@article{ref1,
title="Gleaning data from disaster: A hospital-based data mining method to study all-hazard triage after a chemical disaster",
journal="American journal of disaster medicine",
year="2013",
author="Craig, Jean B. and Culley, Joan M. and Tavakoli, Abbas S. and Svendsen, Erik R.",
volume="8",
number="2",
pages="97-111",
abstract="OBJECTIVE: To describe the methods of evaluating currently available triage models for their efficacy in appropriately triaging the surge of patients after an all-hazards disaster.   Design: A method was developed for evaluating currently available triage models using extracted data from medical records of the victims from the Graniteville chlorine disaster.   Setting: On January 6, 2005, a freight train carrying three tanker cars of liquid chlorine was inadvertently switched onto an industrial spur in central Graniteville, SC. The train then crashed into a parked locomotive and derailed. This caused one of the chlorine tankers to rupture and immediately release ~60 tons of chlorine. Chlorine gas infiltrated the town with a population of 7,000.   Participants: This research focuses on the victims who received emergency care in South Carolina.   RESULTS: With our data mapping and decision tree logic, the authors were successful in using the available extracted clinical data to estimate triage categories for use in our study.   CONCLUSIONS: The methodology outlined in this article shows the potential use of well-designed secondary analysis methods to improve mass casualty research. The steps are reliable and repeatable and can easily be extended or applied to other disaster datasets.<p /> <p>Language: en</p>",
language="en",
issn="1932-149X",
doi="10.5055/ajdm.2013.0116",
url="http://dx.doi.org/10.5055/ajdm.2013.0116"
}