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Identifying causes of delay in interfacility transports of injured patients
transported by air ambulance in Ontario
by
Brodie Nolan
A thesis submitted in conformity with the requirements for the degree of Master’s of
Science
Institute of Health Policy, Management & Evaluation University of Toronto
© Copyright by Brodie Nolan 2019
ii
Identifying causes of delay in interfacility transport of injured patients transported by air
ambulance in Ontario
Brodie Nolan
Master of Science
Institute for Health Policy, Management & Evaluation University of Toronto
2019
ABSTRACT:
INTRODUCTION: The purpose of this thesis was to examine patient, paramedic, and
institutional-related risk factors for delay and identify specific causes of delays in
interfacility transfers by air ambulance.
METHODS: Quantile regression was used to identify patient, paramedic and institutional
risk factors for delay. Manual chart review to identify specific causes of delay during
interfacility transport.
RESULTS: Characteristics associated with shorter time intervals included nursing
station as sending facility, rotor-wing aircraft and critical care paramedic crew. Patients
requiring mechanical ventilation or transported from academic centres were all associated
with prolonged times. A total of 458 causes of delay were identified. The most frequent
delays included refuelling, waiting for land EMS escort, documentation, and delays for
intubation, chest tube insertion and diagnostic imaging.
iii
CONCLUSION: Ventilator dependence, paramedic level of care, classification of
sending facility and helipad availability are associated with delays to interfacility
transport of injured patients.
iv
TABLE OF CONTENTS
1.0 Background ……………………………………………………………………. 1
1.1 Study Objectives ……………………………………………………………. 1
1.2 Trauma Epidemiology ……………………………………………………. 1
1.3 Development of Trauma Systems ……………………………………. 2
1.4 Trauma Centres ……………………………………………………………. 3
1.5 Trauma Prehospital Care ……………………………………………………. 4
Figure 1. Field Trauma Triage Guidelines (Ontario) ……………………………. 5
1.6 Use of Air Ambulance for Transporting Injured Patients ……………. 6
1.7 Overview of Ontario Trauma System ……………..…………………….. 7
Figure 2. Ontario Adult Trauma Centres and Referral Boundaries ……………. 8
1.8 Ornge Air Ambulance …………………………………………………... 9
Figure 3. Base locations of Ornge fixed-wing, rotor-wing and land resources …. 9
1.9 Prehospital Trauma Triage ………………………………………… .. 11
1.10 Delays During Interfacility Transfer ………………………………….. 13
1.11 Limitations of Previous Work ………………………………………….. 15
1.12 Rationale ...………………………………………………………………… 16
2.0 Identifying Patient, Paramedic and Institutional Risk Factors for Delay ….. 18
2.1 Methods ……….…………………………………………………………. 18
2.1.1 Primary Aim …………………………………………………... 18
2.1.2 Study Design …………………………………………………... 18
2.1.3 Data Sources …………………………………………………... 18
Figure 4. Measurement of time intervals during interfacility transport ... 19
2.1.4 Study Population …………………………………………... 19
2.1.5 Exposure Variable …………………………………………... 19
2.1.6 Outcomes …………………………………………............... 20
2.1.7 Data Analysis …………………………………………............... 21
2.2 Results …………………………………………………………………... 22
2.2.1 Patient and Injury Characteristics ……….……………………….. 22
Figure 5. Study flow diagram ……….………………………….. 23
v
Table 1. Patient characteristics …………………………………... 24
Table 2. Institutional characteristics …………………………………... 25
Table 3. Paramedic characteristics …………………………………... 25
2.2.2 Variability of time intervals …………………………………... 25
Figure 6. Variability of time intervals of interest …………………... 26
Table 4. Duration of time intervals across quantiles of interest ……….. 27
2.2.3 Quantile regression models …………………………………... 27
Table 5. Results of quantile regression model for Interval 1 (Time from
call accepted to wheels up time of aircraft) …………………………... 28
Table 6. Results of quantile regression model for Interval 2 (Time from
aircraft arriving at sending facility landing site to paramedic arrival at
patient bedside) …………………………………………………... 29
Table 7. Results of quantile regression model for Interval 3 (In-hospital
time) …………………………………………………………………... 30
Table 8. Results of quantile regression model for Interval 4 (Time from
departing patient bedside to arrival back at aircraft) …………………... 31
Table 9. Results of quantile regression model for Interval 5 (Time from
aircraft arrival at receiving centre to paramedic handover to trauma team)
…………………………………………………………………... 32
2.3 Discussion …………………………………………………………………... 33
3.0 Identified Causes of Delay During Interfacility Transport ……………........... 38
3.1 Methods …………………………………………………………………... 38
3.1.1 Primary Aim ………………………………………….................... 38
3.1.2 Secondary Aim …………………………………………................ 38
3.1.3 Study Design …………………………………………............... 38
3.1.4 Data Sources …………………………………………............... 38
Figure 7. Measurement of time intervals and grouping of delays during
interfacility transport …………………………………………............... 39
3.1.5 Study Population …………………………………………... 39
3.1.6 Identification and Classification of Delays ……………………..... 40
vi
3.1.7 Attributable Delay and Length of Delay Analysis …………... 42
Figure 8. Measurement of attributable time of delay …………………... 42
3.2 Results …………………………………………………………………... 43
3.2.1 Baseline Characteristics ………………………………………….. 43
3.2.2 Frequency and Total Attributable Time of Delays ………………. 43
Figure 9. Frequency of identified causes of delay …………………... 44
Figure 10. Pareto charts of total attributable time (in min) and cumulative
percent for each cause of delay …………………………………... 45
3.2.3 Average Length of Delay…………………………………………. 45
Table 10. Mean length of delay in minutes for each identified cause of
delay …………………………………………………………………... 46
3.3 Discussion …………………………………………………………………... 47
4.0 Conclusion …………………………………………………………………... 52
4.1 Directions for Future Research …………………………………………... 52
4.2 Conclusion of Thesis …………………………………………………... 53
5.0 Acknowledgements ............................................................................................ 54
6.0 References ........................................................................................................... 55
vii
LIST OF FIGURES
Figure 1. Field Trauma Triage Guidelines (Ontario)
Figure 2. Ontario Adult Trauma Centres and Referral Boundaries
Figure 3. Base locations of Ornge fixed-wing, rotor-wing and land resources
Figure 4. Measurement of time intervals during interfacility transport
Figure 5. Study flow diagram
Figure 6. Variability of time intervals of interest
Figure 7. Measurement of time intervals and grouping of delays during interfacility
transport
Figure 8. Measurement of attributable time of delay
Figure 9. Frequency of identified causes of delay
Figure 10. Pareto charts of total attributable time (in min) and cumulative percent for
each cause of delay
viii
LIST OF TABLES
Table 1. Patient characteristics
Table 2. Institutional characteristics
Table 3. Paramedic characteristics
Table 4. Duration of time intervals across quantiles of interest
Table 5. Results of quantile regression model for Interval 1 (Time from call accepted to
wheels up time of aircraft)
Table 6. Results of quantile regression model for Interval 2 (Time from aircraft arriving
at sending facility landing site to paramedic arrival at patient bedside)
Table 7. Results of quantile regression model for Interval 3 (In-hospital time)
Table 8. Results of quantile regression model for Interval 4 (Time from departing patient
bedside to arrival back at aircraft)
Table 9. Results of quantile regression model for Interval 5 (Time from aircraft arrival at
receiving centre to paramedic handover to trauma team)
Table 10. Mean length of delay in minutes for each identified cause of delay
1
1. BACKGROUND
1.1 Study Objectives
Delays to a trauma centre for definitive care and management of severe injuries have
been associated with increased morbidity and mortality.1-3 While interfacility transfers
are a known cause of delays to definitive care4 neither the nature of these delays, nor their
specific impact, are well understood. The primary objective of this thesis was to examine
patient, paramedic, and institutional risk factors for delay during interfacility transfer of
injured patients by air ambulance in Ontario. Specifically, I examined the impact of these
variables on various time intervals from time of request to transfer a patient through to
the time of handover to the trauma team at a trauma centre. To do this I used quantile
regression models to estimate how specified quantiles of the distribution of these time
variables varied with patient, paramedic and institutional characteristics. The secondary
objective of this thesis was to identify specific causes of delay to interfacility transfer of
injured patients transported by air ambulance and estimate the attributable time
associated with each delay.
1.2 Trauma Epidemiology
Traumatic injuries affect Canadians of all ages, races and socioeconomic backgrounds.
