estimates across a range of scenarios. The inputs for key variables (patient volume, acuity, staffing, beds available, and medical evacuation) were extrapolated from the literature and interviews with subject-matter experts. Models were developed for a small austere facility, one large facility, and one expanded large facility. Inputs were serially increased to identify the "failure point" for each and the variables most contributing to failure. Two scenarios were created, one moderate volume and one for mass casualty events. Variables most affecting capacity were identified as: average daily volume, mass casualty volume and frequency, acuity, and medical evacuation frequency. The large facility reached failure in 13 (43%) of 30 days and was attributed to bed capacity. The small facility did not reach failure point for bed capability or staffing under low volumes; however, it reached failure immediately under moderate volumes. The most significant factor was medical evacuation frequency. An automated dashboard was created to provide immediate estimates based on varying inputs. We developed an automated and customizable toolkit to analyze mass casualty/disaster capabilities in relation to nurse staffing and hold capacity, assess the impact of key variables, and predict resource needs. Total bed capacity and hospital throughput via discharge/medical evacuation are the most critical factors in surge capacity and sustained mass casualty operations. Decreasing medical evacuation frequency is the greatest contributor to reaching "failure point." Not Applicable.

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