Motor Vehicle Crash Characteristics That Are Predictive of High Acuity Patients: An Analysis of Linked Ambulance and Crash Data

© 2020 National Association of EMS Physicians. Background: Motor vehicle crashes (MVCs) comprise a significant component of emergency medical service workload. Due to the potential for life-threatening injuries, ambulances are often dispatched at the highest priority to MVCs. However, previous...

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Main Authors: Ceklic, Ellen, Tohira, Hideo, Ball, Stephen, Brown, Elizabeth, Brink, D., Bailey, Paul, Whiteside, Austin, Finn, Judith
Format: Journal Article
Language:English
Published: TAYLOR & FRANCIS INC 2020
Subjects:
Online Access:http://purl.org/au-research/grants/nhmrc/1116453
http://hdl.handle.net/20.500.11937/80336
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author Ceklic, Ellen
Tohira, Hideo
Ball, Stephen
Brown, Elizabeth
Brink, D.
Bailey, Paul
Whiteside, Austin
Finn, Judith
author_facet Ceklic, Ellen
Tohira, Hideo
Ball, Stephen
Brown, Elizabeth
Brink, D.
Bailey, Paul
Whiteside, Austin
Finn, Judith
author_sort Ceklic, Ellen
building Curtin Institutional Repository
collection Online Access
description © 2020 National Association of EMS Physicians. Background: Motor vehicle crashes (MVCs) comprise a significant component of emergency medical service workload. Due to the potential for life-threatening injuries, ambulances are often dispatched at the highest priority to MVCs. However, previous research has shown that only a small proportion of high-priority ambulance responses to MVCs encounter high acuity patients. Alternative methods for triaging patients over the phone are required to reduce the burden of over-triage. One method is to use information readily available at the scene (e.g. whether a person was a motorcyclist, ejection status or whether an airbag deployed) as potential predictors of high acuity. Methods: A retrospective cohort study was conducted of all MVC patients in Perth attended by St John Western Australia between 2014 and 2016. Ambulance data was linked with Police crash data. The outcome variable of interest was patient acuity, where high acuity was defined as where a patient (1) died on-scene or (2) was transported by ambulance on priority one (lights & sirens) from the scene to hospital. Crash characteristics that are predictive of high acuity patients were identified by estimating crude odds ratios and 95% confidence intervals. Results: Of the 18,917 MVC patients attended by SJ-WA paramedics, 6.4% were classified as high acuity patients. The odds of being a high acuity patient was greater for vulnerable road users (motorcyclists, pedestrians and cyclists) than for motor vehicle occupants (OR 3.19, 95% CI, 2.80–3.64). A ‘not ambulant patient’ (one identified by paramedics as unable to walk or having an injury incompatible with being able to walk) had 15 times the odds of being high acuity than ambulant patients (OR 15.34, 95% CI, 11.48–20.49). Those who were trapped in a vehicle compared to those not trapped (OR 4.68, 95% CI, 3.95–5.54); and those who were ejected (both partial and full) from the vehicle compared to those not ejected (OR 6.49, 95% CI, 4.62–9.12) had higher odds of being high acuity patients. Discussion: There were two important findings from this study: (1) few MVC patients were deemed to be high acuity; and (2) several crash scene characteristics were strong predictors of high acuity patients.
