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dc.contributor.authorBui, David P
dc.contributor.authorGriffin, Stephanie C
dc.contributor.authorFrench, Dustin D
dc.contributor.authorHu, Chengcheng
dc.contributor.authorPorter, Keshia Pollack
dc.contributor.authorJung, Alesia M
dc.contributor.authorCrothers, Steve
dc.contributor.authorBurgess, Jefferey L
dc.date.accessioned2020-02-12T18:19:49Z
dc.date.available2020-02-12T18:19:49Z
dc.date.issued2019-11-13
dc.identifier.citationBui, D. P., Griffin, S. C., French, D. D., Hu, C., Pollack Porter, K., Jung, A. M., … Burgess, J. L. (2019). The use of proactive risk management to reduce emergency service vehicle crashes among firefighters. Journal of Safety Research, 71, 103–109. https://doi.org/10.1016/j.jsr.2019.09.020 ‌en_US
dc.identifier.issn0022-4375
dc.identifier.pmid31862021
dc.identifier.doi10.1016/j.jsr.2019.09.020
dc.identifier.urihttp://hdl.handle.net/10150/636998
dc.description.abstractIntroduction: Emergency service vehicle crashes (ESVCs), including rollovers and collisions with other vehicles and fixed objects, are a leading cause of death among U.S. firefighters. Risk management (RM) is a proactive intervention to identifying and mitigating occupational risks and hazards. The goal of this study was to assess the effect of RM in reducing ESVCs. Methods: Three fire departments (A, B and C), representing urban and suburban geographies, and serving medium to large populations, participated in facilitated RM programs to reduce their ESVCs. Interventions were chosen by each department to address their department-specific circumstances and highest risks. Monthly crash rates per 10,000 calls were calculated for each department an average of 28 months before and 23 months after the start of the RM programs. Interrupted time series analysis was used to assess the effect of the RM programs on monthly crash rates. Poisson regression was used to estimate the number of crashes avoided. Economic data from Department A were analyzed to estimate cost savings. Results: Department A had a 15.4% (P = 0.30) reduction in the overall monthly crash rate immediately post-RM and a 1% (P = 0.18) decline per month thereafter. The estimated two-year average cost savings due to 167 crashes avoided was $253,100 (95%CI= $192,355 - $313,885). Department B had a 9.7% (P = 0.70) increase in the overall monthly crash rate immediately post-RM and showed no significant changes in their monthly crash rate. Department C had a 28.4% (P = 0.001) reduction in overall monthly crash rate immediately post-RM and a 1.2% (P = 0.09) increase per month thereafter, with an estimated 122 crashes avoided. Conclusions: RM programs have the potential to reduce ESVCs in the fire service and their associated costs; results may vary based on the interventions chosen and how they are implemented. Practical applications: Risk management may be an effective and broadly implemented intervention to reduce ESVCs in the US fire service. (C) 2019 The Author(s). National Safety Council and Elsevier Ltd.en_US
dc.language.isoenen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.rightsCopyright © 2019 The Author(s). National Safety Council and Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.subjectRisk managementen_US
dc.subjectFire serviceen_US
dc.subjectSafety and healthen_US
dc.subjectTime series analysisen_US
dc.subjectCrash preventionen_US
dc.titleThe use of proactive risk management to reduce emergency service vehicle crashes among firefightersen_US
dc.typeArticleen_US
dc.contributor.departmentUniv Arizona, Mel & Enid Zuckerman Coll Publ Hlthen_US
dc.identifier.journalJOURNAL OF SAFETY RESEARCHen_US
dc.description.noteOpen access articleen_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal published versionen_US
refterms.dateFOA2020-02-12T18:19:50Z


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