Simulating hospital evacuation—the influence of traffic and evacuation time windows

E Tayfur and K Taaffe

Journal of Simulation, 2009, vol. 3, issue 4, 220-234

Abstract: Hospital operators typically do not have the luxury of carrying out a sufficient number of full-scale drills to accurately predict performance (eg, evacuation completion time, time required to evacuate a patient, when to start the evacuation, etc) during evacuation. This research presents a stochastic model via simulation to address an advanced-notice evacuation event such as a hurricane. We employ a simulation-optimization approach, comparing the benefits of additional simulation replications or additional simulation test scenarios in providing statistical accuracy in the results. We then identify the staffing and vehicle transport requirements within a pre-specified evacuation time period while minimizing cost. Moreover, we provide these managers with a modelling framework that can indicate if their current resource set is inadequate to evacuate the patient population within the specified time period. Because the operational costs can be highly variable by facility, we present two alternate cost structures in the analysis. Finally, we consider the effect of varying the evacuation start time on overall cost, as well as evacuation completion. By accounting for competing traffic flow from the mass population evacuation, it would be in the best interest of the hospital to begin their evacuation early, however this is often not an option due to the uncertainty in weather predictions several days prior to hurricane landfall.

Date: 2009
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1057/jos.2009.16 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjsmxx:v:3:y:2009:i:4:p:220-234

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjsm20

DOI: 10.1057/jos.2009.16

Access Statistics for this article

Journal of Simulation is currently edited by Christine Currie

More articles in Journal of Simulation from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().