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spelling curtin-20.500.11937-803362021-06-16T06:45:18Z Motor Vehicle Crash Characteristics That Are Predictive of High Acuity Patients: An Analysis of Linked Ambulance and Crash Data Ceklic, Ellen Tohira, Hideo Ball, Stephen Brown, Elizabeth Brink, D. Bailey, Paul Whiteside, Austin Finn, Judith Science & Technology Life Sciences & Biomedicine Emergency Medicine Public, Environmental & Occupational Health motor vehicle crash dispatch ambulance priority one lights & sirens patient acuity INJURY SEVERITY OSISP ALGORITHM ROLLOVER TRIAGE © 2020 National Association of EMS Physicians. Background: Motor vehicle crashes (MVCs) comprise a significant component of emergency medical service workload. Due to the potential for life-threatening injuries, ambulances are often dispatched at the highest priority to MVCs. However, previous research has shown that only a small proportion of high-priority ambulance responses to MVCs encounter high acuity patients. Alternative methods for triaging patients over the phone are required to reduce the burden of over-triage. One method is to use information readily available at the scene (e.g. whether a person was a motorcyclist, ejection status or whether an airbag deployed) as potential predictors of high acuity. Methods: A retrospective cohort study was conducted of all MVC patients in Perth attended by St John Western Australia between 2014 and 2016. Ambulance data was linked with Police crash data. The outcome variable of interest was patient acuity, where high acuity was defined as where a patient (1) died on-scene or (2) was transported by ambulance on priority one (lights & sirens) from the scene to hospital. Crash characteristics that are predictive of high acuity patients were identified by estimating crude odds ratios and 95% confidence intervals. Results: Of the 18,917 MVC patients attended by SJ-WA paramedics, 6.4% were classified as high acuity patients. The odds of being a high acuity patient was greater for vulnerable road users (motorcyclists, pedestrians and cyclists) than for motor vehicle occupants (OR 3.19, 95% CI, 2.80–3.64). A ‘not ambulant patient’ (one identified by paramedics as unable to walk or having an injury incompatible with being able to walk) had 15 times the odds of being high acuity than ambulant patients (OR 15.34, 95% CI, 11.48–20.49). Those who were trapped in a vehicle compared to those not trapped (OR 4.68, 95% CI, 3.95–5.54); and those who were ejected (both partial and full) from the vehicle compared to those not ejected (OR 6.49, 95% CI, 4.62–9.12) had higher odds of being high acuity patients. Discussion: There were two important findings from this study: (1) few MVC patients were deemed to be high acuity; and (2) several crash scene characteristics were strong predictors of high acuity patients. 2020 Journal Article http://hdl.handle.net/20.500.11937/80336 10.1080/10903127.2020.1771487 English http://purl.org/au-research/grants/nhmrc/1116453 TAYLOR & FRANCIS INC fulltext
spellingShingle Science & Technology
Life Sciences & Biomedicine
Emergency Medicine
Public, Environmental & Occupational Health
motor vehicle
crash
dispatch
ambulance
priority one
lights & sirens
patient acuity
INJURY SEVERITY
OSISP ALGORITHM
ROLLOVER
TRIAGE
Ceklic, Ellen
Tohira, Hideo
Ball, Stephen
Brown, Elizabeth
Brink, D.
Bailey, Paul
Whiteside, Austin
Finn, Judith
Motor Vehicle Crash Characteristics That Are Predictive of High Acuity Patients: An Analysis of Linked Ambulance and Crash Data
title Motor Vehicle Crash Characteristics That Are Predictive of High Acuity Patients: An Analysis of Linked Ambulance and Crash Data
title_full Motor Vehicle Crash Characteristics That Are Predictive of High Acuity Patients: An Analysis of Linked Ambulance and Crash Data
title_fullStr Motor Vehicle Crash Characteristics That Are Predictive of High Acuity Patients: An Analysis of Linked Ambulance and Crash Data
title_full_unstemmed Motor Vehicle Crash Characteristics That Are Predictive of High Acuity Patients: An Analysis of Linked Ambulance and Crash Data
title_short Motor Vehicle Crash Characteristics That Are Predictive of High Acuity Patients: An Analysis of Linked Ambulance and Crash Data
title_sort motor vehicle crash characteristics that are predictive of high acuity patients: an analysis of linked ambulance and crash data
topic Science & Technology
Life Sciences & Biomedicine
Emergency Medicine
Public, Environmental & Occupational Health
motor vehicle
crash
dispatch
ambulance
priority one
lights & sirens
patient acuity
INJURY SEVERITY
OSISP ALGORITHM
ROLLOVER
TRIAGE
url http://purl.org/au-research/grants/nhmrc/1116453
http://hdl.handle.net/20.500.11937/80336