Content uploaded by Hannah Baumgartner
Author content
All content in this area was uploaded by Hannah Baumgartner on Jul 10, 2023
Content may be subject to copyright.
DOT/FAA/AM-23/08
Aviation Safety
Office of Aerospace Medicine
Washington, DC 20591
Human Factors in Helicopter Air Ambulance
Operations Annotated Bibliography (2014 – 2022)
Hannah M. Baumgartner1
Rebecca DiDomenica2
Justin Durham2
Peter T. Hu2
1Civil Aerospace Medical Institute
Federal Aviation Administration
Oklahoma City, OK 73125
2Cherokee Nation Support, Services, & Solutions
Oklahoma City, OK 73125
February 2023
i
NOTICE
This document is disseminated under the sponsorship of the U.S.
Department of Transportation in the interest of information exchange.
The United States Government assumes no liability for the contents
thereof.
________________
This publication and all Office of Aerospace Medicine technical
reports are available in full-text from the Civil Aerospace Medical
Institute’s publications Website: www.faa.gov/go/oamtechreports
ii
Technical Documentation Page
1. Report No.
2. Government Accession
No.
3. Recipient's Catalog No.
DOT/FAA/AM-23/08
4. Title and Subtitle
Perceptions of Factors Influencing Effectiveness of ATC
Field Training
5. Report Date
February 2023
6. Performing Organization Code
7. Author(s)
8. Performing Organization Report
No.
Baumgartner, H.1, DiDomenica, R.2, Durham, J.2, Hu, P.2
9. Performing Organization Name and Address
10. Work Unit No. (TRAIS)
Federal Aviation Administration
Civil Aerospace Medical Institute, AAM-500
Oklahoma City, OK 73169
11. Contract or Grant No.
12. Sponsoring Agency Name and Address
Office of Aerospace Medicine
Federal Aviation Administration
800 Independence Ave., S.W.
Washington, DC 20591
13. Type of Report and Period
Covered
15. Supplementary Notes
16. Abstract
Helicopter air ambulance (HAA) operations involve particularly challenging conditions, including
landing at unfamiliar, remote, or unimproved sites with terrain and obstacle hazards, and involve urgent
or time-sensitive situations. Associated human factors (HF) issues including fatigue, stress, human error,
and perceived pressure to fly compound the challenging nature of HAA operations. This report aims to
inform the current understanding of HF risks and considerations within HAA operations spanning 2014
– 2022 through a focused review of flightcrew fatigue considerations, environmental conditions, areas
for increased training opportunities, and other operational risk factors.
17. Key Words
Helicopter air ambulance; human factors;
fatigue; training
18. Distribution Statement
Unlimited
19. Security Classif. (of this
report)
Unclassified
20. Security Classif. (of this
page)
Unclassified
21. No. of Pages
60
22. Price
Form DOT F 1700.7 (8-72)
Reproduction of completed page
authorized
iii
Acknowledgments
Research reported in this paper was conducted under the Flight Deck Program
Directive/Level of Effort Agreement between the Federal Aviation Administration
NextGen Human Factors Division (ANG-C1) and the Aerospace Human Factors
Research Division (AAM-500) of the Civil Aerospace Medical Institute.
The opinions expressed are those of the authors alone, and do not necessarily
reflect those of the Federal Aviation Administration, the Department of Transportation,
or the Federal government of the United States.
Correspondence concerning this report should be addressed to Hannah
Baumgartner, Aerospace Human Factors Research Division (AAM-500), 6500 S.
MacArthur Blvd. Oklahoma City, OK, 73125. Email: hannah.m.baumgartner@faa.gov
iv
Table of Contents
Acknowledgments.............................................................................................................. iii
List of Tables ...................................................................................................................... v
List of Abbreviations ......................................................................................................... vi
Background ......................................................................................................................... 1
Purpose ................................................................................................................................ 2
Methodology ....................................................................................................................... 3
Findings............................................................................................................................... 3
Flightcrew Fatigue .......................................................................................................... 3
Environmental Conditions .............................................................................................. 4
Training ........................................................................................................................... 4
Other Operational Risk Factors ...................................................................................... 5
Annotated Bibliography ...................................................................................................... 6
Flightcrew Fatigue .......................................................................................................... 6
Environmental Conditions ............................................................................................ 14
Training ......................................................................................................................... 21
Other Operational Risk Factors .................................................................................... 27
References ......................................................................................................................... 42
vi
List of Abbreviations
AC Advisory Circular
ACTA Applied Cognitive Task Analysis
ATS Accumulated Time with Sleepiness
BMI
Body Mass Index
BOS
Beginning of a Shift
CFIT
Controlled Flight into Terrain
CFR
Code of Federal Regulations
CFV Christophorus Flugrettungsverein (Christophorus Air Rescue
Association)
COVID-19 Coronavirus Disease 2019
CRM Crew Resource Management
DTE
Domain Task Experience
DTIC
Defense Technical Information Center
ECG
Electrocardiography
EDS
Excessive Daytime Sleepiness
EMS Emergency Medical Services
EMT Emergency Medical Technician
ESS Epworth Sleepiness Scale
FAA Federal Aviation Administration
FRAT
Flight Risk Assessment Tool
GA
General Aviation
GCS
Glasgow Coma Scale
HAA Helicopter Air Ambulance
HCM HEMS Crewmember
HEMES Helicopter Hospital Emergency Medical Evacuation Service
HEMS Helicopter Emergency Medical Service
HF
Human Factors
vii
HFACS
Human Factors Analysis and Classification System
HHO Helicopter Hoist Operation
HR Heart Rate
HTAWS Helicopter Terrain Awareness and Warning System
ICU
Intensive Care Unit
IFR
Instrument Flight Rules
IMC
Instrument Meteorological Conditions
ISS
Injury Severity Score
KSS Karolinska Sleepiness Scale
LD Liability Damage
LOC Loss of Control
LOS Length of Stay
NAA
Norwegian Air Ambulance
NASA
National Aeronautics and Space Administration
NTRS
NASA Technical Reports Server
NTS
Non-technical Skills
NTSB National Transportation Safety Board
NVG Night Vision Goggles
PEARLS Promoting Excellence and Reflective Learning in Simulation
PVT Psychomotor Vigilance Test
QTc
Q-wave to T-wave (Interval)
RNoAF
Royal Norwegian Air Force
SAR
Search and Rescue
SBP Systolic Blood Pressure
SCORE Systematic Coronary Risk Evaluation
SCWT Stroop Color and Word Test
SMS Safety Management System
viii
SOP
Standard Operating Procedures
TDPS Temperature Dew Point Spread
TFA Transport Fatigue Assessment
UWES-9 Utrecht Work Engagement Scale
VFR
Visual Flight Rules
WHO-5
World Health Organization 5-item
WHOQOL-100
WHO Quality of Life
1
Background
Following a high number of accidents and ongoing safety issues associated with
Helicopter Air Ambulance (HAA)1 operations, the Federal Aviation Administration
(FAA) received Congressional direction in the “FAA Modernization and Reform Act of
2012” (P.L. 112-095), as well as in National Transportation Safety Board
recommendations, to improve the safety of HAA operations. In response, the FAA
instituted operating requirements for HAA operations by publishing the final rule
“Helicopter Air Ambulance, Commercial Helicopter, and Part 91 Helicopter Operations”
(79 F.R. 9931, 2014), and its subsequent revision “IFR Operations at Locations Without
Weather Reporting” 2 (84 F.R. 35820, 2019). Careful consideration of the human factors
(HF) issues associated with HAA operations is necessary to support safe HAA operations
and ensure that potential new risks are identified and addressed. This report aims to
inform the current understanding of HF risks and considerations within HAA operations
by assessing and summarizing the related scientific literature. Findings will be used to
inform future research and analysis regarding HF-related incidents and accidents in HAA
operations.3
The HAA primarily functions to transport patients from the scene of an accident
to a medical facility for treatment or to transport patients between different medical
facilities. Flight and medical crewmembers staff HAA operations. Often pilots are the
only flightcrew onboard because of the limited space available in helicopters.4 In addition
to operating the aircraft, HAA pilots are responsible for pre-flight planning, analyzing
potential risks and hazards, and executive decision-making (i.e., declining, canceling,
diverting, or terminating a flight; see 14 CFR § 135 Subpart L and 14 CFR § 91). HAA
pilots fly under strict flight-time limitations and rest requirements to ensure safety in
these conditions to help offset the risks (see Table 1). Teams of highly trained medical
staff including medical doctors, paramedics, emergency medical technicians (EMTs), and
nurses accompany the flightcrew/HAA.5 HAA operations are conducted around the clock
and occur at low altitudes during various weather conditions. They often involve landing
1 The term Helicopter Air Ambulance replaced Helicopter Emergency Medical Service (HEMS), which
was made obsolete in 2015 by FAA Advisory Circular (AC) 135-14B. The change recognizes not all air
ambulance flights operated involve an emergency. References to HEMS in this report reflect the original
language of the authors.
2 Instrument Flight Rules.
3 Incidents and accidents are defined in 49 CFR § 830.
4 Patients are configured in the aircraft in such a way that they generally block the co-pilot seat in rotorcraft
(Ruskin, 2019).
5 These roles include medical training as EMT, paramedics, or nurses, and assist the pilot as needed
(Rasmussen & Sollid, 2015).
2
at unfamiliar, remote, or unimproved sites with terrain and obstacle hazards, and typically
involve urgent or time-sensitive situations.
Between 1999 and 2019, the proportion of fatal helicopter accidents was higher
for emergency medical service (EMS) accidents than for non-EMS helicopter operations
(Greenhaw & Venesco, 2021). Between 2007 and 2019, 35% of accidents (or 28 of 80
total accidents) involving Part 135 air medical flight operations6 resulted in a fatality
(National Transportation Safety Board [NTSB], 2019). It should be noted, however, that
these data do not reflect how the role of exposure (e.g., flight hours) across helicopter
operations may interact with these fatality statistics, nor the fact that HAA operations
account for between 2 to 4 times the number of flight hours in comparison to other types
of helicopter operations in the United States (FAA, 2020). Further, trends indicate that
the fatality risk associated with HAA operations may be declining in recent years (FAA,
2020; FAA, 2022). Still, the risks associated with these operations contributed to the
FAA implementing the Helicopter Terrain Awareness and Warning System (HTAWS)7
in addition to stricter weather implementations for flying under visual flight rules (VFR;
14 CFR § 135.605; 14 CFR § 91; see NTSB, 2006).
The challenging nature of HAA operations raises a number of relatively unique
HF issues. Such operational conditions can elevate mental and physical fatigue, stress,
and human error, and make flightcrew communication and decision-making difficult.
Special considerations of HF and safety culture are needed to combat any perceived
pressure on pilots to perform these operations given the critical medical condition of
onboard patients.
Purpose
This report summarizes current scientific literature on HF risks and considerations
within HAA operations spanning 2014 – 2022, focusing on HAA research that has taken
place since the 2014 published rule (79 F.R. 9931). It will inform upcoming research to
analyze HF within serious incidents and accidents in HAA operations. The report
includes a review and an annotated bibliography of HF scientific literature focusing on
four main topics:
1. Flightcrew fatigue, duty and schedule limitations, and risk factors for increased
sleepiness in HAA operations.
6 HAA operations are conducted under 14 CFR § 135 and 14 CFR § 91, depending on who or what is
transported. 14 CFR § 91 is an umbrella term for any operation that is not regulated by 14 CFR § 121, 135
or 129 and is excluded from the statistic. 14 CFR § 135 includes commuter services and on-demand
passenger or cargo services (i.e., non-HAA-specific operations).
7 The HTAWS mandate became effective as of April 2017.
3
2. Environmental conditions that pose risk, such as adverse weather conditions and
nighttime flying.
3. Areas for increased training opportunities.
4. Other operational risk factors within HAA operations.
Methodology
Articles for this annotated bibliography were collected from the Defense
Technical Information Center (DTIC), Google Scholar, the National Aeronautics and
Space Administration (NASA)8 Technical Reports Server (NTRS), ProQuest, and FAA
Library databases between April and June 2022 using the following keywords/phrases:
• Air ambulance
• Air medical services helicopter
• Helicopter "air ambulance" crewing
• Helicopter "air ambulance" fatigue
• Helicopter HAA
• Helicopter HEMS
• Helicopter HEMS crewing
• Helicopter HEMS crewing fatigue
• Helicopter HEMS crewing training
The research principal investigator screened the collected articles using inclusion
criteria that included (a) relevance to air ambulance operations, (b) rotorcraft operations,
and (c) content related to HF and/or accident and serious incident analyses resulting in 91
sources. The principal investigator further screened the sources to exclude secondary
sources and articles that only referenced HAA medical crews or HAA patients, resulting
in the 42 primary research articles reviewed in this annotated bibliography.
Findings
Flightcrew Fatigue
Fatigue-related considerations are particularly important for the on-call nature of
HAA operations, where idleness, shiftwork schedule, workload, and potential circadian
disruptions associated with nighttime flying may influence a pilot’s fatigue level for any
given call. Fatigue can elevate the risk of pilot error that could lead or contribute to a
potential aviation incident or accident (Caldwell, 1997; Gurubhagavatula et al., 2021).
Nonetheless, a recent survey found high levels of daytime sleepiness in U.S. HAA pilots
(Haber Kamine et al., 2022). Research from international HAA operators offers insight
into effective shift work scheduling to minimize fatigue in these operations such as 7-
day-on, 14-day-off scheduling practices (Flaa et al., 2019, 2021, 2022). However, many
international operators are part of state-run healthcare programs and operate under
8 National Aeronautics and Space Administration.
4
different civil aviation authority requirements, making comparisons with private operator
practices in the U.S. difficult. Overall, the annotated literature highlights the need for
more fatigue-related research in U.S. HAA operations. For reference, the current FAA
crew duty time (i.e., a scheduled shift that includes duties that are not flight-related) and
flight time (i.e., the portion of the duty time spent flying) limitations are included in
Table 1.
