Quantitative Evaluation of Fire and EMS Mobilization Times

Quantitative Evaluation of Fire and EMS Mobilization Times presents comprehensive empirical data on fire emergency and EMS call processing and turnout times, and aims to improve the operational benchmarks of NFPA peer consensus standards through a close examination of real-world data. The book also identifies and analyzes the elements that can influence EMS mobilization response times. Quantitative Evaluation of Fire and EMS Mobilization Times is intended for practitioners as a tool for analyzing fire emergency response times and developing methods for improving them. Researchers working in a related field will also find the book valuable.

List of contents

Study Questions and Research Methods.- Recruiting Participants.- Data Collection.- Data Analysis.- Primary Findings.- Conclusions.- Future Study Questions.

Summary

Quantitative Evaluation of Fire and EMS Mobilization Times presents comprehensive empirical data on fire emergency and EMS call processing and turnout times, and aims to improve the operational benchmarks of NFPA peer consensus standards through a close examination of real-world data. The book also identifies and analyzes the elements that can influence EMS mobilization response times. Quantitative Evaluation of Fire and EMS Mobilization Times is intended for practitioners as a tool for analyzing fire emergency response times and developing methods for improving them. Researchers working in a related field will also find the book valuable.

Product details

• Authors: Kathy A Notarianni, Kathy A. Notarianni, Rober Upson, Robert Upson
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 11.05.2012
• EAN: 9781461444411
• ISBN: 978-1-4614-4441-1
• No. of pages: 85
• Dimensions: 157 mm x 7 mm x 235 mm
• Weight: 184 g
• Illustrations: XX, 85 p. 46 illus.
• Series: SpringerBriefs in Fire; SpringerBriefs in Fire
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics