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Predictors of Prehospital On-Scene Time in an Australian Emergency Retrieval Service

Published online by Cambridge University Press:  17 June 2019

Patrick T. Fok ,
David Teubner ,
Jeremy Purdell-Lewis  and
Andrew Pearce
Patrick T. Fok
Affiliation:
Emergency Medical Retrieval Service, SAAS MedSTAR, Adelaide, South Australia, Australia Division of EMS, Department of Emergency Medicine, Dalhousie University, Halifax, Nova Scotia, Canada
David Teubner
Affiliation:
Emergency Medical Retrieval Service, SAAS MedSTAR, Adelaide, South Australia, Australia Emergency Department, Flinders Medical Centre, Adelaide, South Australia, Australia
Jeremy Purdell-Lewis
Affiliation:
Emergency Medical Retrieval Service, SAAS MedSTAR, Adelaide, South Australia, Australia Anaesthetic Department, Southmead Hospital, North Bristol NHS Trust, Bristol, United Kingdom
Andrew Pearce*
Affiliation:
Emergency Medical Retrieval Service, SAAS MedSTAR, Adelaide, South Australia, Australia ED/Trauma, Royal Adelaide Hospital, Adelaide, South Australia, Australia
*
Correspondence: Prof. Andrew Pearce, MD 2 Sir Reginald Ansett Drive Adelaide Airport, South Australia 5095 Australia E-mail: Andrew.Pearce@sa.gov.au
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Abstract

Introduction:

Prehospital physicians balance the need to stabilize patients prior to transport, minimizing the delay to transport patients to the appropriate level of care. Literature has focused on which interventions should be performed in the prehospital environment, with airway management, specifically prehospital intubation (PHI), being a commonly discussed topic. However, few studies have sought additional factors which influence scene time or quantify the impact of mission characteristics or therapeutic interventions on scene time.

Hypothesis/Problem:

The goal of this study was to identify specific interventions, patient demographics, or mission characteristics that increase scene time and quantify their impact on scene time.

Methods:

A retrospective, database model-building study was performed using the prehospital mission database of South Australian Ambulance Service (SAAS; Adelaide, South Australia) MedSTAR retrieval service from January 1, 2015 through August 31, 2016. Mission variables, including patient age, weight, gender, retrieval platform, physician type, PHI, arterial line placement, central line placement, and finger thoracostomy, were assessed for predictors of scene time.

Results:

A total of 506 missions were included in this study. Average prehospital scene time was 34 (SD = 21) minutes. Four mission variables significantly increased scene time: patient age, rotary wing transport, PHI, and arterial line placement increased scene time by 0.09 (SD = 0.08) minutes, 13.6 (SD = 3.2) minutes, 11.6 (SD = 3.8) minutes, and 34.4 (SD = 8.4) minutes, respectively.

Conclusion:

This study identifies two mission characteristics, patient age and rotary wing transport, and two interventions, PHI and arterial line placement, which significantly increase scene time. Elderly patients are medically complex and more severely injured than younger patients, thus, may require more time to stabilize on-scene. Inherent in rotary wing operations is the time to prepare for the flight, which is shorter during ground transport. The time required to safely execute a PHI is similar to that in the literature and has remained constant over the past two years; arterial line placement took longer than envisioned. The SAAS MedSTAR has changed its clinical practice guidelines for prehospital interventions based on this study’s results. Retrieval services should similarly assess the necessity and efficiency of interventions to optimize scene time, knowing that the time required to safely execute an intervention may reach a minimum duration. Defining the scene time enables mission planning, team training, and audit review with the aim of improved patient care.

Keywords

prehospital careprehospital timeretrieval medicinescene timetransport medicine
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 34 , Issue 3 , June 2019 , pp. 317 - 321
Copyright
© World Association for Disaster and Emergency Medicine 2019 

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Footnotes

Note: First and second authors contributed equally to this publication

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