Table 1
Flight Time Limitations and Rest Requirements per 24 Consecutive Hours: Unscheduled
One- and Two-Pilot Crews (14 CFR § 135.267)
One-Pilot Crew
Two-Pilot Crew
Maximum Duty Period
14 hours
14 hours
Maximum Total Flight Time
8 hours
10 hours
Required Rest
10 hours
10 hours
Note. These requirements summarize those found in 14 CFR § 135.267. Operations that
meet additional criteria may instead follow schedule restrictions detailed in 14 CFR §
135.271, “Helicopter Hospital Emergency Medical Evacuation Service (HEMES).”
Environmental Conditions
Environmental conditions (including adverse weather, unfamiliar terrain, and
nighttime flying) can increase pilot task demand, make in-flight decision-making more
challenging, and are known risk factors for fatal HAA accidents and serious incidents
(Aherne et al., 2018, 2021; Ramee et al., 2021). Poor weather conditions and flying at
night also increase susceptibility of inadvertent flight into Instrument Meteorological
Conditions (IMC) or other conditions that require pilots to fly under Instrument Flight
Rules (IFR), which require additional pilot certification and training and additional
approval for the aircraft. Poor visual cues associated with adverse weather events are also
risk factors for spatial disorientation, which can lead to loss of control and impact into
terrain accidents (Aherne et al., 2019). The annotated literature demonstrates the risks
associated with different environmental conditions for HAA flying, and details how these
adverse conditions may influence pilot decision-making.
Training
A number of areas for improvement in training have been identified for HAA
operations, such as increased access to simulation training and an increased focus on pilot
skills related to weather instruments in the cockpit (Abrahamsen et al., 2015; Spiers et al.,
2021). In situ simulation-based training is a common practice in the medical field and
5
includes acting out clinically relevant situations to practice crew interactions and
communication, which may not involve a flight simulation at all. An increased emphasis
on this clinical simulation-based training within HAA operations is supported by the
literature, particularly with regard to honing Crew Resource Management (CRM) and
team communication skills (Bredmose et al., 2021b; Lunde & Braut, 2019; Rasmussen et
al., 2019). Additionally, fatality in HAA accidents that occurred during poor weather
conditions has recently been linked to low pilot domain task experience (DTE; Aherne et
al., 2018), highlighting the need for increased pilot training under IMC using flight
simulators (De Voogt et al., 2020; Spiers et al., 2021).
The annotated literature provides insight into potential training practices that
should be considered or enhanced for HAA crewmembers including simulation training,
virtual and augmented reality scenarios, CRM training, and training for inadvertent
encounters with IMC. These data also provide support for recent operational
improvements in training and simulator facilities that have been adopted by some major
air ambulance operators (Rosenlof, 2020; Air Methods, 2017). A small but significant
focus of the reviewed literature is placed on pilot and crewmember perceptions towards
the different modes (e.g., simulator, virtual reality) of training and assessment. These
perceptions are typically in the form of self-reported reactions concerning level of
engagement, learning, motivation, and satisfaction, and are evaluated to inform future
training practices.9
Other Operational Risk Factors
A number of additional operational risk factors were identified in the literature
with regard to HF considerations in HAA operations. The annotations included in this
section highlight important risk factors and considerations inherent to HAA operations
that do not fall under the themes of fatigue, environmental conditions, or training. For
example, a positive safety culture is particularly important in HAA operations where
pilots face unique pressures to fly related to patients’ medical status (Aalberg et al., 2020;
Chesters et al., 2016; Gardner et al., 2017; Lunde & Braut, 2019). Safety culture refers to
a collective set of views surrounding an organization’s approach to work values, beliefs,
and safety practices (Reason, 1997; see Key et al., Under Review, for a review of the
literature), which can influence a pilot’s perceived pressure to accept an HAA flight
(Aalberg et al., 2020; Lunde & Braut, 2019). Additionally, stressful aspects of HAA
operations such as rescue missions can contribute to an increased risk of serious incidents
9 See Bredmose et al. (2020); Bredmose, Østergaard, & Sollid (2021); Bredmose, Røislien, Østergaard, &
Sollid (2021); Bredmose, Hagemo, Østergaard, & Sollid (2021).
6
or accidents, and have chronic physiological effects on pilots’ health and wellbeing
(Bauer et al., 2018, 2019, 2020; Strauss et al., 2021).
Annotated Bibliography
Flightcrew Fatigue
Akter, R., Larose, T. L., Sandvik, J., Fonne, V., Meland, A., & Wagstaff, A. S. (2021).
Excessive daytime sleepiness and associated factors in military search and rescue
personnel. Aerospace Medicine and Human Performance, 92(12), 975–979.
https://doi.org/10.3357/AMHP.5946.2021
Introduction. The purpose of this study was to determine the prevalence of
abnormal excessive daytime sleepiness (EDS) and contributing factors among Royal
Norwegian Air Force (RNoAF) Search and Rescue (SAR) helicopter personnel.
Methods. Two hundred and fifty SAR helicopter personnel in the RNoAF including
flight commanders, co-pilots, flight engineers, system operators, rescuers, medical
doctors, and technicians were invited to participate in the study. Crews not involved in
on-call duties were excluded. A total of 175 RNoAF SAR personnel completed a survey
of (a) socio-demographic items including age, marriage status, personnel category,
number of children, special family care responsibility, and second job information; and
(b) lifestyle-related factors including smoking status, tobacco use, caffeine use off duty,
commuting distance, health status, and physical exercise. The Epworth Sleepiness Scale
(ESS) was used as both a continuous and categorical outcome variable to evaluate EDS.
On the ESS, participants rated the likelihood of dozing off or falling asleep when
engaging in eight different activities. Higher scores on the ESS indicated greater severity
of EDS. Results. Abnormal EDS was prevalent among 41% of the RNoAF personnel. No
relationship was found between socio-demographic and lifestyle factors on excessive
EDS. Conclusion. Results found that abnormal EDS was common among an RNoAF
SAR sample population. This survey reached a large and diverse sample that represents a
diverse range of occupations and operations within the RNoAF, including a subset that
work with HAA operations. Further research is needed to assess any occupational or
operational differences in daytime sleepiness within this population.
Bushmaker, R., Corey, K., Dunn, J., Lalonde, T., & Estrada, S. (2019). Evaluation of a
new helicopter crew transport fatigue assessment. Air Medical Journal, 38(3),
198-201. https://doi.org/10.1016/j.amj.2018.11.006
7
Introduction. Factors associated with HAA operations such as shift work,
transport times, and night vision goggles (NVG) may uniquely influence fatigue. This
study aimed to create and validate a tool to assess fatigue levels in air ambulance crews.
Methods. Universal and air ambulance-specific factors that contribute to fatigue,
including questions about the number of transports per shift and night vision goggle use,
were included in a new Transport Fatigue Assessment (TFA) tool. In Phase 1, crews (n =
95 shifts) from two HAA operations completed the TFA and the ESS at the beginning of
each shift and after each transport within a shift. Internal consistency between pre- and
post-flight assessments was assessed, as was concurrent validity between TFA and ESS
scores. Seven confusing and/or irrelevant questions were removed from the TFA tool or
reworded based on the exploratory factor analysis. Phase 2 evaluated TFA scores and
self-reported levels of fatigue using a 5-point Likert scale in a new population of HAA
crewmembers at the beginning of a shift (BOS) and following transports. Results. In
Phase 1, ESS scores were found to be internally consistent (α = .72) between BOS (n =
95) and post-transport (n = 63) administrations, while TFA score internal did not reach
significance (α = .48). Phase 1 BOS TFA and BOS ESS scores were positively correlated
(b
= 0.503) as were post flight TFA and ESS scores (b
= 0.167). In Phase 2, BOS TFA
scores (n = 923) and post flight TFA scores (n = 745) were found to be internally
consistent (Cronbach α = .753), and TFA scores were positively associated with
concurrently reported fatigue levels (b
= 0.479 and b
= 0.189 for BOS and post flight
scores, respectively). Conclusion. These findings suggest that the TFA may be a useful
tool in evaluating flightcrew fatigue that is specific to air ambulance operations. The
study found that TFA scores were positively associated with both freely self-reported
fatigue levels and associated with scores on a validated daytime sleepiness scale, the
ESS.
Flaa, T. A., Bjorvatn, B., Pallesen, S., Røislien, J., Zakariassen, E., Harris, A., & Waage,
S. (2021). Subjective and objective sleep among air ambulance
personnel. Chronobiology International, 38(1), 129-139.
https://doi.org/10.1080/07420528.2020.1802288
Introduction. The purpose of this study was to assess how shift work affects
sleep quality and quantity in Norwegian HEMS workers. Methods. Sixty-one pilots and
HEMs crewmembers (HCMs) from Norwegian Air Ambulance (NAA) participated in
this study for 3 weeks during the fall/winter of 2014, and a subset of this population (n =
50) also participated in a second data collection for 3 weeks during summer 2015. The
studied shift schedules included a 7-day on-duty workweek, a 14-day off-duty period, a
7-day on-duty workweek, and a 21-day off-duty period. All shifts started and ended at 10
8
am on Monday morning. Work conditions followed typical NAA procedures, including
communal housing and maximum flight times (7 hours in a consecutive 24-hour period,
12 hours in a 48-hour period, and 30 hours in a 7-day period) and maximum active work
times (14 hours during a consecutive 24-hour period, 30 hours during a 72-hour period)
approved by the Civil Aviation Authority of Norway. The present study analyzed data
from sleep diaries completed daily in the morning and from wrist actigraphy worn
throughout the six test weeks. Results. Actigraphy and sleep diary data showed bedtimes
were later during the workweek in the summer than in the winter, and sleep diary data
showed that workers spent less time in bed during the summer versus winter workweeks.
Summer and winter workweeks did not differ in terms of wake-up time, wake after sleep
onset, sleep efficiency, or total sleep time. During the winter, actigraphy and sleep diary
data showed that bedtime and wake time were later, time in bed was longer, and wake
after sleep onset was higher during the workweek compared to the weeks before and
after. Additionally, actigraphy data showed that sleep efficiency was lower, and sleep
diary data showed that total sleep time was longer during the winter workweek. During
the summer, actigraphy and sleep diary data showed later bedtimes and wake-up times,
longer times in bed, and wake after sleep onset was higher during the workweek in
comparison to the weeks before and after work. Finally, actigraphy data also showed that
sleep efficiency was lower during the workweek. Conclusion. Actigraphy and sleep diary
data were largely similar between HEMS workweeks during the winter and summer
seasons in NAA, and the observed slight changes in bedtime and time in bed could be
due to seasonal workload and circadian differences. Altogether, workers experienced
delayed sleep onsets, more time awake after sleep onset, and lower sleep efficiency
scores during the workweek in comparison to non-working weeks, which relate to being
on-call for night HEMS trips. However, total sleep times were higher during the
workweek, at least during the winter season, and more time was spent in bed during the
workweek across seasons. Overall, these findings suggest that HEMS workers are
relatively well adjusted to sleep schedules during the workweek, though attention to
actigraphy data is important to assess objective measures of sleep quality and disruption
due to shift work.
Flaa, T. A., Bjorvatn, B., Pallesen, S., Zakariassen, E., Harris, A., Gatterbauer-Trischler,
P., & Waage, S. (2022). Sleep and sleepiness measured by diaries and actigraphy
among Norwegian and Austrian helicopter emergency medical service (HEMS)
pilots. International Journal of Environmental Research and Public
Health, 19(7), 4311. https://doi.org/10.3390/ijerph19074311
9
Introduction. HEMS pilots in the NAA and the Christophorus Flugrettungverein
(Christophorus air rescue association, CFV) in Austria work a seven consecutive 24-hour
shift schedule. The fatigue and sleepiness experienced by these pilots can be detrimental
to HEMS operations. This study examined the sleep and sleepiness of NAA and CFV
pilots in HEMS using sleep diaries and wrist actigraphy data. Methods. Twenty-five
NAA (1 female, 24 male; MAge = 43.6 years; SD = 5.2) and 22 CFV pilots (0 female, 22
male; MAge = 42.8 years, SD = 6.1) working seven consecutive 24-hour shifts participated
in this study. A questionnaire was administered on the first workday regarding sex, age,
years in the position, and caffeine intake at work (number of cups), sleep needs, and sleep
problems related to the work schedule. NAA and CFV staff recorded the time spent
during training sessions, time spent on missions, and the total number of missions in a
Mission Log. Sleep was recorded upon awakening each morning in a sleep diary and
continuously throughout the week by wrist actigraphy. Sleep variables (i.e., bedtime,
wake-up time, wake after sleep onset, time in bed, total sleep time, and sleep efficiency10)
were calculated based on the diary entries. The Karolinska Sleepiness Scale (KSS)
measured sleepiness11 every other hour throughout the workweek. Results. The NAA
pilots had later bedtime and wake-up time, spent more time awake after sleep onset, spent
more time in bed, slept longer, reported more disturbed sleep, and had lower sleep
efficiency compared with the CFV pilots. All differences were significant (p < .01). Sleep
and sleepiness parameters did not change throughout the workweek; however, both crews
reported later bedtime and wake-up times towards the end of the workweek (Days 6 and
7). KSS scores significantly differed by the time of day and day of the week, but did not
differ between crews. NAA pilots completed upwards of 30 missions per week whereas
CFV pilots completed upwards of 51 missions per week. However, the number of
missions did not influence sleep variables significantly. Conclusion. Differences between
NAA and CFV pilots were indicated by diary entries and actigraphy. NAA pilots had
later bedtime and wake-up times and spent more time awake after sleep onset and had
lower sleep efficiency compared with the CFV pilots. This could be due to the NAA
pilots taking on more missions after dark. There were no differences in the bedtime and
wake-up time throughout the workweek for both crews. However, both crews revealed
convergence on the following result: bedtime and wake-up times were delayed by the end
of the workweek.
