A Simple Graphical Method for Quantification of Disaster Management Surge Capacity Using Computer Simulation and Process-control Tools.

INTRODUCTION: Surge capacity, or the ability to manage an extraordinary volume of patients, is fundamental for hospital management of mass-casualty incidents. However, quantification of surge capacity is difficult and no universal standard for its measurement has emerged, nor has a standardized statistical method been advocated. As mass-casualty incidents are rare, simulation may represent a viable alternative to measure surge capacity. Hypothesis/Problem The objective of the current study was to develop a statistical method for the quantification of surge capacity using a combination of computer simulation and simple process-control statistical tools. Length-of-stay (LOS) and patient volume (PV) were used as metrics. The use of this method was then demonstrated on a subsequent computer simulation of an emergency department (ED) response to a mass-casualty incident.

METHODS: In the derivation phase, 357 participants in five countries performed 62 computer simulations of an ED response to a mass-casualty incident. Benchmarks for ED response were derived from these simulations, including LOS and PV metrics for triage, bed assignment, physician assessment, and disposition. In the application phase, 13 students of the European Master in Disaster Medicine (EMDM) program completed the same simulation scenario, and the results were compared to the standards obtained in the derivation phase.

RESULTS: Patient-volume metrics included number of patients to be triaged, assigned to rooms, assessed by a physician, and disposed. Length-of-stay metrics included median time to triage, room assignment, physician assessment, and disposition. Simple graphical methods were used to compare the application phase group to the derived benchmarks using process-control statistical tools. The group in the application phase failed to meet the indicated standard for LOS from admission to disposition decision.

CONCLUSIONS: This study demonstrates how simulation software can be used to derive values for objective benchmarks of ED surge capacity using PV and LOS metrics. These objective metrics can then be applied to other simulation groups using simple graphical process-control tools to provide a numeric measure of surge capacity. Repeated use in simulations of actual EDs may represent a potential means of objectively quantifying disaster management surge capacity. It is hoped that the described statistical method, which is simple and reusable, will be useful for investigators in this field to apply to their own research.