Unintentional injuries are the leading cause of death for Canadians between the ages of 1
and 24 and the second leading cause of death for those aged 24 to 44.5 An estimated 4.27
million Canadians aged 12 or older suffered an injury severe enough to limit their usual
activities every year.6 On a daily basis, more than 10,000 Canadians are injured seriously
2
enough to require medical attention. Of these, approximately 9,567 (93%) are seen in
emergency rooms, 43 (0.4%) die, 634 (6%) are hospitalized, and 165 (1.6%) are left
partially or totally disabled.7 Nationwide, motor vehicle collisions, falls and suicide are
the top three causes of death due to injuries.7 Annually in Ontario, injuries result in he
death of nearly 6000 people, over 75,000 hospitalizations and almost 6 billion dollars in
direct health care costs.7
1.3 Development of Modern Trauma Systems
Identification of the unique needs and resources required to optimally care for injured
patients led to the development of modern trauma systems. The American College of
Surgeons (ACS) first addressed trauma care in 1922 by forming a Committee on Trauma
– initially named the Committee on Treatment of Fractures.8 However, besides some
initial military initiatives there was little further interest in civilian injuries until the 1950s
and 1960s.8 In 1964, Waller et al. were the first to demonstrate that patients injured in a
rural setting were more likely to die despite having less severe injuries.9 This study,
along with many subsequent studies10-13, underscored the need for timely medical
intervention and prehospital care, which is arguably the guiding principle of modern
trauma system. There was significant uptake and development of regionalized trauma
systems in the 1990s, with work aimed at developing specialized trauma centres,
establishing prehospital trauma care guidelines, and identifying the need for rehabilitation
after injury.14 The ACS Committee on Trauma suggests that a comprehensive trauma
system should consist of injury prevention, prehospital care, specialized trauma centre
care, and post-acute care.14
3
1.4 Trauma Centres
The first document to recommend categorizing hospitals as trauma centres was published
by the ACS Committee on Trauma in 1976.15 Trauma centres are accredited based on
clinical and non-clinical criteria by the ACS in the United States or the Trauma
Association of Canada in Canada.14 To pass the clinical accreditation process in Canada,
a trauma centre must have a dedicated trauma team composed of: a trauma team leader,
general surgery, orthopedic surgery, and anesthesia team members.14 There must also be
immediate access to surgical subspecialties such as neurosurgery, cardiothoracic and
vascular surgery. An accredited trauma centre also requires a 24-hour emergency
department with comprehensive medical imaging facilities, a 24-hour operating room and
an appropriately staffed intensive care unit. The non-clinical criteria that must be met
include active research, education and quality improvement activities.14
Multiple studies have demonstrated the benefit of regionalized trauma centres.2 The
National Study on the Costs and Outcomes of Trauma showed a 25% reduction in
mortality for severely injured patients who received care at a trauma centre compared to
patients treated at a non–trauma centre.3 Additionally, a meta-analysis of 14 studies
demonstrated an overall 15% decline in mortality caused by the establishment of
regionalized trauma care at specialized trauma centres.16
4
1.5. Prehospital Trauma Care
The role of prehospital care in a trauma system is to transport injured patients to the
closest appropriate facility in a timely manner.17 There is the concept of the “golden hour
of trauma” which has been engrained in trauma systems and prehospital trauma care.17,18
The golden hour refers to the first 60 minutes after an injury is a critical period to
transport patients to a trauma centre to address life-threatening injuries.17,18 Although
there is little evidence to support a direct time cut-off, many studies have shown that
subgroups of injured patients, mostly those that require emergent surgical intervention,
have improved outcomes with short out-of-hospital times.11,17-19
One of the challenges in the prehospital care of injured patients is identifying patients
who would benefit from being brought directly to a trauma centre without overburdening
these specialized centres with minimally injured patients. The concept of appropriate
triage of injured patients has been the focus of a significant amount of work attempting to
balance over-triage and under-triage. Most efforts have been aimed at reducing under-
triage (the transport of severely injured patients to non trauma centres), which may result
in preventable morbidity and mortality owing to a delay in definitive care.20,21 Over-
triage (the transport of minimally injured patients to a trauma centre) does not have any
deleterious effect to the patient, however can contribute to unnecessary resource
utilization and overcrowding.22-25 In 2006 the Center for Disease Control and Prevention
worked with the ACS Committee on Trauma to establish the Field Trauma Triage
Guidelines (FTTG).26 The FTTG use physiologic, anatomic, mechanism of injury and
special considerations to identify the most severely injured patients that would benefit
5
from direct transport to a trauma centre; potentially bypassing a closer non-trauma
hospital.
Figure 1: Field Trauma Triage Guidelines (Ontario)
Emergency Health Services Branch
Paramedic Prompt Card for Field Trauma Triage Standard
This prompt card provides a quick reference of the Field Trauma Triage Standard contained in the Basic Life Support Patient Care Standards (BLS PCS). Please refer to the BLS PCS for the full standard.
6
1.6 Evidence for Air Ambulance Utilization
Identifying how patients should be transported to a trauma centre is a key aspect of
prehospital trauma care. The utilization of air ambulance to expedite transport to trauma
centres has become an engrained component of modern trauma systems. Intuitively the
use of air ambulance shortens the time to arrival to definitive care, which as mentioned
above has been associated with reduced mortality. The evidence supporting the benefit
of air ambulance use on outcomes for injured patients however is mixed.
Multiple retrospective studies using a national US database of injured patients (the
National Trauma Data Bank) demonstrated a mortality benefit from the use of helicopter
emergency medical services (HEMS) when compared to a cohort of injured patients
transported by land EMS.27-29 Likewise, an early literature review of the impact of HEMS
demonstrated increased survival in all identified studies, with 2.7 lives saved for every
100 HEMS deployments.30 This evidence was countered by studies questioning the
benefit of use of air medical transport, as many patients transported by air ambulance in
the United States were minimally injured and therefore the benefit of quick access would
be negligible.31-33 A meta-analysis of 22 studies of injured patients transported to trauma
centre by air ambulance showed almost 70% of all patients transported were minimally
injured and over 25% were discharged home within 24 hours of admission.34 Looking at
local evidence, a recent study comparing patients brought to a single trauma centre in
Ontario by either air ambulance or ground EMS showed that patients transported by air
ambulance had lower than predicted mortality, whereas patients transported by ground
EMS had higher than predicted mortality.12
7
Air medical transport carries both significant resource and financial costs to a healthcare
system. Air transport is extremely costly; with an estimated a cost of a single patient
transport by air ambulance to be $6,500 USD.35 In a time of scrutiny over health care
spending and trying to find efficiencies, the reduction in unnecessary use of air transport
for minimally injured patients might result in significant cost savings for a healthcare
system. Air transport is also associated with significant risks. Fatal accidents in the US
air medical transport system are increasing.36 In 2008 alone, air ambulance crashes were
responsible for 29 deaths in the US.35
It should be noted that there are significant differences between the American and
Canadian air ambulance systems. In Canada, the air medical transport system is
provincially funded and each transport is covered by publically funded provincial
healthcare, whereas in the United States, air medical transport is privately run and for-
profit.
1.7 The Ontario Trauma System
Ontario has more than 70 different land EMS agencies that are coordinated by upper-tier
municipalities (ie. counties, regional municipalities or districts).37 Although there are
slight differences in the medical directives between each of these EMS services, there are
provincial guidelines to standardize field trauma triage such that if these criteria are met
and patients are within 30-45 minutes drive of a trauma centre they should be transported
directly and bypass any non-trauma centre.38 Ontario has 9 adult trauma centres and
approximately 150 other acute care hospitals that are non trauma centres (Figure 2)7. In
8
Ontario, 40% of the population lives more than a 60 minutes drive to a trauma centre and
15% are more than a 60 minutes transport by air ambulance to a trauma centre.37 Fewer
than half of all severely injured patients are transported directly from the scene to a
trauma centre.39 The Ontario air ambulance system provides an essential service to
improve trauma care access to patients across the province.
Figure 2: Ontario Adult Trauma Centres and Referral Boundaries7
9
1.8 Scope of Ornge Air Ambulance
In Ontario, Ornge serves as the sole provider of both air medical transport and critical
care transport capability (land and air) for interfacility transfers of severely injured
patients. Ornge operates the largest air ambulance fleet in Canada, serving over 13
million people over one million square kilometers of land. They have 9 bases that
operate rotor or fixed-wing aircraft; these include Thunder Bay, Timmins, Kenora, Sioux
Lookout, Moosonee, Sudbury, Ottawa, Toronto and London. There is a fleet of twelve
Leonardo AW-139 helicopters and eight Pilatus Next Generation PC-12 airplanes with
eight helicopters and four airplanes operational on any given day.
Figure 3: Base locations of Ornge fixed-wing, rotor-wing and land resources
10
Ornge is staffed by primary, advanced and critical care paramedics. Primary care
paramedics have the most restricted scope of practice and can provide oxygen along with
limited medications such as toradol, ventolin, nitroglycerin and naloxone. Advanced care
paramedics can provide sedation and analgesia with fentanyl, ketamine and midazolam
and can administer tranexamic acid. Critical care paramedics have the largest scope of
practice with additional medication capabilities such as propofol, esmolol, and
vasopressin. Advanced and critical care paramedics are trained in a number of advanced
procedures including facilitated intubation and airway management, rapid sequence
intubation, needle thoracostomy and cricothyrotomy. Ornge advanced care and critical
care paramedics are the only paramedics in the province trained to transfuse blood
products, and to run ventilators and infusion pumps. A transport medicine physician
provides online medical oversight.
Patients are transported by Ornge to a trauma centre by one of three pathways: a scene
call, modified scene call, or interfacility transfer. A scene call is when a patient is
transported directly from the scene of injury to a trauma center. In these cases they will
bypass the closest hospital to expedite transport to a trauma center. A scene call can be
activated based on initial 9-1-1 information obtained by the central ambulance
communications center (CACC) or requested by the treating land EMS crew as per
FTTG. A modified scene call occurs when a local ground EMS crew meets the Ornge
crew at a site other than the initial place of injury and then transports the patient to a
trauma center. A modified scene call occurs when a scene call is activated, but local
ground EMS are ready to move the patient prior to the arrival of the air ambulance.
11
During a modified scene call, the land EMS crew arranges a rendezvous with the air
ambulance. This is often done at the local community hospital, but sometimes another
location such as a local airport is used. If a patient is brought to a non-trauma center as
part of a modified scene response, the physician at this hospital may help stabilize the
patient. This may include intubating, placing chest tubes, plain film x-rays, bedside
ultrasound, and any other procedures they deem necessary. The intent of a modified
scene response is always to expedite transfer to a trauma centre and patients are only
brought into a local hospital to rendezvous with the flight paramedics if there is a delay in
arrival of the aircraft. An interfacility transfer is a transport where a patient is initially
brought to a non-trauma centre where they are assessed, evaluated, stabilized, and then
later deemed to require transfer to a trauma centre. Interfacility transfers are not activated
through the CACC or land EMS crews but rather by the treating physician who makes a
conscious decision to transfer the patient to a trauma centre and requests an interfacility
transfer.
1.9 Prehospital Trauma Triage
There are many challenges associated with triaging injured patients appropriately to a
trauma centre. To begin with the patient must be identified by EMS that they meet FTTG
and then either transport them directly to a trauma centre or request an air medical scene
response if their transport time is too long. If the patient is not deemed to meet FTTG
they are taken to a non-trauma centre where through further work-up it may be
discovered they have injuries requiring transport to a trauma centre and an interfacility
transfer is requested.
12
There are some reasons why a severely injured patient may initially be brought to a non-
trauma centre by EMS. Many studies have shown that the timely and proper
identification all serious injuries in trauma patients to be challenging.40,41 The decision of
whether to transport a patient to a trauma centre or not must be made quickly and without
complete information. The FTTG were developed to help aid in this decision making for
EMS providers, but, while they are the best available tool for EMS, they lack both
sensitivity and specificity.42,43 Previous studies have identified several factors that are
associated with an increased risk of undertriage, including: elderly patients, decreased
level of consciousness, presence of intoxication, female sex and falls.44,45
Additionally some severely injured patients are intentionally brought to a non-trauma
centre as there is no available trauma centre within an acceptable safe distance to
transport. The remoteness of parts of Ontario make this especially challenging as 40% of
patients injured in Ontario are further than 60 minutes drive to a trauma centre and 15%
are not within a 60 minutes transport by air ambulance.37 These numbers were not taking
into account inclement weather or traffic conditions, which could limit timely access
even more.
Patients who are later transferred to a trauma centre after initial triage to a non-trauma
centre were associated with at least a 30% increase in mortality in the first 48 hours after
injury.46 A small study looking at air medical scene calls transferred to two Ontario
trauma centres showed that 35% of all air scene calls were cancelled, yet 25% of those
patients who were cancelled were still later transferred to a trauma centre.47 These
13
patients experienced a mean delay of over 2 hours before arriving at a trauma centre
compared to patients brought directly from the scene.47 Although it is unclear why these
scene calls were initially cancelled, it likely speaks to the difficulty in identifying
severely injured patients.47 Poor prehospital identification of severely injured patients
results in undertriage; with patients being initially brought to a non-trauma centre and
then requiring eventual transport to a trauma centre.47,48 This is one driver of delays that
occur during the interfacility transfer process.
1.10 Current Understanding of Delays During Interfacility Transfer
Delays in interfacility transfer are due to failure to immediately recognize the need for
transfer, prolonged evaluation or unnecessary interventions, and waiting for
transportation.4,49,50
The failure to immediately recognize the need for transfer is multifactorial. As
mentioned above, there are some well-known risks for under-recognition of injured
patients. These include elderly patients, decreased level of consciousness, presence of
intoxication, female sex and falls.44,45 Furthermore, the ACS Committee on Trauma has
suggested that patients whom meet any of the following being transferred to a dedicated
trauma centre14:
1. Confirmed blood pressure less than 90 mm Hg at any time in adults.
2. Gunshot wounds to the neck, chest, abdomen, or extremities proximal to the
elbow/knee.
14
3. Glasgow Coma Scale (GCS) score less than 9 with mechanism attributed to
trauma.
4. Transfer patients from other hospitals receiving blood to maintain vital signs.
5. Intubated patients transferred from scene or patients who have respiratory
compromise or are in need of an emergency airway.
One study found that compliance to these recommendations was only 51%-82%.49 The
study authors hypothesized that this may be due to lack of identification of patients
meeting a criterion for transfer or believing a patient can be adequately cared for at their
current institution.49 Failure to apply these criteria results in a delay in the decision to
transfer the patient and ultimately the interfacility transfer process.
Another significant cause of delay to interfacility transfer is prolonged evaluation.
Patients transferred from non-trauma centres that have surgical specialties available and
access to computed tomography (CT) scans have prolonged in-hospital times compared
to hospitals lacking these resources.50 It’s likely the availability of these resources may
lead to unnecessary interventions or work-up and increase the time before the patient is
transferred to a trauma centre. One study in Ontario found that common causes of in-
hospital delays included the sending physician performed a procedure and delays for
diagnostic imaging.4
Interfacility transport refers to the time from dispatch of the transporting medical team to
arrival of the patient at the receiving facility.4 There have been few studies looking at
causes of delay in interfacility transport process within the Ontario trauma system. One
15
study of 911 patients transported to two Ontario trauma centres by air ambulance showed
a median time to complete interfacility transport of 145 minutes (interquartile range of
116-175 minutes) with 5% of patients having a time of over 250 minutes.4 Modifiable
causes of delay to arriving at the sending facility included refuelling the aircraft, delays
related to crew changes and being cancelled off from transporting a patient and then later
called back. Lastly, delays to arriving at the trauma centre included waiting for land EMS
escort, the trauma team not being assembled and lack of clarity of who was to receive the
patient.4
1.11 Limitations of Prior Work
As mentioned above, there are few studies exploring causes of delay to interfacility
transfer. The few studies that have been done have significant limitations when
attempting to extrapolate to our provincial trauma system.
Most studies have assessed ways to optimize interfacility transfer within Ontario and
aimed to identify ways to improve access of rural patients to trauma care37,51. These
studies however do not focus on identifying specific causes of delay. Similarly, many
studies have been limited to patients cared for at individual trauma centres. These studies
have relied on trauma registry data or individual data-sharing agreements between
prehospital and hospital databases but have been limited to one or two trauma
centres.4,12,47 Lastly, most of these studies have been limited in their small sample size.
The largest study looking at modifiable causes of delay to air ambulance transport in
Ontario had only 150 delays identified and was a secondary outcome in the study.4
16
1.12 Rationale
Timely access to definitive care is a critical component of modern trauma systems and
has been shown to improve patient outcomes after injury.1-3 Access to a trauma centre is
not consistent throughout the world and patients without immediate access have had
worse outcomes.2 In Canada almost 66% of severely injured patients are initially brought
to a non-trauma centre for initial assessment and stabilization.46 Many of these patients
in Ontario are later transferred to a trauma center by our provincial air ambulance, Ornge.
Air ambulance is a costly and limited resource, although has been associated with
decreased mortality in the Ontario trauma system.12
Delays to a trauma centre for definitive care and management of severe injuries has been
associated with increased morbidity and mortality.46 While interfacility transfers have an
inherent delay to definitive care, neither the nature of these delays, nor their specific
impact, are well understood. The purpose of this study is to examine patient, paramedic,
and institutional-related risk factors for delay and identify specific causes of delays in
interfacility transfers by air ambulance.
A detailed analysis of the types and impact of delays to interfacility transport of severely
injured patients at a provincial level is essential to evaluate our current trauma system.
This study identified specific causes of modifiable delays and estimated the attributable
time associated with each of these delays. The information gained from this study will
provide a basis for future quality improvement endeavours and education of frontline
17
providers (at the physician and paramedic level as well as hospital and air ambulance
service level) and ensure our trauma system in Ontario is safe, efficient and timely
18
2. IDENTIFYING PATIENT, PARAMEDIC AND INSTITUTIONAL RISK
FACTORS FOR DELAY
2.1 Methods
2.1.1 Primary Aim
The primary objective of this study was to examine patient, paramedic, and institutional
risk factors for delay during interfacility transport of injured patients by air ambulance in
Ontario.
2.1.2 Study Design
This study was a retrospective cohort study of injured patients undergoing interfacility
transport to an Ontario trauma centre who were transported by air ambulance. Ethics
approval for this study was obtained from the research ethics board at the University of
Toronto.
2.1.3 Data sources
Data were derived from a database of electronic patient care records (ePCR) at Ornge
which includes all patients transported by Ornge paramedics. The ePCR includes data
pertaining to patient demographics, reason for transfer, vital signs, mechanism of injury,
ventilator settings and parameters, medications administered, interventions performed
and information on the level of paramedic care and type of aircraft being used.
19
There are various times associated with each transport that were entered by paramedics
and collected in the ePCR (Figure 1). These include the time that the call was accepted,
the time the crew leaves their base, the time they arrive at sending facility landing site,
the times they arrive and depart from patient bedside, the time they depart from sending
facility landing site, the time they arrive at the receiving trauma centre landing site and
the time they handover to the trauma team.
Figure 4: Measurement of time intervals during interfacility transport
2.1.4 Study population
We included all emergent interfacility transports for injured patients aged 16 years or
greater transported to a trauma centre between January 1, 2013 and December 31, 2017.
Patients who were classified as being an urgent or non-urgent priority transfer, who were
transported to a non-trauma centre or who were transported by a land ambulance were
excluded from the study. Patients with missing or implausible times were removed from
the study.
2.1.5 Exposure variables: Patient, paramedic and institutional characteristics
The primary objective of our study was to assess the impact of patient, paramedic and
institutional characteristics on key time intervals during the interfacility transport process.
Arrive at
sending
hospital/
landing site
Call acceptedCrew leave
base
Arrive at
patient
bedside
Depart patient
bedside
Depart
sending
hospital/
landing site
Arrive at
receiving
hospital/
landing site
Handover to
trauma team
Flight Time Flight TimeInterval 1 Interval 2 Interval 3 Interval 4 Interval 5
20
Patient and injury characteristics that were recorded included: age, sex, mechanism of
injury, ventilator dependence at time of request to transfer, the first vitals signs obtained
by transporting paramedics (heart rate, respiratory rate, oxygen saturation, systolic blood
pressure and Glasgow coma scale [GCS]), time of day and season of transport. Paramedic
and transport attributes explored included paramedic level of care (primary, advanced or
critical care) and type of aircraft (rotor or fixed-wing). We also assessed institutional
characteristics of the sending facility (academic, community with greater than 100 beds,
community with less than 100 beds or nursing station), aircraft landing site characteristics
of sending and receiving facilities (landing pad at hospital requiring to land ambulance
transfer, landing pad remote from hospital requiring land ambulance transport, and no
landing pad at hospital requiring landing at local airport with land ambulance transport))
and volume of receiving trauma centre (categorized by tertile of patients arriving by air
ambulance).
2.1.6 Outcomes
The primary outcome of interest was the modifiable time to complete the interfacility
transport process. Using the times captured in ePCR, we created five unique time
intervals for each patient that occurred during their interfacility transport (Figure 1).
Flight times for both the flight to sending facility and flight to receiving centre were not
assessed in this study, as they are non-modifiable. In total the five intervals of interest
were defined as follows: Interval 1 (time from call accepted to wheels up time of
aircraft); Interval 2 (time from aircraft arriving at sending facility landing site to
paramedic arrival at patient bedside); Interval 3 (in-hospital time), Interval 4 (time from
21
departing patient bedside to arrival back at aircraft), Interval 5 (time from aircraft arrival
at receiving centre to paramedic handover to trauma team). Time intervals were
measured in minutes. The primary outcome of interest – modifiable time to complete
interfacility transport – was defined as the sum of Intervals 1-5.
2.1.7 Data analysis
Descriptive statistics were used to assess the distribution for all variables of interest in
each group. Continuous variables were assessed for normality by evaluating kurtosis and
skewness and were summarized as means and standard deviations or medians and
interquartile range for normal and non-normally distributed data, respectively.
Categorical variables were displayed as counts and percentages. P-values less than 0.05
were considered statistically significant for all analyses.
Multivariable analyses of the association between patient, paramedic and institutional
characteristics and interfacility transport intervals were conducted by quantile regression.
Commonly used regression models for determining the association of variables with an
outcome, such as ordinary least squares (OLS) or linear regression, assess how the mean
of a conditional distribution varies with changes in system or patient characteristics.52
However, the mean of a distribution may be a poor indicator of central tendency, and
conveys limited information about how the system performs for the majority of patients,
which requires an analysis of the tail of a distribution.53 Due to our interest in delays
during the interfacility transport process (i.e. the skewed tail of the distribution of interval
times), we elected to use quantile regression modelling in our analysis.
22
We created five quantile regression models, one for each of the time intervals measured.
All exposure variables were considered for inclusion of each model. Variable selection
for each model was determined using stepwise selection with significance levels to enter
and exit the model set at 0.1. Patients with any missing data for one or more of the
variables of interest were excluded from the final model. Missing data resulted in
exclusion of less than 1% of observations.
Quantile regression models at the 10th, 30th, 50th, 70th, and 90th percentiles were used to
determine the effect of patient, paramedic and institutional characteristics on time
intervals to interfacility transport. All variables were assessed for multicollinearity using
a variation inflation factor (VIF) of 4 as the cut-off for exclusion.
All statistical analyses were conducted using SAS Studio version 3.71 (SAS Institute,
North Carolina, USA).
2.2 Results
2.2.1 Patient and injury characteristics
There were a total of 24,608 adult emergent interfacility transfers transported by Ornge
between January 1, 2013 and December 31, 2017, of which 2,884 met our inclusion
criteria (Figure 4). After excluding patients that were transported by critical care land
EMS or had missing/implausible time data, our final study population was 2,178 patients.
The study patient, paramedic and institutional characteristics are summarized in Table 1.
23
The median patient age was 46 years (interquartile range [IQR] 28-62) and 73.7% were
male. The most frequent mechanisms of injury were motor vehicle collisions (36.4%)
and falls (23.0%), while penetrating injuries accounted for 4.0% of injuries.
Figure 5: Study flow diagram
24
Table 1: Patient characteristics
Patient Characteristics (n = 2,178) Age, median (IQR) 46 (28,62) Age in years grouped, n (%) Less than 35 35-44 45-54 55-64 65-74 Greater than 75
787 (36.1) 284 (13.0) 352 (16.2) 317 (14.6) 238 (10.9) 200 (9.2)
Sex, n (%) Male Female
1607 (73.7) 571 (26.3)
Mechanism of injury, n (%) Motor Vehicle Fall Penetrating Other
793 (36.4) 500 (23.0) 86 (4.0)
799 (36.6) Heart rate (beats/min), n (%) Greater than 100 50-100 Less than 50
618 (28.4) 1426 (65.4) 134 (6.2)
Respiratory rate (breaths/min), n (%) Greater than 29 10-29 Less than 10
65 (3.0)
1931 (88.6) 182 (8.4)
Systolic blood pressure, n (%) Greater than 180 90-180 Less than 90
55 (2.5)
1963 (90.1) 160 (7.4)
Oxygen saturation less than 90%, n (%) 238 (10.9) Glasgow coma scale, n (%) 13-15 9-12 <8
1467 (67.4)
42 (1.9) 669 (30.7)
Mechanically ventilated, n (%) 565 (25.9) Time of transport, n (%) 08:00-16:59 17:00-23:59 00:00-07:59
795 (36.5) 853 (39.2) 530 (24.3)
Season of transport, n (%) Winter Spring Summer
Fall
346 (15.9) 548 (25.2) 803 (36.8) 481 (22.1)
25
Table 2: Institutional characteristics
Class of hospital, n (%) Academic Community >100 beds Community <100 beds
Nursing station
80 (3.7)
782 (35.9) 1204 (55.3) 112 (5.1)
Landing site of sending facility, n (%) Local airport At hospital with short drive by land EMS At hospital, no land EMS component
655 (30.1) 152 (7.0)
1371 (62.9) Landing site of receiving trauma centre, n (%) Local airport At hospital with short drive by land EMS At hospital, no land EMS component
122 (5.6) 858 (39.4) 1198 (55.0)
Volume of trauma centre, n (%) High volume (>350 transports) Mid volume (150-300 transports) Low volume (<150 transports)
1229 (56.4) 704 (32.3) 245 (11.3)
Table 3: Paramedic characteristics
Paramedic level of care, n (%) Primary care Advanced care Critical care
28 (1.3)
581 (26.7) 1569 (72.0)
Type of aircraft, n (%) Rotor-wing Fixed-wing
1551 (71.2) 627 (28.8)
2.2.2 Variability of time intervals
The variability of time intervals is summarized in Figure 5. The duration of each time
interval across the 10th, 30th, 50th, 70th and 90th percentiles are displayed in Table 2.
Interval 3, the in-hospital time, was the longest with a median time of 29 minutes (IQR
17-45 minutes, 90th percentile 71 minutes).
26
Figure 6: Variability of time intervals of interest
010
20
30
40
50
60
70
80
Interval1:Tim
efrom
callaccep
tedto
whe
elsu
ptim
eofaircraft
Interval2:Tim
efrom
aircraftarrivingat
send
ingfacilityland
ingsitetoparam
edic
arriv
alatp
atientbed
side
Interval3:In-ho
spita
ltim
eInterval4:Tim
efrom
dep
artin
gpatie
nt
bedsidetoarrivalbackataircraft
Interval5:Tim
efrom
aircraftarrivalat
receivingcentreto
param
edichando
verto
traumateam
Percent
TimeInterval
Time(m
in)
0-15
16-30
31-45
46-60
61-75
76-90
91-105
>105
27
Table 4: Duration of time intervals across quantiles of interest (in minutes) Variable
10th
30th
Quantile50th
70th
90th
Interval1 3 8 10 15 26 Interval2 3 7 10 15 30Interval3 9 19 29 41 71Interval4 4 9 12 17 31Interval5 7 12 17 25 47
2.2.3 Quantile regression models
The results of each quantile regression model are summarized in Tables 3-7.
The characteristics identified through quantile regression that were significantly
associated with a shorter time interval at the 90th percentile were nursing station as
sending facility and rotor-wing aircraft. By contrast, an academic centre as the sending
facility or the need for a land EMS escort were both associated with prolonged times.
The magnitude of effect of these characteristics on time was largest at higher quantiles.
Furthermore, patients that were mechanically ventilated were associated with longer in-
hospital times across all quintiles and patients transported with a critical care paramedic
crew had shorter in-hospital times compared to advanced care paramedic crews.
28
Table 5: Results of quantile regression model for Interval 1 (Time from call accepted to wheels up time of aircraft) Variable
10th
30th
Quantile50th
70th
90th
Heartrate>10050-100<50
0.0Ref-2.0
-0.3Ref-1.3
-0.3Ref-2.0*
0.0Ref-2.0
-2.2 Ref -4.3
Respiratoryrate>3010-30<10
-3.0*Ref3.0*
-0.5Ref1.8*
-0.7Ref1.7*
-2.0Ref3.0*
-7.8Ref4.8
GCS13-159-12<8
Ref1.0-1.0
Ref1.0-0.3
Ref0.80.3
Ref2.00.0
Ref7.61.0
Timeofday08:00-16:5917:00-23:5900:00—7:59
Ref2.0*2.0*
Ref0.8*1.3*
Ref0.7*0.7*
Ref1.01.0
Ref2.23.3
ClassofHospitalAcademiccentreCommunity>100bedsCommunity<100bedsNursingstation
0.0-1.0Ref0.0
0.2-0.8*Ref1.8*
2.1*-0.7*Ref3.7*
4.0*-2.0*Ref5.0*
18.5*-3.0Ref-1.2
LandingsiteattraumacentreAthospital,nolandescortAthospital,landescortLocalairport
Ref-1.0-3.0
Ref-0.3-3.5*
Ref-0.3-3.3*
Ref0.0-4.0*
Ref0.9-5.8*
TraumacentrevolumeHighesttertileMiddletertileLowesttertile
Ref-1.02.0
Ref0.32.0*
Ref0.03.0*
Ref1.04.0*
Ref0.95.0
LevelofcarePrimarycareAdvancedcareCriticalcare
Ref-1.00.0
Ref-1.5-2.5
Ref-3.7*-5.7*
Ref-4.0-7.0*
Ref
-24.1*-28.2*
TypeofaircraftRotor-wingFixed-wing
1.0Ref
-1.5*Ref
-2.3*Ref
-3.0*Ref
-7.2*Ref
Coefficient estimates are reported as change to time interval in minutes GCS = Glasgow coma scale, Ref=reference, *p-value<0.05
29
Table 6: Results of quantile regression model for Interval 2 (Time from aircraft arriving at sending facility landing site to paramedic arrival at patient bedside) Variable
10th
30th
Quantile50th
70th
90th
Heartrate>10050-100<50
1.0Ref1.0
0.3Ref0.3
0.7Ref0.7
0.8Ref0.6
0.0Ref0.0
Mechanicallyventilated 1.0* 1.3* 1.7* 2.4* 3.0*ClassofHospitalAcademiccentreCommunity>100bedsCommunity<100bedsNursingstation
-1.01.0*Ref-3.0*
1.7*1.3*Ref-8.0*
5.0*1.7*Ref
-13.0*
9.0*1.6*Ref
-19.3*
26.0*0.0Ref
-22.0*LandingsiteatsendingfacilityAthospital,nolandescortAthospital,landescortLocalairport
Ref1.0*2.0*
Ref3.0*4.3*
Ref2.7*5.0*
Ref2.5*7.3*
Ref6.0*11.0*
TraumacentrevolumeHighesttertileMiddletertileLowesttertile
Ref0.00.0
Ref0.30.0
Ref0.31.3*
Ref0.31.1
Ref3.0*3.0
SeasonSummerFallWinterSpring
0.00.00.0Ref
0.00.7*0.3Ref
0.31.3*1.7*Ref
-0.11.01.1*Ref
0.03.0*1.0Ref
TypeofaircraftRotor-wingFixed-wing
1.0*Ref
-4.3*Ref
-11.7*Ref
-18.1*Ref
-27.0*Ref
Coefficient estimates are reported as change to time interval in minutes Ref=reference, *p-value<0.05
30
Table 7: Results of quantile regression model for Interval 3 (In-hospital time) Variable
10th
30th
Quantile50th
70th
90th
AgeLessthan3535-4445-5455-6465-74Greaterthan7
Ref1.00.02.5*0.50.5
Ref1.42.6*3.0*2.60.9
Ref1.40.72.03.1*0.2
Ref0.41.53.36.8*0.3
Ref2.07.6*4.16.86.4
Heartrate>10050-100<50
1.0Ref-2.0
1.5Ref-0.7
3.1*Ref1.2
2.6*Ref-3.8
6.4*Ref-9.4
Oxygensaturation<90% 1.5 2.1 1.8 8.6* 10.2*Mechanicallyventilated 12.5* 18.1* 22.9* 29.5* 37.1*MechanismofinjuryMotorvehicleFallPenetratingOther
1.50.5-1.0Ref
2.3*-1.3-3.2Ref
3.3*-1.6-3.9Ref
3.0*-2.4-6.1*Ref
3.4-4.3-11.5*Ref
ClassofHospitalAcademiccentreCommunity>100bedsCommunity<100bedsNursingstation
3.5*0.5Ref2.0
14.1*0.5Ref-2.3*
22.2*0.3Ref-2.3
21.8*-1.0Ref-5.5
32.6*-1.6Ref
-13.5*LandingsiteatsendingfacilityAthospital,nolandescortAthospital,landescortLocalairport
Ref-2.0-4.5*
Ref-3.7*-4.3*
Ref-2.9-5.4*
Ref-4.1-7.3*
Ref-3.4-5.8*
LandingsiteattraumacentreAthospital,nolandescortAthospital,landescortLocalairport
Ref1.5*3.0
Ref2.0*6.7*
Ref2.2*6.1*
Ref3.4*9.8*
Ref1.416.0*
TraumacentrevolumeHighesttertileMiddletertileLowesttertile
Ref2.0*-1.0
Ref1.80.0
Ref3.9*-0.8
Ref5.0*-1.4
Ref5.6*-3.4
LevelofcarePrimarycareAdvancedcareCriticalcare
Ref1.50.5
Ref6.64.4
Ref15.8*10.3*
Ref18.2*11.9*
Ref22.1*14.8*
TypeofaircraftRotor-wingFixed-wing
5.0*Ref
2.3*Ref
-5.0*Ref
-16.6*Ref
-25.8*Ref
31
Coefficient estimates are reported as change to time interval in minutes Ref=reference, *p-value<0.05 Table 8: Results of quantile regression model for Interval 4 (Time from departing patient bedside to arrival back at aircraft) Variable
10th
30th
Quantile50th
70th
90th
Mechanicallyventilated 3.0* 3.5* 4.0* 3.0* 7.0*ClassofHospitalAcademiccentreCommunity>100bedsCommunity<100bedsNursingstation
0.51.5*Ref0.5
3.1*2.3*Ref-4.0*
5.1*2.0*Ref
-10.0*
7.5*2.0*Ref
-13.0*
11.6*0.0Ref
-16.0*LandingsiteatsendingfacilityAthospital,nolandescortAthospital,landescortLocalairport
Ref0.50.5
Ref0.32.3*
Ref1.04.0*
Ref1.05.0*
Ref4.0*7.0*
LandingsiteattraumacentreAthospital,nolandescortAthospital,landescortLocalairport
Ref0.01.5
Ref0.32.7*
Ref1.0*4.0*
Ref1.0*3.0*
Ref1.0-1.0
TraumacentrevolumeHighesttertileMiddletertileLowesttertile
Ref-0.50.5
Ref0.80.3
Ref1.0*0.0
Ref2.0*0.0
Ref4.0*3.0
LevelofcarePrimarycareAdvancedcareCriticalcare
Ref2.02.5*
Ref4.3*4.5*
Ref9.0*9.0*
Ref9.0*9.0*
Ref10.0*9.0*
TypeofaircraftRotor-wingFixed-wing
3.0*Ref
-2.5*Ref
-13.0*Ref
-18.0*Ref
-22.0*Ref
Coefficient estimates are reported as change to time interval in minutes Ref=reference, *p-value<0.05
32
Table 9: Results of quantile regression model for Interval 5 (Time from aircraft arrival at receiving centre to paramedic handover to trauma team) Variable
10th
30th
Quantile50th
70th
90th
Mechanicallyventilated 1.0 2.0* 2.3* 2.0* 2.3MechanismofinjuryMotorvehicleFallPenetratingOther
-1.0-1.00.0Ref
0.00.0-2.0*Ref
-0.80.0-2.5*Ref
-1.00.0-2.0Ref
-3.3*-1.3-5.7*Ref
Timeofday08:00-16:5917:00-23:5900:00—7:59
Ref0.0-1.0
Ref0.0-1.0*
Ref-1.5*-2.0*
Ref-2.0*-2.0*
Ref-3.7*-3.3*
ClassofHospitalAcademiccentreCommunity>100bedsCommunity<100bedsNursingstation
4.3*0.0Ref4.0*
7.0*0.0Ref-1.0
9.9*0.3Ref-1.8
9.0*1.0Ref-3.0
5.62.7*Ref-1.7
LandingsiteattraumacentreAthospital,nolandescortAthospital,landescortLocalairport
Ref3.0*14.0*
Ref4.0*20.0*
Ref4.5*24.5*
Ref5.0*31.0*
Ref5.3*54.0*
TraumacentrevolumeHighesttertileMiddletertileLowesttertile
Ref0.00.0
Ref1.0*-2.0*
Ref2.5*0.5
Ref4.0*0.0
Ref4.7*0.3
LevelofcarePrimarycareAdvancedcareCriticalcare
Ref7.0*8.0*
Ref18.0*19.0*
Ref11.5*13.0*
Ref8.0*10.0*
Ref4.76.3
TypeofaircraftRotor-wingFixed-wing
-5.0*Ref
-18.0*Ref
-22.3*Ref
-27.0*Ref
-35.3*Ref
Coefficient estimates are reported as change to time interval in minutes Ref=reference, *p-value<0.05
33
2.3 Discussion
This objective evaluated risk factors for delays during interfacility air transport. There
were three key findings identified. First, the use of rotor-wing aircraft and hospital-based
helipads was associated with substantially lower transport times. Second, transports from
academic centres were associated with longer transport times compared to those that
originated at community hospitals or nursing stations. Third, interfacility transport times
are heavily skewed and delays disproportionately affect longer patient transports.
Our study demonstrates the large variability of transport times in our air ambulance
system. There were heavily skewed distributions across all transport time intervals with
the in-hospital time interval being the longest. The presence of heavily skewed
distributions suggests the potential for improvement to reduce the variation across
interfacility transports. This is in keeping with a previous study from Ontario that found
wide variability of time to complete interfacility transports.4
We used quantile regression modeling to explore the skewed tail end of transport times to
better assess risk factors for delay. Previous studies in a prehospital setting have
demonstrated the benefits of using quantile regression modeling over OLS or linear
regression. 53,54 The flexibility of quantile regression makes it well suited for the non-
uniformity, skewed or asymmetrical distribution of data that would violate the
assumptions of OLS regression techniques.52 Our results demonstrate that the association
of delays due to patient, paramedic and institutional factors are not uniform, but worse at
34
the tail end of transport intervals. Put another way, delays during interfacility transport
disproportionally affect patients who already have longer transport times.
Our findings expand on the limited understanding of interfacility transport delays by
identifying patient, paramedic and institutional risk factors associated with delays. We
found that being transported by a critical care or advanced care paramedic was associated
with shorter times from the call being accepted to wheels up time of the aircraft. At the
90th percentile, the time benefit of an advanced or critical care medic in reference to a
primary care crew was 24.1 and 28.2 minutes respectively. A small study examining
delays to interfacility transport to two Canadian trauma centres by air ambulance
identified refuelling, mechanical and weather issues as being frequent causes of delays to
launching an aircraft.4 Our study suggests that we may be able to expedite launching of
an aircraft by ensuring we have advanced and critical care crews transporting our
severely injured patients. Furthermore, up-training paramedics to a critical care level
across the organization could also reduce the time to launch an aircraft as critical care
paramedics had shorter transport times compared to advanced care crews.
Our study identified the type of aircraft landing site being associated with interfacility
transport delays. Many sending facilities in our trauma system do not have a helipad on
site or require the aircraft to land at a local airport away from the hospital and then have a
local land EMS crew pick them up from the airport and bring them to the sending facility.
This effort requires coordination from our air ambulance service as well as local EMS to
ensure an ambulance is available when the aircraft lands. Furthermore, the use of rotor-
35
wing aircraft, even when controlling for landing sites was consistently faster than use of a
fixed-wing aircraft for every transport time interval measured in our study. Advocating
for hospital-based helipads and optimizing coordination between our air ambulance
provider and local land EMS when a land escort is required may help reduce interfacility
transport times.
Another finding of our study was that patients being transferred from a nursing station
had shorter in-hospital times compared to patients being transported from an academic
centre. This relationship may be partially explained by the higher level resources
available at academic centres. Gomez et al. demonstrated that patients being transported
from “resource rich” centres, defined by the presence of surgical specialties, CT scanners
and intensive care capabilities, are associated with longer emergency department length
of stays compared to centres lacking these resources.50 Furthermore, previous work has
identified patients undergoing diagnostic imaging at the sending facility an important
cause of in-hospital and patient contact delays.4 In this study, over 14% of in-hospital
delays were a result of patients undergoing further diagnostic imaging after the arrival of
transporting paramedics.4 Nursing stations by comparison have very limited resources,
often with no access to blood products, x-rays or CT scans.55 Since there is less than can
be done for patients at nursing stations, it may propagate a mentality of “load and go” as
little can be done to stabilize patients in these settings. Improved communication
between the sending and receiving physicians to ensure only essential diagnostic imaging
and medically necessary procedures are completed prior to transport may help reduce
interfacility transport times.
36
Patient characteristics mostly influenced the in-hospital time interval in our study. The
need for mechanical ventilation prolonged in-hospital times by over 37 minutes at the
90th percentile. Intubated patient require infusions for sedation and ventilator
manipulation, which will naturally take time to accomplish. Furthermore, hypoxic
patients may have required interventions such as intubation, placement of airways or
insertion of chest tubes to optimize their oxygenation prior to air transport, resulting in
longer in-hospital times. The hypobaric effects of air transport often make it necessary to
place chest tubes before insertion and improve oxygenation prior to transport as it is
difficult to address hypoxia at altitude.56,57
From a patient perspective, a clinically meaningful delay that can result in increased
mortality may be as short as 15-30 minutes.58,59 Therefore, based on our results, the
decision to send an advanced care or critical care paramedic crew, or the availability of
rotor-wing aircraft or the placement of a hospital helipad could be a matter of life or
death.
Our study has several potential limitations. Paramedics entered the times used to
calculate the transport intervals manually. These transport times were recorded either in
real time during the patient transport or retrospectively after the transport was completed,
leaving the potential for measurement error. Additionally, our study was unable to
measure the time a patient spent at a sending facility prior to the request to transfer the
patient. The time to make the decision to transport a critically injured patient plays an
important role in overall delays to interfacility transfer and warrants future study.
37
Furthermore, as our study was limited to the air ambulance database, we were unable to
directly assess the impact of longer transport times on patient outcomes. We can,
however, infer from other studies that these delays experienced by our patients would be
associated with worse outcomes.58,59 Finally, the use of an air ambulance database
precluded our ability to include variables such as injury severity scores and comorbidity
indices commonly presented in trauma literature. We hope that future relationships
between our air ambulance service and provincial trauma registries may allow for this
sharing of data to enrich this understanding.
In summary, we have demonstrated that ventilator dependence, paramedic level of care,
classification of sending facility and helipad availability are associated with delays to
interfacility transport of injured patients. Efforts can be made at both the air ambulance
and institutional levels to ensure timely and efficient transports.
38
3. IDENTIFIED CAUSES OF DELAY DURING INTERFACILITY TRANSPORT
3.1 Methods
3.1.1 Primary Aim
The primary aim of this objective was to identify specific causes of modifiable delays
during the interfacility transport process for injured patients transported to a trauma
centre by air ambulance in Ontario.
3.1.2 Secondary Aim
The secondary aim of this objective was to estimate the attributable time associated with
delays identified during interfacility transport of injured patients transported to a trauma
centre by air ambulance in Ontario.
3.1.3 Study Design
This study was a retrospective cohort study of injured patients undergoing interfacility
transfer to a trauma centre who were transported by air ambulance in Ontario. Ethics
approval for this study was obtained from the research ethics board at the University of
Toronto.
3.1.4 Data Sources
Data were derived from a database of ePCRs at Ornge which includes all patients
transported by Ornge paramedics. The ePCR includes data pertaining to patient
demographics, reason for transfer, vital signs, medications given and interventions
39
performed. Paramedics also complete a narrative text of the transport and could assign
standardized delay codes to the call. In addition, there are various times associated with
each transfer that were entered by paramedics and collected in the ePCR (Figure 2).
These include the time of dispatch, the time the crew leaves their base, the time they
arrive at sending facility landing site, the times they arrive and depart from patient
bedside, the time they depart from sending facility landing site, the time they arrive at the
receiving trauma centre landing site and the time they handover to the trauma team.
Figure 7: Measurement of time intervals and grouping of delays during interfacility transport
3.1.5 Study Population
The study population included all emergent interfacility transfers for injured patients
transported to a trauma centre by either fixed or rotor-wing resources between January 1,
2014 and December 31, 2016. Patients with a primary medical reason for transfer, those
who were transported to a non-trauma centre or were transported by a land ambulance
were excluded from the study.
Callaccepted
Crewleavesbase
Arriveatlandingsite/
hospital
Arriveatpatientbedside
Departpatientbedside
Departlandingsite/
hospital
Arriveattraumacentre
Handovertotraumateam
Time-to-sendingdelays In-hospitaldelays Time-to-receivingdelays
Flighttime Flighttime
OverallTime
40
3.1.6 Identification and classification of delays
The secondary objective of this study was to identify the frequency and causes of delays
during interfacility transport. In addition, we evaluated the total attributable time for each
delay.
Using the times captured in ePCR, we created three time intervals for each patient
transport. These times included: i) the time-to-sending interval, which was measured
from the time of dispatch to arrival to patient bedside; ii) the in-hospital time interval,
defined by the time from paramedic arrival to patient bedside to departure with patient;
and iii) the time-to-receiving/handover interval, which was measured from the time of
departure with patient to handover to the trauma team (Figure 1). Since we were
interested in the modifiable aspect of interfacility transport, the flight times for both the
time-to-sending and time-to-receiving/handover intervals were not included in the
calculation of these times.
Given the large number of records and the need for manual review of the ePCR, we used
a screening process to identify patients that were likely to have experienced a delay
during their interfacility transport. The screening process involved using three
approaches. First, we identified charts for review if there was a standardized delay code
entered by paramedics. These delay codes are pre-determined and can be added by
paramedics to the patient care record at any point if they deem appropriate. Second, the
free-text narrative field of each patient record was searched for the terms “delay”
“prolong” “wait” or “duty out”, including common misspellings of these words. Any
41
patient record containing these terms was then flagged for review. Lastly, all patient
records that had transport times exclusive of flight times above the 75th percentile for
overall time to complete interfacility transfer, time-to-sending-hospital, in-hospital or
time-to-receiving/handover (excluding flight times) were also manually reviewed.
Any patient identified through any one of these screening methods had their entire Ornge
electronic patient care record manually reviewed to search for causes of the delay. In the
case that a patient was positively screened but no reason for delay was identified, no
delay reason was recorded for that patient. Likewise, if a patient had a delay code
entered by the paramedics but there was nothing to substantiate the reason for delay, no
delay reason was recorded. A delay was defined as anything the paramedics identified in
their charting that hindered or postponed transport. Identified causes of delay were then
coded and categorized into time-to-sending, in-hospital and time-to-receiving/handover
delays. The frequency of each type of delay was recorded. A 10% random sample of
patient records that were not identified through our search strategy were also manually
reviewed to validate our screening methods and to inform if these search parameters
should be extended. Our screening approached proved to be effective, with no additional
incidents or causes of delay identified in the sample.
42
3.1.7 Attributable delay and length of delay analysis
Having categorized causes of delay, we then sought to evaluate the mean time
attributable to each cause of delay. Mean times for time-to-sending, in-hospital and time-
to-receiving/handover were calculated for each sending facility using records where no
delay had been identified. Similarly, times for the interval where a delay was identified
were determined. The difference between the two was the “attributable time of delay” for
that type of delay (Figure 3). We then calculated the “total attributable time” for each
delay type as the product of its duration and its frequency such that it represents the
cumulative time (in minutes) that a delay was responsible for. This was done for each
sending facility, and then summed across all facilities. Ultimately, the average length of
delay was calculated by dividing the total attributable time by the frequency of delay
type.
Figure 8: Measurement of attributable time of delay
Mean in-hospital time for Hospital A
30 minutes
In-hospital time for Delay Z that occurred in Hospital A
40 minutes
Attributable time of delay
10 minutes
43
3.2 Results
3.2.1 Baseline characteristics
There were 932 injured patients emergently transported by air ambulance from a
community hospital to a trauma centre over the 3-year study period. Our screening
method identified 552 (59%) patients whom required manual review of their electronic
patient records and from which 329 (35%) patients were identified as having at least one
delay during their transport. There were a total of 458 unique causes of delay that were
identified. Of the 329 patients who experienced a delay during interfacility transport,
there were 234 (71%) patients with a single delay during their transport, 67 (20%)
patients with two delays, 24 (7%) patients with three delays and 2 (1%) each with four
and five delays, respectively.
3.2.2 Frequency and total attributable time of delays
The most frequent cause of delays to sending facility were refuelling (38%), waiting for
land EMS escort (25%) and weather (12%) (Figure 6). The most common in-hospital
delays included waiting for documentation (32%), delay to intubate (15%), medically
unstable patient (13%) and waiting for diagnostic imaging (DI) (12%). The most
frequent delays to receiving/handover included waiting for land EMS escort (31%),
trauma team not assembled (24%) and weather (17%).
44
Figure 9: Frequency of identified causes of delay
The delays to sending facility with the highest total attributable time were refuelling
(1249 minutes), waiting for land EMS (898 minutes) and weather (478 minutes) (Figure
7). The in-hospital delays with the highest total attributable time included delay to
intubate (1226 minutes), delays for diagnostic imaging (911 minutes), delays waiting for
documentation (801 minutes) and medically unstable (693 minutes). The delays to
receiving/handover with the highest attributable time were trauma team not assembled
(153 minutes), waiting for land EMS escort (115 minutes) and weather (113 minutes).
We examined the individual cases involved in delays due to the trauma team not being
assembled and found that the mean delay is significantly skewed by two patients. These
0
20
40
60
80
100
120
Refuel WaitingforlandEMSescort
Weather Mechanical Crewchange Triage Cancelledandcalledback
Restockingaircraft
Dispatchissues Other
0
10
20
30
40
50
60
0
2
4
6
8
10
WaitingforlandEMSescort
Traumateamnotassembled
Weather Equipmentissues Refuel Mechanical Other
Delaystosen
ding
(Cou
nt)
Inhospitaldelays
(Cou
nt)
Delaystoreceiving/
hand
over(C
ount)
45
two patients both sustained isolated head injuries and had a 100-minute and 40-minute
delay due to handing over to the neurosurgical team at the receiving trauma centre. All
other delays waiting for the trauma team to assemble were less than 10 minutes.
Figure 10: Pareto charts of total attributable time (in min) and cumulative percent for each cause of delay
3.2.3 Average length of delay
Delays to sending facility with the highest average length of delay were dispatch issues
(23 minutes), restocking aircraft (21 minutes) and crew change (20 minutes) (Table 8).
In-hospital delays with the longest average length of delay included stabilization of
patient in the operating room (77 minutes), chest tube insertion (53 minutes), multi-
casualty incident (50 minutes), delay to intubate (49 minutes) and delays for diagnostic
Delaystosen
ding
Time(m
in)
Inhospitaldelays
Tim
e(m
in)
Delaystoreceiving/hando
ver
Time(m
in)
0%
20%
40%
60%
80%
100%
0
200
400
600
800
1000
1200
1400
Refuel WaitingforlandEMSescort
Weather Crewchange Mechanical Restockingaircraft
Cancelledandcalledback
Dispatchissues Triage Other
0%
20%
40%
60%
80%
100%
0
200
400
600
800
1000
1200
1400
0%
20%
40%
60%
80%
100%
0
50
100
150
200
Traumateamnotassembled
WaitingforlandEMSescort
Weather Equipmentissues Refuel Mechanical Other
Cumulativepe
rcen
tCu
mulativepe
rcen
tCu
mulativepe
rcen
t
46
imaging (46 minutes). Delays to receiving/handover with the highest average length of
delay were weather (23 minutes), trauma team not assembled (22 minutes) and
equipment issues (15 minutes).
Table 10: Mean length of delay in minutes for each identified cause of delay Delay Mean delay in min (SD) Delay to sending facility Dispatch issues Restocking aircraft Crew change Cancelled and called back Weather Mechanical Waiting for land EMS escort Refuel Triage Other
23.5 (42.7) 21.2 (18.5) 20.6 (19.4) 16.2 (12.8) 15.4 (37.3) 14.3 (29.1) 13.6 (23.0) 12.4 (22.8) 7.7 (13.7) 4.8 (13.8)
In-hospital delays Stabilization in operating room Other Delay for chest tube Multi casualty incident Delay to intubate Delay for diagnostic imaging Equipment issues Medically unstable Confirming disposition/receiving Delay for cast/splint Waiting for blood products Waiting for documentation
76.7 (69.6) 54.0 (55.2) 53.4 (52.8) 50.0 (46.7) 49.0 (37.6) 45.6 (41.3) 43.4 (38.9) 31.5 (36.5) 28.8 (20.4) 23.7 (50.2) 17.2 (19.9) 15.1 (29.0)
Delay to sending facility Weather Trauma team not assembled Equipment issues Waiting for land EMS escort Refuel Mechanical Other
22.6 (17.3) 21.9 (43.3) 15.5 (30.7) 12.8 (13.9) 5.5 (2.1) 0.5 (0.5) 0.5 (0.5)
SD = standard deviation
47
3.3 Discussion
In this study, we identified multiple modifiable causes of delay during the process of
interfacility transport of injured patients transported by air ambulance. There are three
key findings in our study. First, it is important to assess both the frequency and duration
of delay, as many high frequency delays were short in duration. Second, patients who
had invasive procedures (ie. intubation, chest tube insertion) and advanced DI at the
sending facility experienced the longest delays. Third, improving communication
between local EMS and air ambulance can reduce delays incurred by waiting for land
EMS escorts.