10 Total sleep time/time in bed X 100.
11 Sleepiness is measured on a scale of 1 (very alert) to 9 (very sleepy, great effort to stay awake, fighting
sleep). Excessive sleepiness is indicated by a score of 7 or greater.
10
Flaa, T. A., Harris, A., Bjorvatn, B., Gundersen, H., Zakariassen, E., Pallesen, S., &
Waage, S. (2019). Sleepiness among personnel in the Norwegian air ambulance
service. International Archives of Occupational and Environmental Health, 92(8),
1121-1130. https://doi.org/10.1007/s00420-019-01449-w
Introduction. Shift work conditions and extended work hours in Norwegian
HEMS operations put crews at risk for increased sleepiness and fatigue. This field study
assessed sleepiness in Norwegian HEMS flightcrews before, during, and after a 7-day
workweek and across various operations, schedules, and conditions. Methods. Fifty
pilots and HCMs (1 female, 49 male) from NAA that had previously participated in an
initial shift-work study, took part in a 3-week second study in the spring/summer of 2015.
Schedule information for these participants mimicked the conditions described above (see
Flaa et al., 2021). Crews completed a questionnaire and the ESS on their first duty day,
completed the KSS every other hour while awake during the workweek, completed a
reaction-time test at different points throughout the workweek, and completed the
Accumulated Time with Sleepiness (ATS) scale nightly before bed for the 3-consecutive
study weeks. Results. Participants reported lower sleepiness scores during the workweek
versus off-weeks for all six measures of ATS (i.e., heavy eyelids, feeling gravel-eyed,
difficulty focusing your eyes, irresistible sleepiness, reduced performance, periods of
fighting sleep). ATS scores remained consistent within the 7-day workweek. During the
workweek, time of day significantly increased KSS scores (highest at 2400h).
Additionally, having a higher workload was associated with lower KSS scores, and
participants reported higher KSS scores on day 1 of the workweek in comparison to the
remaining six workdays of the study. Reaction times did not significantly change
throughout the workweek. Conclusion. Overall, the participants reported less sleepiness
and associated factors during the 7-day workweek in comparison to off-duty weeks.
Home-life factors including child rearing, second jobs, and personal responsibilities may
explain this reported effect, in combination with the structured living environment
available while on duty. Additionally, the activeness associated with a higher workload
may explain the decrease in associated sleepiness scores during the workweek. Overall,
these results suggest that the work conditions and structured living environment may be
effective in mitigating risks of elevated sleepiness associated with shift work and long
work hours in NAA crews.
Fletcher, A., Stewart, S., Heathcote, K., Page, P., & Dorrian, J. (2022). Work schedule
and seasonal influences on sleep and fatigue in helicopter and fixed-wing aircraft
operations in extreme environments. Scientific Reports, 12(1), 1-13.
https://doi.org/10.1038/s41598-022-08996-2
11
Introduction. The purpose of this research was to measure sleep, work, alertness,
mental performance, and other fatigue-related factors within several aviation emergency
medical, firefighting, SAR, offshore transport, and other mission-critical contexts.
Methods. Two hundred and ten employees at a company providing EMS, SAR, and oil
and gas services participated in this study. Participants included pilots, other crew, and
technicians across seven countries. Data were collected between November 2014 and
December 2018 over 21 days for each study in which participants continued their duties
while they completed study questionnaires and performance tasks. Experimenters visited
each operating company to provide equipment and training where participants were on-
duty at the base, working either continuously (not including breaks) or as needed (i.e., on-
call). Participants wore activity monitors, completed electronic tablet-based work, and
sleep diaries. Participants completed the Psychomotor Vigilance Test (PVT) on tablets
during breaks in duty periods and on days off. Results. Work occurred primarily during
daytime hours while most sleep occurred during the night for both daytime operations
and 24-hour operations. The proportion of sleep occurring during duty time fluctuated
between 0% and 30% across countries. However, there were extended sleep and nap
times in the afternoons and during days off. Overall, PVT response times were
significantly longer on duty days compared to non-duty days. Conclusion. The results
indicate that some extended sleep and napping occur during duty time in the examined
aviation operations, which should be taken into account when assessing fatigue risk
management. Most sleep occurred at night for both daytime operations and 24-hour
operations, suggesting that the availability of rest places for on-call 24-hour operations is
critical. This study provides insight into typical resting patterns of a large range of
aviation personnel across seven countries involved in extreme environments, which could
inform future fatigue mitigation plans for similar high-stress aviation operations.
Haber Kamine, T., Dhanani, H., Wilcox, S., Kelly, E., Alouidor, R., Kramer, K., Carey,
Y., Ryb, G., Putnam, A.T., Winston, E., & Cohen, J. (2022). American helicopter
emergency medical service pilots report to work despite high rates of sleepiness.
Air Medical Journal, 41(5), 432-434. https://doi.org/10.1016/j.amj.2022.07.005
Introduction. The purpose of this study was to assess sleepiness in HEMS pilots
in the United States. Methods. Thirty-one HEMS pilots (0 female, 31 male; MAge = 48
years, SD = 12) completed the ESS and answered demographic questions. Results.
Twelve of the 31 pilots completed the ESS while on duty (n = 9 on the day shift, n = 3 on
the night shift). Twenty or 65% of pilots reported ESS scores >10, indicating EDS. There
were no differences found between ESS scores of on-duty versus off-duty pilots.
Fourteen pilots (45%) reported that they have previously turned down a flight due to
12
fatigue, while 20 pilots (65%) reported that they should have previously turned down a
flight due to fatigue. Pilots reported that fatigue degraded alertness during flight (77.6%),
degraded performance during flight (51.6%), and that it affected their ability to
concentrate during flight (29%). When fatigue affected performance in flight, 74% of
pilots reported that it largely occurred during the route to the destination as opposed to
takeoff or landing. Conclusion. These findings demonstrate the high prevalence of
daytime sleepiness among HEMS pilots whether on- or off-duty and show that the effects
of this sleepiness on flight performance are noticeable to pilots. Further, these results
imply that while some pilots are turning down flights due to fatigue, several pilots that
report that they should have previously turned down flights due to fatigue but did not.
Further research should investigate differences in daytime sleepiness and fatigue while
on- and off-duty in HEMS pilots with a larger sample to better assess differences between
day and night shiftwork.
Radstaak, M., Geurts, S. A. E., Beckers, D. G. J., Brosschot, J. F., & Kompier, M. A. J.
(2014). Work stressors, perseverative cognition and objective sleep quality: A
longitudinal study among Dutch helicopter emergency medical service (HEMS)
pilots. Journal of Occupational Health, 56(6), 469-477.
https://doi.org/10.1539/joh.14-0118-OA
Introduction. In general, individuals with poor sleep quality do not completely
recover from the cognitive and emotional demands of work and consequently, put their
health and well-being at risk. A longitudinal study was conducted to examine the
associations between work stressors (e.g., workload and distressing shifts), preservative
cognition (prolonged activation of the cognitive representation of stressors), and
objective and subjective sleep quality (i.e., sleep onset latency). Methods. Twenty-four
pilots (1 female, 23 male; MAge = 44.1 years, SD = 5.97) working for the Dutch HEMS
participated in this study. Each participant was administered six questionnaires
addressing work stressors, sleep quality, and perseverative cognition. Questionnaires
were administered at the end of three consecutive day shifts and each morning following
the shifts. An activity monitor was worn for three consecutive days during testing to
measure sleep quality (i.e., onset latency, total sleep time, and the number of
awakenings). Results. Work stressors were positively associated with poor sleep quality;
more distressing shifts further delayed the onset of sleep (r = 0.5) and higher workloads
further impaired subjective sleep quality (r = -0.42). Work stressors were positively
associated with perseverative cognition; higher workload and distressing shifts led to
higher levels of perseverative cognition (r = 0.19, r = 0.62, respectively). Perseverative
cognition was positively associated with delayed sleep onset (r = 0.74). Perseverative
13
cognition mediated the association between work stressors and sleep onset latency (95%
CI [0.02, 5.99]). Conclusion. This study examined the association between work stress
and sleep quality. Distressing shifts delayed the onset of sleep and negatively impacted
subjective sleep quality, even more so than perseverative cognition. This suggests that
distressing shifts take the most time to recover from, perhaps because they are more
emotionally charged. Most notably, preservative cognition acted as an explanatory
mechanism in the association between work stressors and sleep onset, supporting the
preservative cognition hypothesis’ which asserts that thinking about stressful events can
impede stress recovery.12
Zakariassen, E., Waage, S., Harris, A., Gatterbauer-Trischler, P., Lang, B., Voelckel, W.,
Pallesen, S., & Bjorvatn, B. (2019). Causes and management of sleepiness among
pilots in a Norwegian and an Austrian air ambulance service—A comparative
study. Air Medical Journal, 38(1), 25-29.
https://doi.org/10.1016/j.amj.2018.11.002
Introduction. HEMS pilots work for extended hours, during different times of
day, and on different shift schedules. This can disrupt natural sleeping patterns and be
hazardous for the job. As an attempt to combat sleepiness in HEMS pilots, subjectively
reported sleepiness and fatigue levels, as well as strategies for managing sleepiness and
fatigue, were evaluated. Methods. NAA and CFV pilots in Austria participated in this
study. Thirty NAA pilots completed a work schedule that sequentially consisted of 7 days
on-duty, 14 days off-duty, 7 days on-duty, and 21 days off-duty. Twenty-four CFV pilots
completed the same work schedule, but instead with seven days on-duty, followed by
seven days off-duty. While on duty, the pilots completed a questionnaire addressing
sleep, work-related sleepiness and fatigue, and management of sleepiness. Pilots rated
situations for their fatigue-triggering potential (does not cause fatigue, low fatigue,
moderate fatigue, and high fatigue). The ESS and KSS were used to evaluate sleepiness.
Results. NAA and CFV pilots had normal ESS and KSS scores (within acceptable range)
and reported getting sufficient sleep on- and off-duty. Both groups used napping and
coffee to combat sleepiness and fatigue. However, a significantly larger proportion of
NAA pilots than CFV pilots slept more and did physical exercise to combat sleepiness
and fatigue. CFV pilots reported administrative duties, phone calls, and environment as
factors preventing them from napping while on duty; NAA pilots reported HEMS
missions as a factor preventing them from napping. Conclusion. Strategies for managing
sleepiness and fatigue were assessed between two groups of HEMS pilots. Napping and
12 See Brosschot et al. (2006) for a discussion of the perseverative cognition hypothesis.
14
coffee-drinking were prevalent strategies for preventing sleepiness and fatigue for both
groups. Neither group suffered from sleep deprivation; ESS and KSS scores were normal
and pilots reported “sufficient sleep” while on and off duty. Overall, results validated that
NAA and CFV pilots perceive low levels of sleepiness.
Environmental Conditions
Aherne, B., Newman, D., & Chen, W. S. (2021). Acute risk in helicopter emergency
medical service transport operations. Health Science Journal, 15(1), 0-0.
Introduction. The purpose of this study was to objectively measure the difference
in acute risk between day and night HEMS transport relative to aviation and medical
procedure risks. Methods. U.S. HEMS fatal accident data between 1995 and 2015 –
including accidents involving any flights to pick up a patient, transport a patient, or return
to base after delivering a patient to the destination were identified from previous research
and used in this study. The frequency of fatal HEMS accidents by day and night
missions, fatal patient injuries, and patients transported by day and night were
quantitatively classified. Acute risk was quantified in micromorts, a unit of risk
representing a one-in-a-million chance of death, to estimate the probability of a fatal
HEMS accident by day and night, fatal patient injury in a HEMS accident during the day,
fatal spatial disorientation HEMS accident during the night, fatal patient injury in a
spatial disorientation HEMS during the night, and fatal HEMS accident at night from
other causes. Acute risk for medical procedures including fatal injury in road ambulance
accidents, anesthesia-related mortality, skiing fatalities, diving fatalities, parachuting
fatalities, and rock climbing fatalities were also used to make comparisons. Results.
There was an overall acute risk of 15 micromorts for fatal HEMS accidents per mission.
Acute risk was lower for daytime accidents (7.55 micromorts) relative to nighttime
accidents (27.33 micromorts). For nighttime accident acute risk, the majority of
operational accident risk was made up of spatial disorientation (18.75 micromorts, 69%).
Patient risk during nighttime spatial disorientation (6.43 micromorts) was greater than
double the patient risk during the daytime (2.95 micromorts). Importantly, acute risk to
HEMS flightcrew was double relative to a patient’s risk during daytime HEMS missions
(7.55 micromorts vs 2.95 micromorts) and more than quadruple for nighttime HEMS
missions (27.33 micromorts vs 6.43 micromorts). Conclusion. In general, this study
found that nighttime HEMS missions increase acute risk to HEMS flightcrews and
patients compared to daytime HEMS missions for accidents that occurred from 1995-
2015. This work provides one metric to compare differences in risk between daytime and
15
nighttime HEMS missions, though other factors besides fatality (e.g., accident rates,
injuries) are also important considerations for overall safety comparisons.
