Identifying causes of delay in interfacility transports of ... · Figure 1. Field Trauma Triage Guidelines (Ontario) Figure 2. Ontario Adult Trauma Centres and Referral Boundaries

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

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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


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


departing patient bedside to arrival back at aircraft) …………………... 31


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

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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

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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

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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


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*


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


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


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


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


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*


Ref1.5*3.0

Ref2.0*6.7*

Ref2.2*6.1*

Ref3.4*9.8*

Ref1.416.0*


Ref2.0*-1.0

Ref1.80.0

Ref3.9*-0.8

Ref5.0*-1.4

Ref5.6*-3.4


Ref1.50.5

Ref6.64.4

Ref15.8*10.3*

Ref18.2*11.9*

Ref22.1*14.8*


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


Ref0.50.5

Ref0.32.3*

Ref1.04.0*

Ref1.05.0*

Ref4.0*7.0*


Ref0.01.5

Ref0.32.7*

Ref1.0*4.0*

Ref1.0*3.0*

Ref1.0-1.0


Ref-0.50.5

Ref0.80.3

Ref1.0*0.0

Ref2.0*0.0

Ref4.0*3.0


Ref2.02.5*

Ref4.3*4.5*

Ref9.0*9.0*

Ref9.0*9.0*

Ref10.0*9.0*


3.0*Ref

-2.5*Ref

-13.0*Ref

-18.0*Ref

-22.0*Ref


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*


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


Ref3.0*14.0*

Ref4.0*20.0*

Ref4.5*24.5*

Ref5.0*31.0*

Ref5.3*54.0*


Ref0.00.0

Ref1.0*-2.0*

Ref2.5*0.5

Ref4.0*0.0

Ref4.7*0.3


Ref7.0*8.0*

Ref18.0*19.0*

Ref11.5*13.0*

Ref8.0*10.0*

Ref4.76.3


-5.0*Ref

-18.0*Ref

-22.3*Ref

-27.0*Ref

-35.3*Ref


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

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120

Refuel WaitingforlandEMSescort

Weather Mechanical Crewchange Triage Cancelledandcalledback

Restockingaircraft

Dispatchissues Other

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WaitingforlandEMSescort

Traumateamnotassembled

Weather Equipmentissues Refuel Mechanical Other

Delaystosen

ding

(Cou

nt)

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(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

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1000

1200

1400

0%

20%

40%

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100%

0

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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.

Documents

Identifying causes of delay in interfacility transports of ... · Figure 1. Field Trauma Triage Guidelines (Ontario) Figure 2. Ontario Adult Trauma Centres and Referral Boundaries