Gleaning Data from Disaster: A Hospital-Based Data Mining Method to Studying All-Hazard Triage after'a Chemical Disaster

2.50
Hdl Handle:
http://hdl.handle.net/10755/303930
Category:
Full-text
Type:
Presentation
Title:
Gleaning Data from Disaster: A Hospital-Based Data Mining Method to Studying All-Hazard Triage after'a Chemical Disaster
Author(s):
Culley, Joan Marie; Tavakoli, Abbas; Svendsen, Erik R.; Craig, Jean B.
Lead Author STTI Affiliation:
Alpha Xi
Author Details:
Joan Marie Culley, PhD, MPH, MS, RN, CWOCN, jculley@sc.edu; Abbas Tavakoli, DrPH, MPH, ME; Erik R. Svendsen, PhD, MS, BS; Jean B. Craig, PhD, MS, BS;
Abstract:

Session presented on: Wednesday, July 24, 2013

Purpose:

On January 6, 2005, a freight train carrying three tanker cars of liquid chlorine was inadvertently switched onto an industrial spur in central Graniteville, South Carolina. 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. This research focuses on the victims who received emergency care in South Carolina. The objective of presentation is 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.

Methods:

We developed a method for evaluating currently available triage models using extracted data from medical records of the victims from the Graniteville chlorine disaster.

Results:

With our data mapping and decision tree logic, we were successful in employing the available extracted clinical data to estimate triage categories for use in triage effectiveness research.

Conclusion:

The methodology outlined in this paper can be used to assess the performance of triage models after a disaster. The steps are reliable and repeatable and can easily be extended or applied to other disaster datasets.

Keywords:
Triage Effectiveness Research; All Hazard Mass Casualty Triage; Data Mining Techniques
Repository Posting Date:
22-Oct-2013
Date of Publication:
22-Oct-2013 ; 22-Oct-2013
Conference Date:
2013
Conference Name:
24th International Nursing Research Congress
Conference Host:
Sigma Theta Tau International, the Honor Society of Nursing
Conference Location:
Prague, Czech Republic
Description:
24th International Nursing Research Congress Theme: Bridge the Gap Between Research and Practice Through Collaboration. Held at the Hilton Prague Hotel.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_GB
dc.language.isoenen
dc.type.categoryFull-texten
dc.typePresentationen
dc.titleGleaning Data from Disaster: A Hospital-Based Data Mining Method to Studying All-Hazard Triage after'a Chemical Disasteren
dc.contributor.authorCulley, Joan Marieen
dc.contributor.authorTavakoli, Abbasen
dc.contributor.authorSvendsen, Erik R.en
dc.contributor.authorCraig, Jean B.en
dc.contributor.departmentAlpha Xien
dc.author.detailsJoan Marie Culley, PhD, MPH, MS, RN, CWOCN, jculley@sc.edu; Abbas Tavakoli, DrPH, MPH, ME; Erik R. Svendsen, PhD, MS, BS; Jean B. Craig, PhD, MS, BS;en
dc.identifier.urihttp://hdl.handle.net/10755/303930-
dc.description.abstract<p>Session presented on: Wednesday, July 24, 2013</p><b>Purpose: </b> <p>On January 6, 2005, a freight train carrying three tanker cars of liquid chlorine was inadvertently switched onto an industrial spur in central Graniteville, South Carolina. 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. This research focuses on the victims who received emergency care in South Carolina. The objective of presentation is 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. <p><b>Methods: </b> <p>We developed a method for evaluating currently available triage models using extracted data from medical records of the victims from the Graniteville chlorine disaster. <p><b>Results: </b> <p>With our data mapping and decision tree logic, we were successful in employing the available extracted clinical data to estimate triage categories for use in triage effectiveness research. <p><b>Conclusion: </b> <p>The methodology outlined in this paper can be used to assess the performance of triage models after a disaster. The steps are reliable and repeatable and can easily be extended or applied to other disaster datasets.en
dc.subjectTriage Effectiveness Researchen
dc.subjectAll Hazard Mass Casualty Triageen
dc.subjectData Mining Techniquesen
dc.date.available2013-10-22T20:26:05Z-
dc.date.issued2013-10-22-
dc.date.issued2013-10-22en
dc.date.accessioned2013-10-22T20:26:05Z-
dc.conference.date2013en
dc.conference.name24th International Nursing Research Congressen
dc.conference.hostSigma Theta Tau International, the Honor Society of Nursingen
dc.conference.locationPrague, Czech Republicen
dc.description24th International Nursing Research Congress Theme: Bridge the Gap Between Research and Practice Through Collaboration. Held at the Hilton Prague Hotel.en
All Items in this repository are protected by copyright, with all rights reserved, unless otherwise indicated.