16
Aherne, B. B., Zhang, C., Chen, W. S., & Newman, D. G. (2018). Pilot decision making
in weather-related night fatal helicopter emergency medical service
accidents. Aerospace Medicine and Human Performance, 89(9), 830-836.
https://doi.org/10.3357/AMHP.4991.2018
Introduction. Nighttime flights in fog or cloud are particularly dangerous for
HEMS flights operating under VFR. The purpose of this study was to investigate the
relationship between Temperature Dew Point Spread (TDPS) and pilot years of
experience during these situations. It was hypothesized that HEMS pilots with less
experience were associated with increased fatal outcomes when TDPS was low.
Methods. Thirty-two NTSB-reported fatal accidents between 1994 and 2013 were
selected; these accidents were single-pilot, at night, under VFR, and involved a loss of
control (LOC) or controlled flight into terrain (CFIT). Relative risk and odds ratios were
calculated for the likelihood of nonvisual meteorological conditions (non-VMC) and the
likelihood of a fatal accident when TDPS is in the 0°-to-4°C range (i.e., cloud-ceiling
conditions) versus TDPS ≥5°C. Relative risk and odds ratio was also calculated for fatal
accidents during 0°-to-4°C TDPS when pilots have low or high experience. Results.
Among the 32 fatal accidents examined, pilot experience was found to be a significant
predictor in estimating the 0°-to-4°C TDPS range. The 0°-to-4°C TDPS range was also
significantly associated with fatal outcomes, and low-experience pilots were significantly
associated with fatal outcomes in the 0°-to-4°C TDPS range when compared to high-
experience pilots. Conclusion. The finding that experience predicting TDPS indicates
that high-experience pilots flew significantly more in non-VMC conditions with lower
cloud ceiling than low-experience pilots. However, accidents during 0°-to-4°C TDPS
conditions were over nine times more fatal when flown by a pilot with low experience
(≤2 years of HEMS experience) than when flown by a pilot with ≥6 years of HEMS
experience. Therefore, increased experience may inform better risk assessments in these
conditions. However, increased experience may also lead such pilots to demonstrate
overconfidence when assessing risk. Further research is needed to understand how other
factors, such as experience with weather cues, work pressure, and cognitive demand may
affect outcomes.
17
Aherne, B. B., Zhang, C., Chen, W. S., & Newman, D. G. (2019). Systems safety risk
analysis of fatal night helicopter emergency medical service accidents. Aerospace
Medicine and Human Performance, 90(4), 396-404.
https://doi.org/10.3357/AMHP.5180.2019
Introduction. Nighttime conditions are a common risk factor for accidents in
HEMS operations. Other risk factors for accidents include pilots with less than 6 years of
HEMS DTE, pilots lacking instrument flying capabilities, and adverse weather
conditions. This study conducted a system safety risk analysis to (a) determine whether
fatal night accident rates differ in the day and night; (b) identify other risk factors driving
fatal accident rates; and (c) identify measures to reduce the likelihood of fatal accidents
occurring during the nighttime. Methods. Findings from 32 night VFR fatal HEMS
accidents between 1995 and 2013 were obtained. Accidents were stratified by LOC, night
operational accident sequence, and the following design options: pilot DTE (i.e., low,
high), and flight rule capability. The probability of fatal accidents occurring under
different DTE, VFR, and IFR conditions was calculated as a measure of the overall
effectiveness of these design options as a high-risk system.13 Effectiveness results were
used to estimate residual risk for the overall system. Results. Fatal accident rates were
significantly different between daytime and nighttime operations. The fatal accident rate
was over three times greater for low-DTE than high-DTE pilots, and over six times
greater for pilots without IFR-capabilities (VFR-only) than for pilots with IFR
capabilities. Low-DTE pilots with VFR-only capabilities were the least effective
combination, as they had the highest probability of sustained spatial disorientation and
were significantly associated with night operational nonsurvivable accidents. VFR-only
capability had a higher probability of spatial disorientation than IFR capability.
Conclusion. This study used a system safety approach to determine the factors that could
reduce the likelihood of fatal accidents in HEMS, with the larger goal of preventing
future accidents. Night operations, DTE, and instrument flying capabilities influenced the
severity of HEMS accidents and contributed to the different rates of fatal accidents
observed during the day versus the night. Visual orientation cues are lost during the
nighttime and often result in spatial disorientation. This study showed that low-DTE
pilots with VFR-only capabilities were less likely to maintain spatial orientation, were
less familiar with the aircraft instruments, and thus were at a much greater risk for fatal
night accidents.
13 The system safety risk analysis technique used also assesses the stability of the design options, identifies
issues that may increase risk over time, and determines how rapidly effectiveness of the system declines
over time.
18
Aherne, B. B., Zhang, C., & Newman, D. G. (2016). Pilot domain task experience in
night fatal helicopter emergency medical service accidents. Aerospace Medicine
and Human Performance, 87(6), 550-556.
http://doi.org/10.3357/AMHP.4454.2016
Introduction. This study examines the relationship between pilot experience with
HEMS (i.e., DTE) and accidents during night HEMS operations. Methods. Thirty-two
fatal single-pilot nighttime HEMS accidents between 1994 and 2013 were identified in
the NTSB database. Years of HEMS experience, age, sex, and total flight hours were
identified against an EMS pilot industry demographic. Results. All 32 pilots were male,
MAge = 47.6 years (SD = 9.23). Total flight hours varied between 1,902 and 20,537 hours
(MFlight = 5,283 hours, SD = 3,893). Average HEMS experience was M = 4.10 years (SD
= 6.23); 14 pilots had less than one year of HEMS experience. Five pilots (16%) had an
instrument proficiency check within the preceding six months. Pilots with less than 4
years of HEMS experience had a statistically significant increase in accident rate; pilots
with more than 10 years of HEMS experience had a statistically significant decrease in
the accident rate. Conclusion. The study found a relationship between HEMS experience
and the likelihood of a nighttime accident. The majority of pilots (56%) in the identified
accidents had less than two years of HEMS experience. The lack of experience may be in
part due to the on-demand nature of HEMS operations. Although increased (>10 years)
experience may be effective at reducing risk, years of experience do not directly explain
the decision-making that leads pilots to operate in risky, hazardous conditions. Although
cognitive and decision-making mechanisms are proposed, more research is needed to
better understand and prevent future HEMS accidents.
De Voogt, A., Kalagher, H., & Diamond, A. (2020). Helicopter pilots encountering fog:
An analysis of 109 accidents from 1992 to 2016. Atmosphere, 11(9), 994.
https://doi.org/10.3390/atmos11090994
Introduction. The FAA increased weather minimums for helicopter operations in
2014 as a precaution against fatal accidents during IMC. Prior to this change, most
helicopters could operate in Class G airspace under IFR and VFR with low and
potentially unsafe minimum visibility. Accident reports were evaluated for fog,
specifically to understand its occurrence in helicopter operations in IMC. Methods. One
hundred and nine helicopter accident reports between 1992 and 2016 were acquired from
the NTSB online database. Only accidents that mentioned fog around the area of and
during the accident were selected. NTSB investigator impressions (i.e., narrative
statements) of whether or not the pilot faced external or self-induced pressures to
19
maneuver the helicopter to or away from IMC conditions (i.e., fog) were also obtained.
Results. Seventy-three (67%) incidents evaluated in this study were fatal, with a total of
163 fatalities. Instrument rating was not a significant factor in fatal accidents. Fatal
accidents occurred more often when the pilot flew into IMC intentionally as opposed to
unintentionally. Accidents occurred significantly more frequently when the pilot was
under pressure compared to when the pilot was not under pressure, even after excluding
HEMS pilots from the analysis. Conclusion. Fog poses a significant risk to helicopter
operations. Pilots who were reportedly under pressure when encountering fog were more
likely to be in an accident, as were pilots who reportedly flew into IMC intentionally.
These findings from NTSB investigator impressions suggest that flight accidents under
fog conditions are mainly due to decision-making under pressure. Therefore, helicopter
pilots should be trained on how to respond to IMC to mitigate the risks involved.
Ramee, C., Speirs, A., Payan, A. P., & Mavris, D. (2021). Analysis of weather-related
helicopter accidents and incidents in the United States. In AIAA Aviation 2021
Forum (p. 2954). https://doi.org/10.2514/6.2021-2954
Introduction. The purpose of this study was to determine what types of weather
cause helicopter incidents. Methods. Two hundred and fifty-four weather-related
helicopter events between 2008 and 2018 were analyzed from the NTSB aviation
database. FAA GA and Part 135 Activity Surveys administered between 2008 and 2018
were used to estimate the number of flight hours by helicopter type and industry (data
was not available for 2011). Geographical analysis of event location was also performed.
Results. Overall, weather was a factor in 28% of fatal helicopter accidents. Weather-
related factors (i.e., wind, ceiling visibility, precipitation, light conditions) were more
often associated with accidents and incidents that also cited issues with aircraft operations
performance and capabilities (68%), task performance (57%), and action/decision (45%).
Wind was the most common weather type among incidents but had a low fatality rate
(7%). However, the next most common weather types – ceiling/visibility/precipitation
and light conditions – had very high fatality rates (62% and 57% respectively).
Furthermore, turbulence and convective weather had low frequencies but also high
fatality rates (33% and 67% respectively). Incidents and accidents involving wind-related
weather involved flights close to the ground and often were related to LOC. The majority
of weather conditions that affected flight visibility had a fatality rate greater than 70%.
Additional analyses found that weather-related events occurred more frequently in the
summer. Moreover, pilots with lower total flight hours had higher counts of weather-
related events. Air ambulance operations accounted for the highest proportion of weather
events related to visibility conditions (29%) across types of operations. Conclusion.
20
These findings describe general trends in the relationship between weather and helicopter
accidents and incidents. While it provides some information about different types of
operations, including HAA, most of the findings relate to non-operationally specific
trends in helicopter events. Future research should improve awareness of weather
conditions and training to maintain control of the aircraft in windy conditions or poor
visibility conditions.
Speirs, A., Ramée, C., Payan, A. P., Mavris, D., & Feigh, K. M. (2021). Impact of
adverse weather on commercial helicopter pilot decision-making and standard
operating procedures. In AIAA Aviation 2021 Forum (p. 2771).
https://doi.org/10.2514/6.2021-2771
Introduction. Weather poses a significant challenge for helicopter pilots.
Helicopter pilots receive limited weather data in the cockpit and this can be detrimental to
their decision-making, and ultimately, their safety; weather is a factor in 28% of fatal
helicopter incidents. This study investigated the weather-related challenges faced by
helicopter pilots. Methods. Two hundred and sixteen helicopter professionals (22
helicopter pilots; 70% with HAA experience) completed a survey about their respective
demographics (i.e., crew experience), flight environment (i.e., weather conditions), and
safety operations (i.e., equipment / technologies). Nine of the surveyed pilots (three each
from the HAA, air tour / air taxi, and law enforcement industries) were interviewed using
the Applied Cognitive Task Analysis (ACTA) that consists of (a) a surface-level
interview and task diagram depicting the operation’s Standard Operating Procedures
(SOP); (b) an overview of weather-related events encountered by the pilot; and (c) a
"knowledge audit” reviewing the in-flight competencies of the pilots during adverse
weather conditions.14 Interviews were audio recorded, transcribed, and reviewed for
accuracy and common themes of interest. Results. The majority of pilots reported using
digital tools and graphical displays both before and during the flight, such as the HEMS
weather tool15 and the Flight Risk Assessment Tool (FRAT). HAA pilots reported having
access to panel-mounted displays more than other commercial helicopter pilots and were
more likely to report using these displays during weather events. Pilots used fewer
weather sources while in-flight than during the pre-flight phase. Pilots who did not view
the weather tools available to them as sufficient (29%) also frequently reported on the
scarcity of weather stations. Pilots most frequently reported on a lack of weather
14 Also covered the pilot’s opinions on their SOP, how the SOP could be improved to enhance safety, and
how they recognize when their missions will deviate from their SOP. (Minotra & Feigh, 2017, 2020).
15 Originally developed for HEMS operations. See https://www.aviationweather.gov/hemst for more
information.
21
information, sparsity of weather sensing, reliance on local weather knowledge or past
experience, impact of current technology on safety, external pressures on weather-related
decision-making, and distrust of weather information. Conclusion. Overall, pilots view
the tools at their disposal as sufficient for safe operations. However, many difficult
aspects of using and interpreting weather information were identified, suggesting that
there is room for improvement.
Training
Abrahamsen, H. B., Sollid, S. J., Öhlund, L. S., Røislien, J., & Bondevik, G. T. (2015).
Simulation-based training and assessment of non-technical skills in the
Norwegian helicopter emergency medical services: A cross-sectional
survey. Emergency Medicine Journal, 32(8), 647-653.
http://doi.org/10.1136/emermed-2014-203962
Introduction. Due to the risky nature of HEMS operations, adverse events and
injuries while on the job are not uncommon. Non-technical skills (NTS; i.e., cognitive,
social, and personal resource skills) may reduce the risk of adverse events and contribute
to a safer work environment. The purpose of this study was to assess the level of in-situ
stimulation-based training in, and assessment of, NTSs in Norwegian HEMS. Methods.
Two hundred and seven physicians, non-physician medical HCMs, and pilots working in
the civilian Norwegian HEMS completed a questionnaire covering seven NTS categories:
situation awareness, decision-making, communication, teamwork, leadership, managing
stress, and coping with fatigue. Participants indicated their maximum number of
consecutive on-call duty hours. Logistic regression was used to assess differences in
simulation-based training and assessment between professions. Fisher’s exact test was
used to explore the associations among profession, on-call duty hours, and simulation-
based training and assessment. Results. The majority of HEMS personnel lacked
simulation-based training and assessment of their NTSs, with physicians undergoing
significantly less training and NTS assessment than pilots and HCMs. HEMS personnel
training on how to cope with fatigue was severely limited; 79% of physicians who were
on-call for more than 72 consecutive hours did not have training in coping with fatigue
and 54% of pilots and HCMs who were on call for more than 3 consecutive days did not
have training in coping with fatigue. Conclusion. This study compared the frequency of
in-situ simulation-based training and assessment in Norwegian HEMS crewmembers by
occupation, and suggest that in comparison to pilots and non-physician HCMs,
22
physicians undergo less training and assessment of NTSs. While these results provide
information about the number of yearly trainings and assessments of NTSs in this setting,
future research is needed to draw conclusions about the quality of the trainings or
assessments received.
