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UBC Theses and Dissertations

Evaluating post-earthquake functionality and surge capacity of hospital emergency departments using discrete event simulation Palomino Romani, Gerald M.

Abstract

Past earthquakes have illustrated the impacts of reduced hospital functionality due to physical damage resulting in a health service deficit immediately after a major seismic event. In this paper, a methodology was developed to quantify the deficit in health care anticipated due to a loss of functionality of a hospital emergency department (ED) and a surge in demand due to regional damage in an earthquake scenario. Earthquake-induced patient arrivals were calculated using multi-severity casualty estimation for the catchment area of the hospital. The surge in patients was then compared to the ability of the hospital to treat patients (capacity) based on anticipated functionality. Nonlinear response history analysis of the hospital building was performed using simplified structural models, and the structural and nonstructural component damage was estimated based on FEMA P-58. Expected damage was linked to the post-earthquake functionality of the ED services areas on each floor by incorporating the fault tree analysis method. Lastly, Discrete event simulation was utilized to evaluate the ED surge capacity, providing hospital performance metrics such as wait times (WT) and length of stay (LOS) for patients of ranging acuity. A case study of a hospital in the City of Vancouver subjected to an Mw9.0 Cascadia Subduction Zone scenario earthquake was presented. Emergency rooms were identified as the ED bottleneck during the emergency response. The mean ER WT exceeded its limit of two hours and reached up to 17 hours in the most unfavorable simulation. Likewise, the mean LOS nearly doubled from 6.5 to 12 hours, also exceeding the established target of 10 hours. The deployment of field hospitals for less severe patients as an emergency plan to mitigate the ED overcrowding was also analyzed to demonstrate that the methodology can be used as a decision support tool to improve healthcare disaster planning.

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Attribution-NonCommercial-NoDerivatives 4.0 International