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. 2024 Oct 23:12:1453788.
doi: 10.3389/fpubh.2024.1453788. eCollection 2024.

Effect of emergency medical service response time on fatality risk of freeway crashes: Bayesian random parameters spatial logistic approach

Peng Huang  1 , Sheng Ouyang  1 , Han Yan  1 , Xiaofei Wang  2 , Jaeyoung Jay Lee  3 , Qiang Zeng  2
Affiliations

Effect of emergency medical service response time on fatality risk of freeway crashes: Bayesian random parameters spatial logistic approach

Peng Huang et al. Front Public Health. .

Abstract

Introduction: Emergency medical service (EMS) serves as a pivotal role in linking injured road users to hospitals via offering first aid measures and transportation. This paper aims to investigate the effect of emergency medical service (EMS) response time on the fatality risk of freeway crashes.

Methods: Crash injury severity data from Kaiyang Freeway, China in 2014 and 2015 are employed for the empirical investigation. A Bayesian random parameters spatial logistic model is developed for analyzing crash severity.

Results: Bayesian inference of the random parameters spatial logistic model demonstrates the importance of reducing EMS response time on minimizing the fatality risk of freeway crashes. Fatality odds would increase by 2.6% for 1 min increase in EMS response time. Additionally, vehicle type, crash type, time of day, horizontal curvature, vertical grade, and precipitation are also found to have significant effects on the fatality probability of freeway crashes.

Conclusion: It is crucial to reduce EMS response time to decrease the fatality likelihood of freeway crashes. Some countermeasures have been proposed to shorten EMS response time.

Keywords: emergency medical service; fatality risk; freeway crash; random parameters spatial logistic model; response time.

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Conflict of interest statement

PH, SO, and HY were employed by Guangzhou Expressway Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The distribution of EMS response time.
Figure 2
Figure 2
History plot of the parameter for EMS response time in the random parameters model.
Figure 3
Figure 3
Traveling path of a rescue vehicle.
See this image and copyright information in PMC

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