Bredmose, P. P., Hagemo, J., Østergaard, D., & Sollid, S. (2021a). Combining in-situ
simulation and live HEMS mission facilitator observation: A flexible learning
concept. BMC Medical Education, 21(1), 1-10. https://doi.org/10.1186/s12909-
021-03015-w
Introduction. In-situ simulation training can be useful in HEMS because it fuses
together the working environment with simulation technology. However, training
sessions are often interrupted by live missions, and this can be detrimental to learning.
The purpose of this study was to determine whether observation by the simulation
facilitator during live HEMS missions and post-mission debriefing would be a feasible
alternative to mission-interrupted simulation training. Methods. Three Norwegian HEMS
bases with different mission profiles in terms of the number of annual missions,
population density, and crew configuration were sampled. Data describing the number
and types of interventions (i.e. simulation or live mission observation) were collected
over a one-year period beginning in May 2016. Senior HEMS physicians served as the
facilitators and developed scenarios depending on each base mission profile. When
simulations were interrupted by live missions, facilitators joined the crews on the
missions to observe them. Facilitators debriefed crewmembers after both in-situ
simulations and live mission observations using the Promoting Excellence and Reflective
Learning in Simulation (PEARLS)16 framework. A questionnaire was administered to
facilitators and crewmembers followed by 20-minute interviews performed with
physicians, HEMS technical crewmembers and facilitators at the end of the study period
to gather more in-depth feedback. Results. Of the 78 training sessions attempted, 46
(59%) were conducted as planned, 23 (29%) were not started, and 9 (12%) were
converted to observed live missions. The Lørenskog base undertook 43 (55%) attempts to
facilitate simulation training. Ål and Ålesund bases undertook 16 (21%) and 19 (24%)
attempts to facilitate simulation training, respectively. Both in-situ simulations and live
missions received high satisfaction ratings, were seen as having an appropriate duration,
and as having included relevant SOPs. Furthermore, crewmembers did not have concerns
about exposing skills and competencies after live mission training. However, facilitators
considered live mission observation to be more challenging than in-situ observation.
16 Eppich and Cheng (2015).
23
Conclusion. This study compared the effectiveness of live-mission observation and
debriefing by a simulation facilitator to in-situ simulation training in HEMS. Overall,
facilitators and crewmembers perceived the new training concept as valuable and helpful
in terms of learning experience and overall satisfaction. Due to the on-call nature of
HEMS operations, this study offers a feasible training option for operators that make use
of in-situ simulation training. Given the limited scope of this study, research on the long-
term learning outcomes that are associated with this type of live training versus in-situ
simulation is needed to fully compare the two training types.
Bredmose, P. P., Hagemo, J., Røislien, J., Østergaard, D., & Sollid, S. (2020). In situ
simulation training in helicopter emergency medical services: Feasible for on-call
crews? Advances in Simulation, 5(1), 1-7. https://doi.org/10.1186/s41077-020-
00126-0
Introduction. In-situ simulation-based training can be effective for maintaining
the skills and competence of HEMS personnel.17 The purpose of this study was to
explore the particularities of implementing on-site (in-situ) simulation-based training in
HEMS. Methods. In-situ simulation-based training was conducted at the HEMS base of
Oslo University Hospital in Norway over the course of a year (January 2012 to December
2012). Eight patient scenarios were created by the main facilitator in consultation with a
physician and based on the mission profile of the base. The training included learning
objectives related to technical and NTS. Forty-four individual simulations were carried
out by 15 physicians, 12 HCMs, and 15 pilots in total; all but four simulations were
conducted by the whole HEMS team (i.e., physician, HCM, and pilot). Training consisted
of (a) preparing the scenario for the simulation; (b) scenario completion; (c) clean-up and
readying the equipment for the next scenario; and (d) a structured debriefing to highlight
any learning points from the simulation. A questionnaire was administered to all team
members after the training. They reported on their experience with and attitude towards
the training using a 7-point Likert scale (1 = I strongly agree, 7 = I strongly disagree).
The time needed to prepare and carry out the training in each phase18 was manually
recorded by the facilitator. Results. The total median time consumption for a simulation
training session for the on-call HEMS crew and facilitator was 65 and 75 minutes,
respectively. The preparation time for scenarios (facilitator only) was 10 minutes. The
time for simulations was 20 minutes, cleaning up after the scenario was 7 minutes, and
debriefing was 35 minutes. Crewmembers viewed the training favorably as almost all
17 Sollid et al. (2019).
18 This includes the time the facilitator spent preparing the scenario, the time the crew spent performing the
actual simulation, time spent cleaning up, and time spent in debrief.
24
(98.4%) responded with the two most positive categories on the Likert scale. Feedback
showed that crews did not see the training as disruptive to on-call work, found it easy to
motivate, and found that the organization and time devoted were sufficient. Conclusion.
This one-year prospective study provides initial support for the feasibility of in-situ
simulation-based training at an HEMS base with on-call crews. Crewmembers were
positive about their experience with the training. Crewmember involvement in the
training was deemed short as did not exceed 65 minutes. However, other factors that
influence implementation must be identified before this training concept becomes more
widely accepted. While this study provides support for the practical feasibility of in-situ
simulation-based training, learning-outcomes and quality of training should be evaluated.
See Bredmose et al. (2021b, 2021c) for more information.
Bredmose, P. P., Østergaard, D., & Sollid, S. (2021b). Challenges to the implementation
of in situ simulation at HEMS bases: A qualitative study of facilitators’
expectations and strategies. Advances in Simulation, 6(1), 1-11.
https://doi.org/10.1186/s41077-021-00193-x
Introduction. Simulation-based training is a useful tool for critical care and
emergency medicine operations such as HEMS. However, facilitators get little guidance
on how to properly implement such training and have low familiarity with their roles.
The purpose of this exploratory study was to identify factors that would challenge the
implementation of in situ-simulation-based training as well as the solutions to overcome
these challenges. Methods. In-situ simulation-based training was implemented by
physicians acting as facilitators at 11 Norwegian HEMS bases and one SAR base.
Facilitators were appointed by the local clinical leads in each base and trained using the
EuSim concept.19 Sixteen HEMS and SAR physicians were recruited for data collection
that occurred over three stages. Sixteen facilitators gathered to identify topics that they
expected would be challenging and obstructive for the implementation of the training at
their HEMS base, as well as their expectations, and use these to create the interview
guides (stage 1). Prior to the training, semi-structured group interviews were conducted
by senior consultants in anesthesiology with extensive air ambulance experience with
these facilitators using an interview guide from stage 1 (stage 2). Seven facilitators
partook in these interviews after one year of training (stage 3). Themes were identified
from stage 2 and stage 3 interviews separately using Systematic text condensation.20
Results. Seventeen themes were identified in the pre- and post-study-year interviews.
19 See the EuSim course description for more information (EuSim Group, 2015).
20 Malterud (2001, 2012).
25
Among these, pedagogical issues, timing and planning, crew- and faculty members’
expectations, and motivation were the most common (i.e., if the training was voluntary
and not mandatory it would boost motivation; having more than one facilitator at the base
could improve the motivation of the facilitator). Management support, dedicated time for
the facilitators to prepare and lead the training, and ongoing development of the
facilitator were also common. The remaining themes included expedient factors, barriers,
and suggestions for how to overcome these barriers (i.e., excessive workload was
considered a barrier that could be overcome by planning less training in busy periods like
mid-summer and holidays). Facilitators described increasing levels of motivation and
engagement in the crews over the study period, and this was regarded as a positive
development. Conclusion. Facilitators commented on the anticipated challenges to the
implementation of simulated-based training in HEMS pre- and post-one year of training.
Pedagogical, motivational, and logistical issues were the most common themes identified
after one year of training. Notably, the crews increased their level of motivation over the
study period. As motivational factors are essential for the implementation of such
programs,21 this was taken as evidence that simulation-based training is useful in HEMS.
Future research could evaluate other objective metrics of operational success to fully
support the adoption of in-situ simulation-based training for HEMS operations.
Bredmose, P. P., Røislien, J., Østergaard, D., & Sollid, S. (2021c). National
implementation of in situ simulation-based training in helicopter emergency
medical services: A multicenter study. Air Medical Journal, 40(4), 205-210.
https://doi.org/10.1016/j.amj.2021.04.006
Introduction. Patients in incidents involving the HEMS are often in need of
critical care. HCMs must have the right skills, experience, and training to provide this
care. Medical simulation-based training is an opportunity for HCMs to brush up on their
caregiving skills, however, implementing the training can be logistically challenging. To
better understand these challenges, the degree to which facilitators (HEMS physicians)
implemented in situ on-call simulation-based training as well as their perceptions towards
the training were evaluated. Methods. Facilitators at 11 Norwegian HEMS bases
(including one SAR base) implemented the simulations. At each base, 1-2 senior HEMS
physicians were selected by the lead physician and trained as simulation facilitators.
Simulation-based training was conducted by HEMS crews during the daytime on a
convenience basis. The total number of sessions or frequency of sessions to be completed
was not specified by the researchers. Standard operational procedures were followed, but
21 Hosny et al. (2017).
26
facilitators were encouraged to design novel scenarios involving crewmembers (i.e.,
pilots, physicians, and paramedics). After each attempted simulation, facilitators noted
whether the training was completed successfully (simulation and briefing were completed
regardless of any interruptions) and evaluated the degree of satisfaction with the
simulation on a visual analog scale ranging between 0 mm (completely unsatisfactory)
and 100 mm (maximum satisfaction). Results. The number of attempted simulations
across bases ranged between 1 and 46 (median = 17). Sixty-six percent of the attempted
simulations across bases were successfully completed. The number of annual missions at
each base did not significantly impact the number of simulation attempts and the number
of completed simulations. However, the number of attempted simulations was higher on
bases containing two, as opposed to one, facilitators. The number of attempted
simulations was not impacted by the facilitator’s travel distance to work. Training
sessions were interrupted on account of acute missions; fatigue and lack of motivation
had very little impact on session completion. Conclusion. This study provided a
retrospective evaluation of the adoption of in-situ simulation-based training in Norwegian
HEMS operators over the course of a one-year prospective study (see Bredmose et al.,
2020, 2021b). Overall they found that the adoption of the program and the number of
attempted simulations was impacted by the number of facilitators available, suggesting
that this is a limiting factor for further adoption of this training style. While these results
offer a retrospective evaluation of a prospective roll-out of national in-situ simulation
training for Norwegian operations, the roll-out of such training in private sector HEMS
operators would likely face distinct challenges.
Rasmussen, K., Langdalen, H., Sollid, S. J., Abrahamsen, E. B., Sørskår, L. I. K.,
Bondevik, G. T., & Abrahamsen, H. B. (2019). Training and assessment of non-
technical skills in Norwegian helicopter emergency services: A cross-sectional
and longitudinal study. Scandinavian Journal of Trauma, Resuscitation and
Emergency Medicine, 27(1), 1-10. https://doi.org/10.1186/s13049-018-0583-1
Introduction. HCMs must have the right technical and NTS, experience, and
training to deliver safe care to patients. Simulation-based training is an opportunity for
crewmembers to develop their NTS. The purpose of this study was to document the level
of simulation-based training and assessment of NTS among Norwegian HMS
crewmembers following the onset of new training initiatives by the Norwegian Air
Ambulance Foundation.22 Methods. A questionnaire was administered to 214 Norwegian
HEMS physicians, pilots, and crewmembers at 12 HEMS bases. All groups reported on
22 Bredmose and Sollid (2015); Martinsen (2015).
27
the frequency of simulation-based training and assessment of each of the seven generic
categories of NTS (situation awareness, decision-making, communication, teamwork,
leadership, stress management, and coping with fatigue) at their local base. Responses
from 109 crewmembers were retained for analysis.23 Results. Simulation-based training
and assessment increased for all but one NTS category (coping with fatigue) since the
onset of the new training initiatives. Physicians were assessed significantly more
frequently for all but two NTS (managing stress and coping with fatigue) and reported on
the most NTS categories compared to pilots and HCMs. There was no significant
difference in the frequency of training and assessment between groups. HCMs increased
the frequency of training but not the assessment of NTS. Coping with fatigue did not
significantly increase for any group. Conclusion. The frequency of simulation-based
training and assessment of NTS have increased significantly over time in the examined
professional groups. Overall, the frequency of assessment was lower than the frequency
of training. Despite a lack of homogeneity in the NTSs reported among groups, NTS
training and assessment is likely equally important to all groups and should continue to
be promoted in HEMS. Further research should additionally assess the quality of training
in achieving desired learning outcomes to better understand the impact of increased
frequency of trainings.
Other Operational Risk Factors
Aalberg, A. L., Bye, R. J., Kråkenes, T., & Evjemo, T. E. (2020). Perceived pressure to
fly predicts whether inland helicopter pilots have experienced accidents or events
with high potential. In P. Baraldi, F. Di Maio, & E. Zio (Eds.), Proceedings of the
30th European Safety and Reliability Conference and the 15th Probabilistic
Safety Assessment and Management Conference. Research Publishing.
