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Journal Article

Citation

Li X, Hu Q, Gregg A. J. Transp. Health 2022; 24: e101315.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.jth.2021.101315

PMID

unavailable

Abstract

Introduction
Emergency Medical Services (EMS) can respond to multiple types of urgent requests from patients demanding urgent healthcare. The total time duration of EMS responding to those requests consists of multiple delays at several stages (e.g., response-to-scene, on-scene, transport). Additionally, the corresponding delay at each stage may correlate with different characteristics (e.g., number of crews/patients, signal priority, acuity). Furthermore, those characteristics can have diversified correlations with EMS response for different urgent requests.

Methods
To capture the diversified correlations for crash-based and health-based EMS requests, this paper collected EMS call data (2018-2019) from the Alabama Department of Public Health and defined crash-based EMS responses as people who are injured in traffic crashes and health-based EMS response as people who either have heart-related health issues or stroke. To account for unobserved heterogeneity due to limited available data, we use random parameter parametric survival models to explore potential varying correlations of the characteristics associated with delays at different stages for three EMS response types.

Results
The results indicate that 108,304, 110,262, and 24,421 EMS responses were requested for traffic crashes, heart problems, and stroke, respectively. The modeling results show that at different stages of EMS responses, the characteristics and their associations with stage delays are diversified. For example, at stage 1, work-related illness or injury is positively correlated with delay for crash- and heart-based EMS responses, but it has a negative association with delay for stroke-based EMS response. Emergency Medical Dispatch (EMD) performed, the number of crews at stage 2, automated signal changing technology at stage 3, additional agency on-scene at stage 4, and stretcher usage at stage 5 are found to correlate with reduced delays at each corresponding stage.

Conclusions
This study offers implications about how various EMS response characteristics impact the delay for three types of EMS response: crash-, heart-, and stroke-based. The findings on those key characteristics would help researchers as well as EMS response personnel better understand how they are associated with EMS delays at different stages.


Language: en

Keywords

EMS delay; Heart problems; Parametric survival models; Stroke; Traffic crashes; Unobserved heterogeneity

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