Our findings on in-hospital delays highlight the importance of understanding both the
frequency and duration of delays. For example, the most common delay experienced in-
hospital was waiting for documentation and although was responsible for 32% of all in-
hospital delays it had the lowest impact on length of delay; resulting in an average delay
of 15 minutes. Likewise, both the stabilization of a patient in the operating room and
mass-casualty incidents were some of the least frequent delays encountered in hospital
however had significant impacts on time resulting in, respectively, an average delay of 77
minutes and 50 minutes. Pareto charts provide a helpful visual analysis of this
relationship between the sum total and cumulative impact of delays (Figure 7). This
approach can be useful to understand where to put efforts into improving the trauma
transport system. For example, efforts to reduce frequent yet smaller delays such as
waiting for documentation could help our overall trauma system efficiency. On the other
48
hand, rare delays such as mass casualty incidents, while significant on a patient level are
a poor focus for systemic improvements.
Another finding in our study was that invasive procedures done at a non-trauma centre
result in some of the longest delays to interfacility transfer. If a patient needed to be
intubated once the flight paramedics arrived (15% of all in-hospital delays), it increased
the in-hospital time by 49 minutes. Likewise chest tube insertion resulted in an average
delay of 53 minutes. There are many sending facilities in the trauma system that have a
low volume of acutely injured patients which may be a contributing factor to the resultant
delay these procedures cause as physicians who are unfamiliar with technique or
equipment available in these high-risk situations may be uncomfortable proceeding
without the backup of another physician or the flight paramedics. Furthermore, it is
possible that patients may continue to deteriorate or previously unidentified injuries are
recognized, such as worsening pneumothorax or hemothorax resulting in a delay to
initiative these procedures. Another cause related to delays from procedures may be from
a lack of familiarity with the physiologic changes and hypobaric environments associated
with air transport.56 Sending physicians may be unfamiliar with the need to place chest
tubes for minimal pneumothoraces or the challenges associated with intubation in an
aircraft, which could result in a delay to initiate these procedures until the paramedic
crew arrives. Communication between the sending physician and receiving trauma team
leader or transport medicine physician could help optimize patients for transport prior to
arrival of the transporting paramedics and reduce these in-hospital delays. The use of a
checklist to optimize patients prior to air transport has previously been suggested.60
49
Additionally, airway management in injured patients is inherently challenging and may
also precipitate a delay for appropriate preparation and execution.10 Another significant
cause of in-hospital delay is waiting for DI. Delays due to DI accounted for 12% of all in-
hospital delays and resulted in an average delay of 46 minutes. One study found that
60% of all interfacility transfers that have CT scans imaging done at the sending facility
have at least one CT scan repeated at the trauma centre.11 Efforts to reduce delays caused
by diagnostic imaging may include a discussion between the sending and trauma
physicians to clarify the necessity of advanced DI prior to transport.
Our findings expand on the limited understanding of interfacility delays and serves to
better characterize modifiable delays at a systemic level. A small study examining delays
to interfacility transport to two Canadian trauma centres by air ambulance identified
refuelling, mechanical and weather issues as being frequent causes of delay to arriving at
sending facility.7 Our findings were consistent, yet we also identified a significant
number of transports that were delayed as a result of waiting for a land EMS escort.
Many sending facilities in our trauma system do not have a helipad on site or require the
aircraft to land at a local airport away from the hospital and then have a local land EMS
crew pick them up from the airport and bring them to the sending facility. This effort
requires coordination from our air ambulance services as well as local EMS systems to
ensure an ambulance is available when the aircraft lands. We found there is often a
breakdown of this coordination resulting in the flight paramedics waiting an average of
14 minutes for a land EMS escort to arrive. Furthermore, we found that dispatching
50
issues, having to restock aircraft and delays surrounding crew changes although occurring
less frequently, had the greatest impact as measured by minutes per delay.
Overall, delays to receiving trauma centre and handover were relatively uncommon. All
causes of delay to receiving accounted for only 29 of all 458 delays identified the study.
As discussed above, like many of our sending facilities, some of our receiving trauma
centres do not have a rooftop helipad and require a land EMS escort from the landing site
to the trauma bay. Waiting for a land EMS escort was the most common cause of delay
to receiving/handover, resulting in 31% of all handover delays and had an average delay
of 13 minutes. Once again, improved communication between air ambulance and land
EMS services may improve coordination and lessen the impact of this delay.
It should be noted that almost 30% of patients identified as having a delay during
interfacility transport experienced more than one delay. This is significant because
having even two or three shorter delays will lead to clinically significant total delay in
transfer. For example a patient who three of the most common but shortest delays; such
as refuelling, waiting for land EMS escort and delay to receiving documentation would
incur around 45 minutes of total delay time during their transport. That may be long
enough to cause patient harm due to delay to definitive care at a trauma centre.
This study is the largest of it’s kind to examine causes of delay to interfacility transport of
injured patients within our trauma system. It provides useful information for targeting
interventions that can reduce the frequency or impact of these delays.
51
There are several limitations to this objective that warrant discussion. This study relied
on delays that were identified by paramedics by either delay codes or written text
describing the delay that occurred. As such there are likely cases where a delay did occur
but no documentation was done and thus we would not have captured those delays in this
study. Additionally, paramedics may have been less likely to report causes of delay that
resulted from their actions. It was not feasible to obtain individual medical records from
each sending facility to assess the physician or nursing notes to see if they documented
any delays incurred on the paramedic side that we did not capture. However, our study
does hold face validity with previous work identifying causes of delay to interfacility
transfer.7 Another limitation to this study is the potential for measurement error in
calculating the attributable delay time and average time per delay. Delay times were
estimated using time stamps of a patient transport entered manually by paramedics,
something that may be done in real time or retrospectively after the patient is transported.
This approach could lead to either an overestimate or underestimate of time of delay,
however is unlikely to result in a significant bias in our results.
52
4. CONCLUSION
4.1 Directions for Future Research
The results of this study suggest several directions for future research. As noted above,
this study was limited to data available in an air ambulance database and thus in-hospital
outcomes, such as mortality could not be assessed. Data sharing agreements between
Ornge and a provincial health administrative database at the Institute for Clinical
Evaluative Sciences are underway. This will allow future studies to assess the impact of
interfacility transport delays on mortality, hospital length of stay, blood product usage
and other patient-centric outcomes.
Also noted in the previous section is the potential inability of our study to have identified
causes of delay from the perspective of the sending or receiving centres. By limiting our
methods to the paramedic patient record, we may have been unable to identify causes of
delay identified by the sending or receiving centres. A future study could reach out to
these centres for feedback or specifically collect causes of delay perceived by these
hospitals.
Futhermore, armed with the knowledge gained from this study in identifying risk factors
and causes of delay during interfacility transport, future endeavours to reduce these
delays can be considered. Another study could assess the effectiveness of these strategies
on reducing the frequency or duration of identified delays.
53
4.2 Conclusion of thesis
This thesis of injured patients transported by air ambulance to a trauma centre was able to
identify both risk factors for and specific modifiable causes of delay that occur during the
interfacility transport process. This thesis demonstrated that ventilator dependence,
paramedic level of care, classification of sending facility and helipad availability are
associated with delays to interfacility transport of injured patients. Furthermore, efforts
to improve communication between air ambulance service and local land EMS services
should be made in an effort to reduce the impact of delays to both sending a receiving
hospitals caused by a lack of land EMS escort. Patients requiring intubation or chest
tubes experience delays of more then 50 minutes. Ensuring physicians are comfortable
with and equipment is readily available for these life saving interventions may help
expedite transport. Patients undergoing advanced diagnostic imaging after the decision to
transfer had been made should ensure the timing does not affect the patient’s transport
and deferral of further DI until arrival at the trauma centre should be considered. Future
efforts can be made at both the air ambulance and institutional levels to ensure timely and
efficient transports.
54
5. ACKNOWLEDGEMENTS
I would like to acknowledge the following people and organizations for their support in
the development of this thesis.
• Thesis committee: Dr. Avery Nathens (thesis supervisor), Dr. Barbara Haas, Dr.
Homer Tien, Refik Saskin
• Queen Elizabeth II/Sunnybrook Prehospital Care Program Graduate Scholarships
in Science and Technology at the University of Toronto
• Canadian Association of Emergency Physicians
• Institute for Health Policy, Management & Evaluation (IHPME)
• Clinical Epidemiology and Health Care Research program at IHPME
• My wife (Julia) and dog (Oliver)
55
6. REFERENCES
1. Piontek FA, Coscia R, Marselle CS, Korn RL, Zarling EJ, American College of Surgeons. Impact of American College of Surgeons verification on trauma outcomes. J Trauma 2003;54(6):1041–6–discussion1046–7.
2. Demetriades D, Martin M, Salim A, et al. Relationship between American College of Surgeons trauma center designation and mortality in patients with severe trauma (injury severity score > 15). J Am Coll Surg 2006;202(2):212–5–quizA45.
3. MacKenzie EJ, Rivara FP, Jurkovich GJ, et al. A national evaluation of the effect of trauma-center care on mortality. N Engl J Med 2006;354(4):366–78.
4. Nolan B, Tien H, Sawadsky B, et al. Comparison of Helicopter Emergency Medical Services Transport Types and Delays on Patient Outcomes at Two Level I Trauma Centers. Prehosp Emerg Care 2017;21(3):327–33.
5. Canada S. Leading causes of death [Internet]. 2011 [cited 2018 Dec 20];Available from: https://www.statcan.gc.ca/pub/82-625-x/2014001/article/11896/c-g/c-g01-eng.htm
6. Canada S. Injuries in Canada: Insights from the Canadian community health survey [Internet]. httpswww.statcan.gc.capub--xarticle-eng.htm. 2011 [cited 2018 Dec 20];Available from: https://www.statcan.gc.ca/pub/82-624-x/2011001/article/11506-eng.htm
7. Parachute. The cost of injury in Canada [Internet]. httpwww.parachutecanada.orgdownloadsresearchCostofInjury-.pdf. 2015 [cited 2018 Dec 20];Available from: http://www.parachutecanada.org/downloads/research/Cost_of_Injury-2015.pdf
8. Cales RH, Trunkey DD. Preventable trauma deaths. A review of trauma care systems development. JAMA 1985;254(8):1059–63.
9. Waller JA, Curran R, Noyes F. Traffic Deaths. A preliminary study of urban and rural fatalities in Californi. Calif Med 1964;101(4):272–6.
10. Sampalis JS, Denis R, Lavoie A, et al. Trauma care regionalization: a process-outcome evaluation. J Trauma 1999;46(4):565–79–discussion579–81.
11. Newgard CD, Schmicker RH, Hedges JR, et al. Emergency medical services intervals and survival in trauma: assessment of the “golden hour” in a North American prospective cohort. Ann Emerg Med 2010;55(3):235–246.e4.