Introduction. Accidents are common in the inland helicopter industry. Accident
rates have been found to vary according to the type of operation, phase of operation,
helicopter type, fatigue, workload, employment conditions, age of pilot and experience
(number of flight hours), competence and training, operational support from the
company, and size of the company, among other factors. The purpose of this study was to
explore which of the aforementioned factors influence the probability of pilots
23 49% (n = 53) responses were from physicians, 28% (n =31) were from HCM and 23% (n = 25) were
from pilots.
28
experiencing a situation that leads to an accident or high-potential event. Methods.
Questionnaire data was adopted for use in this study from previous research that involved
132 pilots in the domestic inland helicopter industry. Pilots self-reported on the
conditions of their work. Based on interviews with industry experts, a statistical model
was formulated to include the following variables: employment conditions, company
size, pilot age, fatigue, pressure to fly, workload/time pressure, experienced event, and
training and competence. Results. The statistical model explained 23% of the variance in
the likelihood of having experienced an event and demonstrated high goodness-of-fit.
Pressure to fly was the only significant predictor for the likelihood of experiencing
accidents or events with high potential; higher reported pressure to fly was associated
with a higher probability of having experienced an event. Fatigue was a significant
predictor before pressure to fly was included in the model, partially supporting the
finding that higher reported fatigue was associated with a higher probability of having
experienced an event. Age was a significant predictor in the model only when pressure to
fly was included. Conclusion. Among the factors associated with the probability of
critical events occurring in inland helicopter operations, pressure to fly was the strongest
predictor; it originates from many sources including low economic margins, motivation
for accumulating flight hours, contract issues, and employment conditions. The
relationship between pressure to fly, fatigue, and the likelihood of having experienced an
event warrants further investigation. Results suggest that fatigue and pressure to fly are
correlated, impacting the ability to claim cause and effect of the likelihood of having
experienced an event.
Aherne, B. B., Zhang, C., Chen, W. S., & Newman, D. G. (2019). Preflight risk
assessment for improved safety in helicopter emergency medical service
operations. Aerospace Medicine and Human Performance, 90(9), 792-799.
https://doi.org/10.3357/AMHP.5330.2019
Introduction. The purpose of this study was to develop predictive risk
assessment tools from historical accident data to support decision-making processes.
Methods. NTSB accident data between 1995 and 2013 were analyzed in this study. The
dataset consisted of 189 rotorcraft accident reports; there were 32 single-pilot night VFR
fatal HEMS accidents due to LOC or CFIT. Relative risk and odds ratios were calculated
for (a) nonsurvivable accidents for routes with positive elevation difference compared to
those with the same or lower elevation, for all flights, and those within a TDPS range of
0-4°C; and (b) accidents for flight sectors with patients compared to flights with crew
only. Logistic regression analyses were performed to develop predictive models for the
probability of accident cause, non-survival outcomes, and nonvisual meteorological
29
conditions (non-VMC). Results. Logistic regression analyses accurately predicted the
likelihood of entering non-VMC in 75% of cases, accident cause in 81% of cases, and
sustaining a nonsurvivable accident in 94% of cases. Twenty-six of the 32 fatal accidents
were nonsurvivable and 22 were flown by low-DTE pilots. The non-VMC model found
that TDPS significantly explained over 18% of the variance in non-VMC outcomes. In
the accident cause model, flight composition sector, TDPS, pilot DTE, flight rule
capability, and task type explained 55% of the variance for all flights. LOC significantly
predicted a nonsurvivable accident explaining over 19% of the variance between
nonsurvivable and survivable accidents. In a separate model, positive elevation
difference, HEMS DTE, and LOC explained over 74% of the variance in nonsurvivable
accidents. Conclusion. Results showed that preflight information can predict the
likelihood of adverse safety outcomes in a planned HEMS mission. Findings from this
study support the use of preflight analysis in safety decision making broadly, though the
small sample size in the current study limits the usability of the specific statistical model.
Future research with larger samples would be needed to fully understand how the specific
variables and risk factors described may predict adverse safety outcomes.
Bauer, H., & Herbig, B. (2019). Occupational stress in helicopter emergency service
pilots from 4 European countries. Air Medical Journal, 38(2), 82-94.
https://doi.org/10.1016/j.amj.2018.11.011
Introduction. HEMS pilots often work in conditions of extreme pressure. These
stressful work conditions combined with insufficient workplace resources could lead to
decreased motivation, skill development, emotional irritability, and in some cases,
illness,24 all of which are potential hazards to flight safety. This study examined the effect
of work conditions on work performance, work engagement, worker well-being, energy
levels, and motivation in HEMS. Methods. Questionnaire data from 72 HEMS pilots (24
Western European, 48 Eastern European; MAge= 51.9 years) employed in 2015/2016 were
obtained. The questionnaire covered different aspects of work-related demands, stressors,
resources, and symptoms of strain. Work conditions were measured by works stressor
(i.e., job insecurity, work hours, work-family conflict) and resource (i.e., social support,
role clarity, autonomy) variables. Work motivation was measured by the 9-item version
Utrecht Work Engagement Scale (UWES-9). Psychological well-being was measured by
the World Health Organization 5-item instrument (WHO-5) and energy levels (i.e., lack
of fatigue) were measured by the 4-item “Energy/Fatigue” subscale of the WHO quality
of life instrument (WHOQOL-100). Data were stratified by the participant’s region of
24 Bakker and Demerouti (2007); Glaser et al. (2015).
30
origin (Eastern or Western Europe) and age. Results. Work stressors were perceived as
medium to low stress whereas work engagement, energy, and subjective well-being were
perceived as high stress. Eastern European pilots reported less social support, lower
autonomy to use their own ideas in their work, and lower levels of explicit supervisor
feedback compared to Western European pilots. Eastern European pilots also reported
lower levels of work engagement than Western European pilots. These differences were
less pronounced between age groups. Work stressors/ resources did not predict work
engagement but did significantly predict subjective well-being and energy; pilots with the
least favorable ratings of work stressors/resources were at higher risk for ill-being in the
form of disturbed mood. Conclusion. Many of the work characteristics were rated
favorably; work stressors and resources were characterized by low to medium levels,
whereas outcomes (i.e., motivation, well-being, and energy) were characterized by high
levels. HEMS pilots strongly identify with their work, even more so than the general
workforce and airline pilots. However, resources such as support groups should be
available to continue promoting safety in HEMS.
Bauer, H., Nowak, D., & Herbig, B. (2018). Aging and cardiometabolic risk in European
HEMS pilots: An assessment of occupational old‐age limits as a regulatory risk
management strategy. Risk Analysis, 38(7), 1332-1347.
http://doi.org/10.1111/risa.12951
Introduction. A retrospective cohort study was conducted to determine the
validity of the “Age 60 Rule” imposed in aviation. Per this rule, older pilots are
prohibited from conducting operations, as they are believed to be at higher risk for
cardiovascular events.25 Cardiometabolic risk marker change rates in HEMS pilots near
or above age 60 served to measure overall incapacitation risk. Methods. The aeromedical
examination records from 66 German, Austrian, Polish, and Czech HEMS pilots
employed in 2015-2016 were obtained from the 10-year period prior to their study
participation (14.8 average number of examinations per pilot). The following risk
markers were assessed: systolic blood pressure (SBP), serum total cholesterol, serum
high-density lipoprotein cholesterol, fasting glucose, body mass index (BMI), and Q-
wave to T-wave interval (QTc interval). A cardiovascular risk score was computed using
the Systematic Coronary Risk Evaluation (SCORE) method to determine the absolute
risk of a fatal cardiovascular event in between examinations. Changes in risk marker rates
25 Note, in the United States, 14 CFR § 121.383 was revised in 2007 to allow for some operations by pilots
up to age 65. See the Fair Treatment for Experienced Pilots Act, P.L. 110-135 (Dec. 13, 2007).
31
were assessed over time.26 The relationship between age and the risk of fatal
cardiovascular events was also assessed. Results. SBP did not change significantly over
time in younger pilots but increased faster in older pilots. QTc increased with aging and
well into the 60s age range. BMI and fasting glucose in older pilots changed at a slower
rate than in younger pilots. The lipid profile improved in older pilots but was unchanged
in younger pilots. SCORE risk was estimated between 0% and 0.3%;27 the absolute
SCORE risk increased in the older, compared to the younger, HEMS pilots. Conclusion.
Age-related changes in cardiovascular risk between HEMS pilots and younger pilots
were observed, however, these results were estimated with uncertainty. Further,
individual differences explained between 41% and 95% of risk marker variability rather
than the outcome measures. Overall, the cardiometabolic risk marker profile is not likely
worse in older than in younger HEMS pilots. Incapacitation risk should be evaluated on
an individual basis, and a one-size-fits-all solution such as the “Age 60 Rule” is likely
insufficient.
Bauer, H., Nowak, D., & Herbig, B. (2020). Age, aging and physiological dysregulation
in safety–critical work: A retrospective longitudinal study of helicopter
emergency medical services pilots. International Archives of Occupational and
Environmental Health, 93(3), 301-314. https://doi.org/10.1007/s00420-019-
01482-9
Introduction. Mental and physical health is known to decline with age.28 The
purpose of this study was to assess the effect of age on the functional decline of multiple
organ systems (i.e., psychological dysregulation) in an occupational context. Professional
pilots are thought to maintain better health than age-similar workers and should therefore
demonstrate lower rates of psychological dysregulation over time compared to the overall
working population. Methods. Aeromedical examination records from 41 male German,
Austrian, Polish, and Czech Republican HEMS pilots employed in 2015-2016 were
obtained from the 10-year period prior to their study participation. The average age
ranged from 27.9 to 60.6 years. From these records, 18 biomarkers were identified and
served as an index for overall health. The aggregated estimated probabilities for lying
outside a predetermined “healthy” or “normal” biomarker range (psychological
dysregulation state), as well as the average biomarker change over time (pace of change),
26 Models were separately fitted for East (Czech Republic, Poland) and West (Austria, Germany) European
pilots.
27 SCORE risk estimates are higher for Eastern European pilots, as they hail from “high-risk” countries.
28 Farrow and Reynolds (2012); Salthouse (2012).
32
and were calculated for each participant.29 The state of psychological dysregulation was
evaluated cross-sectionally and pace of change was evaluated longitudinally. Results.
According to the cross-sectional analysis, psychological dysregulation first increased,
then decreased with age. Maximum dysregulation occurred between ages 45 and 50
years. This same negative quadratic effect of age on dysregulation state was observed in
the longitudinal analysis. Physiological dysregulation significantly increased over time,
however, the pace of change did not differ between participants with a different “average
baseline age” (the age at the first available measurement of each biomarker). Conclusion.
This study analyzed the change rates of health biomarkers over time. Dysregulation first
increased with age up until 45-50 years - after which it started to decrease, demonstrating
a curvilinear pattern. Also, the pace of change did not depend on the average baseline
age. These results are consistent with the “healthy worker survivor” effect30 and suggest
that the particularities of the work (e.g., requiring regular health examinations) influence
the health of the workers.
Bryan, C. G. (2014). An analysis of helicopter EMS accidents using HFACS: 2000-2012
[Master's Thesis, Embry-Riddle Aeronautical University].
https://commons.erau.edu/edt/31/
Introduction. This study examined archival data on HEMS accidents between
2000 and 2012 using the Human Factors Analysis and Classification System (HFACS)
taxonomy to inform human error mitigation strategies. The purpose of this study was to
associate categories of human error with physical and temporal characteristics present in
HEMS accidents. Methods. Multiple keyword searches for all helicopter accidents and a
list of accident file numbers for the total helicopter air medical accidents in the NTSB
database during the time period were merged into a single dataset. Accidents that
occurred outside of the United States and those that did not result from a patient needing
to or potentially needing to be moved were excluded resulting in a total of 147 accidents
to be analyzed. Three graduate-level HF students coded the data and achieved 80% of
agreement after two rounds of coding. HEMS accident phase of flight was coded by
considering the phase of flight (i.e., Takeoff, Transit, Landing), destination at the time of
the accident (i.e., Patient Pick-up, Patient Drop-off, Base of Operations), and type of
patient movement (i.e., Retrieval from Accident Site, Inter-hospital Transfer). Accidents
were divided into four categories: Investigation Incomplete, Unforeseeable/Unknown,
Foreseeable Mechanical Failure, or Human Error. Results. Human error underlaid over
29 Only data from participants who had measurements for at least 15 biomarkers was analyzed. Data was
stratified by participant’s region of origin (East and West Europe).
30 Arrighi and Hertz-Picciotto (1994).
33
two-thirds of the accidents analyzed in this study (101/147, 69%). HEMS accidents
occurred more frequently during landing at patient site, transit to a patient, and transit to
home base. The most frequently identified HFACS error categories were for unsafe acts
(i.e., decision errors, perceptual errors, and skill-based errors) and preconditions in the
physical environment. Rotary wing flying hours for pilots involved in human error-
related accidents was available for 89 of 101 cases. In 70% of these accidents, pilots had
between 2,000 and 6,000 hours of flying experience. Over 60% of accidents that included
natural light conditions at the time of the human error accident occurred at night. No
significant correlations between HEMS missions and accident density were found.
Conclusion. Human error is prevalent in HEMS accidents. Training and testing the
feasibility of the technology to assist pilots in detecting obstacles during degraded vision
conditions are possible strategies to mitigate accidents due to human error.
Chesters, A., Grieve, P. H., & Hodgetts, T. J. (2016). Perceptions and culture of safety
among helicopter emergency medical service personnel in the UK. Emergency
Medicine Journal, 33(11), 801-806. http://dx.doi.org/10.1136/emermed-2015-
204959
Introduction. This study assessed HEMS crewmember attitudes and perceptions
towards risks involving HEMS operations. Methods. One hundred current HEMS
crewmembers (n = 11 pilots, n = 45 doctors, n = 43 paramedics, and n = 1 other) in the
United Kingdom completed a survey by email on risk and safety culture in HEMS
operations. Results. Overall, 34% of respondents responded “No” to the primary research
questions: are “HEMS operations inherently safe?” Respondents with previous
experience of a helicopter crash were more likely to respond “No” to that question. Out
of a list of factors that could potentially contribute to a crash, participants attributed the
most risk to night HEMS operations without the use of NVG, commercial pressure, and
mechanical aircraft failure. Participants also rated factors such as the use of single-engine
aircraft, IMC, limited pilot experience, human error, and pilots not holding a current
instrument rating as factors that were “likely to contribute to a crash.” Respondents rated
landing at the scene and departing the scene as the riskiest stages of flight. The majority
(>70%) of respondents reported regular participation in risk reduction discussions,
regular discussion about risks particular to their own base, review and action of internal
incident reports, and in-flight emergency rehearsals either in flight or on base. Sixteen
respondents said that practices at their base do not fully comply with operational policies
and procedures, and seven reported that not all aviation near-misses or minor incidents
are reported for further action. Only 27% of respondents had undertaken a dedicated
CRM course, and clinical crews overall reported a lack of training in weather minimums
34
for HEMS operations (15%), HEMS aviation exemptions (14%), national aviation
regulations (21%), and HEMS landing procedures (8%). Conclusion. The results
provided insight into perceptions of safety culture and risk among HEMS crewmembers
in the United Kingdom. Crewmembers largely perceive HEMS operations as inherently
safe and largely report positive aspects of safety culture related to organizational policy
and practices. However, a number of operational risk factors were identified by
crewmembers that enhance the likelihood of an accident. Additionally, areas for growth
related to clinical crew training and overall operator practices were noted and provided.
Cline, P. E. (2018). Human error analysis of helicopter emergency medical services
(HEMS) accidents using the human factors analysis and classification system
(HFACS). Journal of Aviation/Aerospace Education & Research, 28(1).
https://doi.org/10.15394/jaaer.2018.1758
Introduction. The purpose of this study was to understand the factors that
contribute to HEMS accidents using HFACS. Methods. Forty-four HEMS accidents
from the NTSB’s Aviation Accident Database between 2000 and 2016 were analyzed in
this study. Only data from operations within the United States that were conducting
HEMS at the time of the accident were used. Of the 44 accidents, 107 independent causal
factors were evaluated. HFACS framework was used to classify causal factors of each
accident. Each HFACS error or violation category was used only once per accident.
Results. The majority of the 44 accidents examined were made up of some kind of skill-
based error (80%), followed by perceptual errors (52%), supervisory errors (52%),
decisional errors (41%), and exceptional violations (16%). Of the 36 skill-based error
accidents, 56% resulted in fatalities, and all fatal accidents in this study involved skill-
based error. Failure to maintain control (50%) and failure to maintain clearance (33%)
made up the majority of causal factors due to skill-based errors. Accidents due to
perceptual errors were primarily caused by IMC (30%) and occurred at night (30%).
Accidents due to supervisory errors were primarily caused by inadequate operational
supervision (57%). Accidents due to decision errors were primarily due to aeronautical
decision-making (56%). Conclusion. Results suggest that the majority of HEMS
accidents were due to skill-based errors and that skill-based errors were associated with
fatal accidents.
De Voogt, A., Hohl, C. H., & Kalagher, H. (2021). Fatality and operational specificity of
helicopter accidents on the ground. Aerospace Medicine and Human
Performance, 92(7), 593-596. https://doi.org/10.3357/AMHP.5801.2021
35
Introduction. The purpose of this study was to investigate the characteristics of
helicopter accidents when they are standing on the ground. Methods. One hundred and
fifteen helicopter accidents from the NTSB online database that occurred during the
‘standing’ or grounded phase of flight between 1998 and 2018 were analyzed in this
study. Results. Standing helicopter accidents made up 115 of 3,291 helicopter accidents
identified between 1998 and 2018. Chi-square tests were performed to determine
differences between expected and observed frequencies of accident factors. Most
helicopter accidents occurred in Alaska (N = 15), California (N = 10), and Florida (N =
10). Accidents in Alaska were off-airport in 13 of 15 cases and were significantly more
frequent than in other states combined. However, accidents in Alaska did not include any
fatalities. Fatal accidents or serious injuries were less frequent when the aircraft was
substantially damaged or destroyed, which may be explained by the occurrence of roll-
over accidents where damage to the aircraft is often substantial while serious injury is
rare. For all 10 fatal accidents in the dataset, a rotor strike was the cause and 8 of these
cases were causally attributed to the victim’s actions. High winds and gusts were also
causal factors in accidents. Conclusion. Results suggest that pilots, passengers, and
crewmembers are at risk when they are outside near a standing helicopter while the rotors
are still moving. Helicopter manuals should highlight the dangers of wind and gusts
specifically when standing, loading/unloading passengers, and during start-up and shut-
down procedures.
Gardner, R. W. (2017). The effects of SMS implementation on safety culture within
helicopter emergency medical services [Master's Thesis, University of North
Dakota]. https://commons.und.edu/theses/369/
Introduction. The purpose of this study was to determine whether safety
management systems (SMSs), safety culture, or a lack thereof influence the perceptions
of HAA operators and crewmembers. Methods. Twenty-nine participants completed the
survey. Part 135 HAA pilots (N = 16), paramedics (N = 5), and flight nurses (N = 8)
responded to questions about their perceived ability to communicate freely, belief that
their organization’s culture was a Just culture, and the effectiveness of hazard mitigation
protocols used in the industry. Results. Participants were divided into three groups based
on job roles (pilots, paramedics, flight nurses). The only statistical difference between the
three groups was in the perception that “crews’ decision making is more important to
management than the use of technological upgrades.” Further comparisons indicated that
paramedics more strongly agreed with this statement than flight nurses, but pilots did not
differ from either group. Participant’s perceptions of their respective operation having a
“Just Culture” was compared based on years of experience. Participant’s perceptions that
36
their operation has a “Just Culture” were significantly greater for participants with 20
years or more of experience compared to participants with 1-5 and 15-19 years of
experience. Conclusion. Overall, SMS has been received fairly well among personnel in
these HAA operations and there are likely minimal differences in perceptions of safety
culture across different HAA job roles.
Gaździńska, A., Jagielski, P., & Gałązowski, R. (2020). Assessment of physical activity
of members of the helicopter emergency medical service (HEMS). Emergency
Medical Service, 6(2). http://doi.org/10.36740/EmeMS202002103
Introduction. The physical activity of HEMS team members (e.g., paramedics
and pilots) was assessed alongside factors responsible for motivating participation in
physical activity. Methods. One hundred and thirty one HEMS team members (65
paramedics, 66 pilots; age range 27-59 years) from all rescue helicopter bases in Poland
participated in this study. A proprietary questionnaire was administered to participants.
The questionnaire covered different aspects of physical activity such as the frequency of
the activity, the choice of forms of physical activity, motivation for undertaking physical
activity, as well as barriers preventing regular activities. Other health factors, such as
BMI were measured. Results. Body weight did not significantly differ between pilots and
paramedics. However, pilots had poorer nutritional health than paramedics. BMI did not
significantly differ with age but did differ with the amount of physical activity reported
by paramedics; paramedics who exercised three or more times per week were more
frequently within normal BMI ranges compared to pilots. Paramedics rated physical
exercise more favorably than pilots; pilots held the opinion that physical activity was
more for maintaining or improving health than for leisure. Conclusion. Physical activity
differed between pilots and paramedics, both in terms of perceptions towards physical
activity and the amount of physical activity partaken in a given week. The main motive
for engaging in physical exercise for pilots was maintaining and improving health (47%),
whereas the main motive for paramedics was well-being (63%). Physical activity is not
simply limited to improving physical health; it can also improve mental health through
reduced stress, both of which are important for HEMS operations.
Greenhaw, R., & Jamali, M. (2021). Medical helicopter accident review: Causes and
contributing factors (Report No. DOT/FAA/AM-21/19). Federal Aviation
Administration, Office of Aerospace Medicine.
https://rosap.ntl.bts.gov/view/dot/57283
Introduction. The purpose of this study was to examine differences in EMS and
non-EMS helicopter accident rates and trends from fatal and non-fatal accidents and
37
identify contributing factors that result in helicopter accidents. Methods. Data were
retrieved from the NTSB aviation accident database between 1999 and 2018, including
event time, date, location, aircraft type, pilot and crewmembers, light and weather
conditions, inspection records, and other parameters. Data were screened for only those
cases that occurred in the United States and did not include homemade or military
helicopters. The remaining cases were split by EMS helicopters (n = 206 accidents) and
non-EMS helicopters (n = 2,832 accidents). The NSTB database includes causal and
contributing factors only for events after 2007 involving: (a) Aircraft/Mechanical; (b)
Visibility/Darkness; (c) Other Weather; (d) Object/Terrain Encounter; (e) Organizational
Compliance; (f) Pilot Decision Making/Judgment; (g) Pilot Experience; (h) Pilot
Incapacitation; (i) Pilot Attention/Orientation Issues; and (j) Pilot Flight Preparation.
Multivariate logistic regression analyses were performed to evaluate the relationship
between outcomes in group membership (EMS helicopters/non-EMS helicopters and
fatal/non-fatal EMS helicopter accidents) and predictor variables. Results. Overall, EMS
and non-EMS helicopter accidents decreased between 1999 and 2018 and fatal accident
rates did not differ between EMS and non-EMS helicopter flights. However, the EMS
accident percentage was greater than the non-EMS percentage for Pilot
Attention/Orientation Issues, Pilot Decision Making/Judgment, and Visibility/Darkness
contributing factors. Conclusion. Results found that accident and fatal accident rates for
both EMS and non-EMS helicopter missions have decreased over time but fatal accidents
are higher for EMS helicopter events than for non-EMS helicopter events. In addition,
causal and contributing factors were identified. Future research should further examine
differences in fatal and non-fatal EMS accidents.
Hinkelbein, J., Schwalbe, M., & Genzwuerker, H. V. (2010). Helicopter emergency
medical services accident rates in different international air rescue systems. Open
Access Emergency Medicine, 2, 45. https://doi.org/10.2147%2Foaem.s9120
Introduction. Approximately two to four crashes occur each year in Germany’s
civilian HEMS. Some result in fatal outcomes. HEMS crash rates and fatal crash rates in
Germany were compared to the United States and Australia using a time-based approach
to determine the safety of the HEMS. Methods. Accident rate data between 1970 and
2009 were obtained from a MEDLINE search. Reviews, letters to the editor, case reports,
case series, and meta-analyses were reviewed in addition to published studies. Data were
reviewed by two specialists in anesthesiology with expertise in air rescue; data rated
eligible were binned into 5-year increments for analysis. One-thousand and fifty-three
studies were identified in this 40 year span, however, only eleven studies dealt with
HEMS accidents on the basis of 10,000 missions or 100,000 flying hours. These eleven
38
studies (seven from the United States, five from Germany, and two from Australia) were
retained for analysis. Results. In Germany, the crash rate per 10,000 missions was 0.4
and the fatal crash rate per 10,000 missions was 0.04. In the United States, the crash rate
per 10,000 missions was 3.05 and the fatal crash rate per 10,000 missions was 2.12. In
Australia, the crash rate per 10,000 missions was 0.6 and the fatal crash rate per 10,000
missions was 0.2. There was a fivefold increase in the accident rate in the United States
compared to that of Germany and Australia. In Germany, the crash rate per 100,000
flying hours was 10.9 and the fatal crash rate per 100,000 flying hours was between 0.91
and 4.1. In the United States, the crash rate per 100,000 flying hours was between 1.7 and
13.4 and the fatal crash rate per 100,000 flying hours was between 1.61 and 4.7. In
Australia, the crash rate per 100,000 flying hours was 4.38 and the fatal crash rate per
100,000 flying hours was 1.46. Conclusion. Overall, results found that the United States
had higher accident and fatal accident rates in HEMS operations in comparison to
German and Australian operations. However, differences/omissions in published data,
use of different time frames of HEMS missions, and differences in HEMS systems make
direct comparisons between these HEMS systems difficult.
Lunde, A., & Braut, G. S. (2019). Overcommitment: Management in helicopter
emergency medical services in Norway. Air Medical Journal, 38(3), 168-173.
https://doi.org/10.1016/j.amj.2019.03.003
Introduction. The high-risk scenarios that lead to requests for HEMS put
responders at risk of overcommitment due to individual and professional drives to save
lives. This qualitative focus group study aimed to investigate individual and
organizational strategies aimed at preventing overcommitment and associated risks.
Methods. Nine crews made up of 30 total crewmembers (10 pilots) participated in focus
groups that included a short background presentation followed by a moderated discussion
that thematically covered (a) associations with the concept of overcommitment; (b)
recognition and sharing of operational cues; (c) causal factors in overcommitment; (d)
preventative factors in overcommitment; and (e) overcommitment and learning. Results.
Analysis of focus group data identified keywords associated with the prevention of
overcommitment in hazardous situations including Anticipation, Contingency Planning,
Communication, Cue Recognition, Equipment & Sensors, Experience, Risk &
Vulnerability Awareness, Quality & Flow of Information, Training & Preparedness,
Standard Procedures, and Teamwork Behavior. Crewmembers noted that early phases of
start-up operations may be at risk for overcommitment due to highly motivated but less-
trained rescue workers, and they emphasized how experience, teamwork, and
communication are key to combatting this behavior. Conclusion. This exploratory focus
39
group study identifies a number of tactics identified by HEMS crews to counteract
overcommitment. Overall, this study supports an increased focus on inter-organizational
CRM-like training to provide a foundation for a team-based approach to adjust the level
of commitment in high-stakes HEMS missions. However, the conclusions should be
interpreted with the caveat that the ultimate responsibility in accepting or rejecting a
flight may differ across international standards, and therefore tactics to prevent
overcommitment may need to be adjusted for American HAA settings.