12. Buchanan IM, Coates A, Sne N. Does Mode of Transport Confer a Mortality Benefit in Trauma Patients? Characteristics and Outcomes at an Ontario Lead Trauma Hospital. CJEM 2016;:1–7.
56
13. McCoy CE, Menchine M, Sampson S, Anderson C, Kahn C. Emergency medical services out-of-hospital scene and transport times and their association with mortality in trauma patients presenting to an urban Level I trauma center. Ann Emerg Med 2013;61(2):167–74.
14. Committee on Trauma ACOS. Resources for optimal care of the injured patient [Internet]. httpswww.facs.orgmediafilesqualityprogramstraumavrcresourcesresourcesforoptimalcare.ashx. 2014 [cited 2019 Feb 2];Available from: https://www.facs.org/~/media/files/quality%20programs/trauma/vrc%20resources/resources%20for%20optimal%20care.ashx
15. Committee on Trauma ACOS. Optimal hospital resources for care of the seriously injured. Bulletin of American College of Surgeons 1976;(61):15–22.
16. Celso B, Tepas J, Langland-Orban B, et al. A systematic review and meta-analysis comparing outcome of severely injured patients treated in trauma centers following the establishment of trauma systems. J Trauma 2006;60(2):371–8–discussion378.
17. Lerner EB, Moscati RM. The golden hour: scientific fact or medical "urban legend"? Acad Emerg Med 2001;8(7):758–60.
18. Newgard CD, Meier EN, Bulger EM, et al. Revisiting the “Golden Hour”: An Evaluation of Out-of-Hospital Time in Shock and Traumatic Brain Injury. Ann Emerg Med 2015;66(1):30–3.
19. Harmsen AMK, Giannakopoulos GF, Moerbeek PR, Jansma EP, Bonjer HJ, Bloemers FW. The influence of prehospital time on trauma patients outcome: a systematic review. Injury 2015;46(4):602–9.
20. Wigman LD, van Lieshout EMM, de Ronde G, Patka P, Schipper IB. Trauma-related dispatch criteria for Helicopter Emergency Medical Services in Europe. Injury 2011;42(5):525–33.
21. Thomas SH, Brown KM, Oliver ZJ, et al. An Evidence-based Guideline for the air medical transportation of prehospital trauma patients. Prehosp Emerg Care 2014;18 Suppl 1:35–44.
22. Vercruysse GA, Friese RS, Khalil M, et al. Overuse of helicopter transport in the minimally injured: A health care system problem that should be corrected. J Trauma Acute Care Surg 2015;78(3):510–5.
23. Cheung BH, Delgado MK, Staudenmayer KL. Patient and trauma center characteristics associated with helicopter emergency medical services transport for patients with minor injuries in the United States. Acad Emerg Med 2014;21(11):1232–9.
24. Andruszkow H, Hildebrand F, Lefering R, Pape H-C, Hoffmann R, Schweigkofler
57
U. Ten years of helicopter emergency medical services in Germany: do we still need the helicopter rescue in multiple traumatised patients? Injury 2014;45 Suppl 3:S53–8.
25. Doucet J, Bulger E, Sanddal N, Fallat M, Bromberg W, Gestring M. Appropriate use of Helicopter Emergency Medical Services for transport of trauma patients. Journal of Trauma and Acute Care Surgery 2013;75(4):734–41.
26. Center for Disease Control, Prevention. Guidelines for field triage of injured patients. MMWR Morb Mortal Wkly Rep 2009;58:2–12.
27. Brown JB, Stassen NA, Bankey PE, Sangosanya AT, Cheng JD, Gestring ML. Helicopters and the civilian trauma system: national utilization patterns demonstrate improved outcomes after traumatic injury. J Trauma 2010;69(5):1030–4–discussion1034–6.
28. Sullivent EE, Faul M, Wald MM. Reduced mortality in injured adults transported by helicopter emergency medical services. Prehosp Emerg Care 2011;15(3):295–302.
29. Stewart KE, Cowan LD, Thompson DM, Sacra JC, Albrecht R. Association of direct helicopter versus ground transport and in-hospital mortality in trauma patients: a propensity score analysis. Acad Emerg Med 2011;18(11):1208–16.
30. Ringburg AN, Thomas SH, Steyerberg EW, van Lieshout EMM, Patka P, Schipper IB. Lives saved by helicopter emergency medical services: an overview of literature. Air Med J 2009;28(6):298–302.
31. Cunningham P, Rutledge R, Baker CC, Clancy TV. A comparison of the association of helicopter and ground ambulance transport with the outcome of injury in trauma patients transported from the scene. J Trauma 1997;43(6):940–6.
32. Shatney CH, Homan SJ, Sherck JP, Ho C-C. The utility of helicopter transport of trauma patients from the injury scene in an urban trauma system. J Trauma 2002;53(5):817–22.
33. Eckstein M, Jantos T, Kelly N, Cardillo A. Helicopter transport of pediatric trauma patients in an urban emergency medical services system: a critical analysis. J Trauma 2002;53(2):340–4.
34. Bledsoe BE, Wesley AK, Eckstein M, Dunn TM, O'Keefe MF. Helicopter scene transport of trauma patients with nonlife-threatening injuries: a meta-analysis. J Trauma 2006;60(6):1257–65–discussion1265–6.
35. Delgado MK, Staudenmayer KL, Wang NE, et al. Cost-effectiveness of helicopter versus ground emergency medical services for trauma scene transport in the United States. Ann Emerg Med 2013;62(4):351–364.e19.
58
36. Bledsoe BE, Smith MG. Medical helicopter accidents in the United States: a 10-year review. J Trauma 2004;56(6):1325–8–discussion1328–9.
37. Gomez D, Haas B, Doumouras AG, et al. A population-based analysis of the discrepancy between potential and realized access to trauma center care. Ann Surg 2013;257(1):160–5.
38. Health OMO, Care LT. Field trauma triage and air ambulance utilization [Internet]. httpwww.health.gov.on.caenproprogramsehsdocsehstrainingblltnen.pdf. 2014 [cited 2018 Dec 20];Available from: http://www.health.gov.on.ca/en/pro/programs/ehs/docs/ehs_training_blltn113_en.pdf
39. Gomez D, Berube M, Xiong W, et al. Identifying targets for potential interventions to reduce rural trauma deaths: a population-based analysis. J Trauma 2010;69(3):633–9.
40. Newgard CD, Rudser K, Hedges JR, et al. A critical assessment of the out-of-hospital trauma triage guidelines for physiologic abnormality. J Trauma 2010;68(2):452–62.
41. Brown JB, Forsythe RM, Stassen NA, Gestring ML. The National Trauma Triage Protocol: can this tool predict which patients with trauma will benefit from helicopter transport? J Trauma Acute Care Surg 2012;73(2):319–25.
42. Lehmann RK, Arthurs ZM, Cuadrado DG, Casey LE, Beekley AC, Martin MJ. Trauma team activation: simplified criteria safely reduces overtriage. Am J Surg 2007;193(5):630–4–discussion634–5.
43. van Rein EAJ, Houwert RM, Gunning AC, Lichtveld RA, Leenen LPH, van Heijl M. Accuracy of prehospital triage protocols in selecting severely injured patients: A systematic review. J Trauma Acute Care Surg 2017;83(2):328–39.
44. Ciesla DJ, Pracht EE, Tepas JJ, et al. Measuring trauma system performance: Right patient, right place-Mission accomplished? J Trauma Acute Care Surg 2015;79(2):263–8.
45. Staudenmayer KL, Hsia RY, Mann NC, Spain DA, Newgard CD. Triage of elderly trauma patients: a population-based perspective. J Am Coll Surg 2013;217(4):569–76.
46. Haas B, Stukel TA, Gomez D, et al. The mortality benefit of direct trauma center transport in a regional trauma system: a population-based analysis. J Trauma Acute Care Surg 2012;72(6):1510–5–discussion1515–7.
47. Nolan B, Ackery A, Nathens A, Sawadsky B, Tien H. Canceled to Be Called Back: A Retrospective Cohort Study of Canceled Helicopter Emergency Medical Service Scene Calls That Are Later Transferred to a Trauma Center. Air Med J
59
2018;37(2):108–14.
48. Giannakopoulos GF, Bloemers FW, Lubbers WD, et al. Criteria for cancelling helicopter emergency medical services (HEMS) dispatches. Emerg Med J 2012;29(7):582–6.
49. Tignanelli CJ, Vander Kolk WE, Mikhail JN, Delano MJ, Hemmila MR. Non-compliance with ACS-COT recommended criteria for full trauma team activation is associated with undertriage deaths. J Trauma Acute Care Surg 2017;84(2):287–94.
50. Gomez D, Haas B, De Mestral C, et al. Institutional and provider factors impeding access to trauma center care: an analysis of transfer practices in a regional trauma system. J Trauma Acute Care Surg 2012;73(5):1288–93.
51. Gomez D, Haas B, Larsen K, et al. A novel methodology to characterize interfacility transfer strategies in a trauma transfer network. J Trauma Acute Care Surg 2016;81(4):658–65.
52. Austin PC, Schull MJ. Quantile regression: a statistical tool for out-of-hospital research. Acad Emerg Med 2003;10(7):789–97.
53. Schull MJ, Morrison LJ, Vermeulen M, Redelmeier DA. Emergency department overcrowding and ambulance transport delays for patients with chest pain. CMAJ 2003;168(3):277–83.
54. Do YK, Foo K, Ng YY, Ong MEH. A quantile regression analysis of ambulance response time. Prehosp Emerg Care 2013;17(2):170–6.
55. Nolan B, Ackery A, Mamakwa S, et al. Care of the Injured Patients at Nursing Stations and during Air Medical Transport. Air Med J 2018;37(3):161–4.
56. Grocott M, Montgomery H, Vercueil A. High-altitude physiology and pathophysiology: implications and relevance for intensive care medicine. Crit Care 2007;11(1):203.
57. Braude D, Tutera D, Tawil I, Pirkl G. Air transport of patients with pneumothorax: is tube thoracostomy required before flight? Air Med J 2014;33(4):152–6.
58. Harrington DT, Connolly M, Biffl WL, Majercik SD, Cioffi WG. Transfer times to definitive care facilities are too long: a consequence of an immature trauma system. Ann Surg 2005;241(6):961–6–discussion966–8.
59. Pham H, Puckett Y, Dissanaike S. Faster on-scene times associated with decreased mortality in Helicopter Emergency Medical Services (HEMS) transported trauma patients. Trauma Surg Acute Care Open 2017;2(1):e000122.
60. Lockwood J, Ackery A. Improving air medical transport of the trauma patient from
60
the ground. CJEM 2014;16(3):243–6.