Müller, A., Prohn, M. J., Huster, K. M., Nowak, D., Angerer, P., & Herbig, B. (2014).
Pilots’ age and incidents in helicopter emergency medical services: a 5-year
observational study. Aviation, Space, and Environmental Medicine, 85(5), 522-
528. http://doi.org/10.3357/ASEM.3861.2014
Introduction. The purpose of this study was to identify the factors that jeopardize
safety in HEMS operations that are so critical to patient care. Age may be one such risk
factor; older pilots are believed to be at higher risk than younger pilots for being involved
in an incident due to the known decrease of cognitive abilities over time.31 In particular,
this study assessed the association between the age of pilots and incidents in HEMS
involving at least one Liability Damage (LD) over a five year period. Methods. Incident
and person-related data from 257 Austrian and German HEMS pilots (3 female, 254
male; MAge = 44.52 years [2007] and 46.57 years [2011]) active between 2007 and 2011
was obtained. Incidents were operationalized as the number of claims made on an LD for
an individual over this five year period. Data was supplemented in each incomplete year
by multiplying the average number of LD by the number of months where the data was
not obtained. Missing LD data was imputed via multiple imputation32. Results. One-
thousand seven-hundred and seventy LDs were observed that involved property damage
or person-related injuries. There were approximately 4 LDs per 1,000 operations making
the overall risk of being involved in one LD during an operation low. The number of LD
increased over time; this general trend was observed within age groups. There was no
significant effect of age on LD; however, there was a significant effect of age on the
change patterns of LD over time. Older and younger pilots displayed different growth
curves on LD over time, with younger pilots showing greater increases in LDs over time.
Conclusion. Results do not support the assumption that the number of incidents increases
31 Hardy and Parasuraman (1997); Stone (1993).
32 Pilots with missing LD data were significantly younger and had less flight experience than pilots with
complete data. Therefore, the data was not missing at random and was supplemented using 20 different
simulated data sets. Multiple imputation has been shown to produce unbiased parameter estimates for
missing data (Schafer & Graham, 2002).
40
with age. Rather, the results support the hypothesis that the development of LD patterns
changes with age; there were age-differences in the change rate of LD over time. Instead,
LD increased at a faster rate in younger rather than older pilots, suggesting that over time
older pilots were involved in less errors than younger pilots.
Rikken, Q. G., Mikdad, S., Mota, M. T. C., De Leeuw, M. A., Schober, P., Schwarte, L.
A., & Giannakopoulos, G. F. (2021). Operational experience of the Dutch
helicopter emergency medical services (HEMS) during the initial phase of the
COVID-19 pandemic: Jeopardy on the prehospital care system? European
Journal of Trauma and Emergency Surgery, 47(3), 703-711.
https://doi.org/10.1007/s00068-020-01569-w
Introduction. The HEMS and HEMS-ambulance deliver prehospital medical care
to severely injured and critically ill patients. The purpose of this study was to assess the
effect of the COVID-1933 pandemic on the incidence of trauma-related injuries and the
emergency medical response to these injuries. The incidence, type, and characteristics of
Dutch HEMS and HEMS-ambulance “Lifeliner 1”34 dispatches were compared between
the start of the COVID-19 nationwide lockdown orders and on year prior. Methods. The
Dutch HEMS and HEMS-ambulance dispatches in the “Lifeliner 1” operational area for a
two-month period in 2019, and again in 2020, were reviewed for dispatch, operational,
patient, injury, and on-site treatment characteristics. The rate of positively tested COVID-
19 HEMS personnel and the time that physicians were unable to take a call was also
assessed. Results. The number of HEMS (helicopter and ambulance) dispatches
significantly differed between pandemic and non-pandemic circumstances; HEMS
“Lifeliner 1” was requested in 528 cases during the initial phase of the pandemic and in
630 cases one year prior. Of these, 298 (56.4%) of the COVID-19 cases and 314 (50.7%)
of cases one year prior were cancelled. Further, the dispatch and cancellation rate differed
over time such that week 2 and week 4 rates during the study period were less than the
same weeks one year prior. Helicopter dispatches were more frequent than ambulance
dispatches during the pandemic. Incident location type (i.e., the number of injuries that
occurred at home), mechanisms of injury (e.g., self-inflicted, trauma-related, violence-
related), and prehospital interventions (e.g., prehospital incubation, resuscitative efforts)
did not differ between pandemic and non-pandemic circumstances. Three out of 13
(23.1%) HEMS personnel tested positive for COVID-19. Physicians who tested positive
were unable to take call for 25 days on average. Conclusion. The number of HEMS
33 Coronavirus Disease 2019.
34 The Dutch ambulance helicopter (Lifeliner 1) services up to 80% of the Dutch population due to its
operational location (Giannakopoulos et al., 2010; Giannakopoulos, et al., 2013).
41
deployments and cancelled missions significantly differed between pandemic and non-
pandemic circumstances, with more mission cancellations and fewer deployments in the
COVID-19 study period. Incident location type, mechanisms of injury, and prehospital
interventions were not found to differ between circumstances. Future efforts should focus
on the mental health aspects of the COVID-19 pandemic on HEMS operations.
Strauss, M., Dahmen, J., Hutter, S., Brade, M., & Leischik, R. (2021). Rescue operations
lead to increased cardiovascular stress in HEMS crewmembers: A prospective
pilot study of a German HEMS cohort. Journal of Clinical Medicine, 10(8), 1602.
https://doi.org/10.3390/jcm10081602
Introduction. HEMS operations are high-risk and high-stress, and likely pose a
threat to cardiovascular health for these reasons. The purpose of this study was to
compare the cardiovascular stress profile of HCMs during rescue operations to the
cardiovascular profile during the resting phase between rescue situations (standby time)
same-day. Methods. Twenty-one HCMs (1 female, 20 male; MAge = 40.6 years, SD = 7.7)
at a German rescue helicopter base participated in this study. Heart Rate (HR), SBP, and
the rate of cardiac events35 (e.g., arrhythmia, extrasystoles) were assessed in HCMs
performing 52 total rescue operations to assess cardiovascular load. Long-term
electrocardiography (ECG) was measured continuously over the working day to assess
the rate of cardiac events. HR, long-term ECG, and long-term ambulatory blood pressure
measurement devices recorded continuously throughout the day. Results. All measures
were compared to their occurrence in “rescue operation” time compared to “standby”
time. This comparison was made using a random-effects linear regression model. SBP
increased by 7.4 ± 9.0 mmHg, on average, from standby time to rescue operation time, CI
[5.1- 9.7]. Further, blood pressure mean and maximum were significantly higher during
rescue operation time. MHR was 13 bpm higher during rescue operation time than on
standby time (CI [10.8- 15.3]). Further, maximum HR was 33.7 bpm higher, on average
(CI [26.2- 40.8]). The rate of cardiac events was significantly higher during rescue
operations than during standby time; the event rate increased from 11 per hour to 16.7 per
hour. Conclusion. SBP, HR, and rate of cardiac events were higher during rescue
missions than during standby time. Thus, rescue operations likely impose a significant
load on the cardiovascular system during rescue operations. HCMs should be screened
for cardiovascular health prior to participating in rescue operations to prevent
cardiovascular events.
35 Cardiovascular risk scores were computed from the European Society of Cardiology (ESC) risk score
and based on a 10-year projection but are not a primary result.
42
References
Note: An asterisk (*) indicates the reference has been annotated in this report.
*Aalberg, A. L., Bye, R. J., Kråkenes, T., & Evjemo, T. E. (2020). Perceived pressure to
fly predicts whether inland helicopter pilots have experienced accidents or events
with high potential. In P. Baraldi, F. Di Maio, & E. Zio (Eds.), Proceedings of the
30th European Safety and Reliability Conference and the 15th Probabilistic
Safety Assessment and Management Conference. Research Publishing.
*Abrahamsen, H. B., Sollid, S. J., Öhlund, L. S., Røislien, J., & Bondevik, G. T. (2015).
Simulation-based training and assessment of non-technical skills in the
Norwegian helicopter emergency medical services: A cross-sectional
survey. Emergency Medicine Journal, 32(8), 647-653.
http://doi.org/10.1136/emermed-2014-203962
*Aherne, B., Newman, D., & Chen, W. S. (2021). Acute risk in helicopter emergency
medical service transport operations. Health Science Journal, 15(1), 0-0.
*Aherne, B. B., Zhang, C., Chen, W. S., & Newman, D. G. (2018). Pilot decision making
in weather-related night fatal helicopter emergency medical service
accidents. Aerospace Medicine and Human Performance, 89(9), 830-836.
https://doi.org/10.3357/AMHP.4991.2018
*Aherne, B. B., Zhang, C., Chen, W. S., & Newman, D. G. (2019). Preflight risk
assessment for improved safety in helicopter emergency medical service
operations. Aerospace Medicine and Human Performance, 90(9), 792-799.
https://doi.org/10.3357/AMHP.5330.2019
*Aherne, B. B., Zhang, C., Chen, W. S., & Newman, D. G. (2019). Systems safety risk
analysis of fatal night helicopter emergency medical service accidents. Aerospace
Medicine and Human Performance, 90(4), 396-404.
https://doi.org/10.3357/AMHP.5180.2019
*Aherne, B. B., Zhang, C., & Newman, D. G. (2016). Pilot domain task experience in
night fatal helicopter emergency medical service accidents. Aerospace Medicine
and Human Performance, 87(6), 550-556.
http://doi.org/10.3357/AMHP.4454.2016
Airman: Limitations on Use of Services, 14 CFR 121.383 (2018).
https://www.ecfr.gov/current/title-14/chapter-I/subchapter-G/part-121/subpart-
M/section-121.383
43
*Akter, R. (2021). Socio-demographic and lifestyle factors associated with abnormal
excessive daytime sleepiness in Norwegian military search and rescue helicopter
personnel – A cross-sectional study [Master’s thesis, University of Oslo].
https://www.duo.uio.no/bitstream/handle/10852/89629/INTHE4012_114.pdf?seq
uence=1
Arrighi H.M., Hertz-Picciotto, I. (1994). The evolving concept of the healthy worker
survivor effect. Epidemiology, 5,189–196.
Bakker, A. B., & Demerouti, E. (2007). The job demands‐resources model: State of the
art. Journal of Managerial Psychology, 22(3), 309-328.
https://doi.org/10.1108/02683940710733115
*Bauer, H., & Herbig, B. (2019). Occupational stress in helicopter emergency service
pilots from 4 European countries. Air Medical Journal, 38(2), 82-94.
https://doi.org/10.1016/j.amj.2018.11.011
*Bauer, H., Nowak, D., & Herbig, B. (2018). Aging and cardiometabolic risk in
European HEMS pilots: An assessment of occupational old‐age limits as a
regulatory risk management strategy. Risk Analysis, 38(7), 1332-1347.
http://doi.org/10.1111/risa.12951
*Bauer, H., Nowak, D., & Herbig, B. (2020). Age, aging and physiological dysregulation
in safety–critical work: A retrospective longitudinal study of helicopter
emergency medical services pilots. International Archives of Occupational and
Environmental Health, 93(3), 301-314. https://doi.org/10.1007/s00420-019-
01482-9
*Bredmose, P. P., Hagemo, J., Østergaard, D., & Sollid, S. (2021). Combining in-situ
simulation and live HEMS mission facilitator observation: A flexible learning
concept. BMC Medical Education, 21(1), 1-10. https://doi.org/10.1186/s12909-
021-03015-w
*Bredmose, P. P., Hagemo, J., Røislien, J., Østergaard, D., & Sollid, S. (2020). In situ
simulation training in helicopter emergency medical services: Feasible for on-call
crews? Advances in Simulation, 5(1), 1-7. https://doi.org/10.1186/s41077-020-
00126-0
*Bredmose, P. P., Østergaard, D., & Sollid, S. (2021). Challenges to the implementation
of in situ simulation at HEMS bases: A qualitative study of facilitators’
expectations and strategies. Advances in Simulation, 6(1), 1-11.
https://doi.org/10.1186/s41077-021-00193-x
44
*Bredmose, P. P., Røislien, J., Østergaard, D., & Sollid, S. (2021). National
implementation of in situ simulation-based training in helicopter emergency
medical services: A multicenter study. Air Medical Journal, 40(4), 205-210.
https://doi.org/10.1016/j.amj.2021.04.006
Bredmose, P. P., & Sollid, S. (2015, December). Weekly simulation for an on call
helicopter emergency medical crew: feasible or impossible? Scandinavian
Journal of Trauma, Resuscitation and Emergency Medicine, 23(2), 1.
https://doi.org/10.1186/1757-7241-23-S2-A23
Briefing of Medical Personnel, 14 CFR 135.621 (2014).
Brosschot, J. F., Gerin, W., & Thayer, J. F. (2006). The perseverative cognition
hypothesis: A review of worry, prolonged stress-related physiological activation,
and health. Journal of Psychosomatic Research, 60(2), 113−24.
https://doi.org/10.1016/j.jpsychores.2005.06.074
*Bryan, C. G. (2014). An analysis of helicopter EMS accidents using HFACS: 2000-2012
[Master's Thesis, Embry-Riddle Aeronautical University].
https://commons.erau.edu/edt/31/
*Bushmaker, R., Corey, K., Dunn, J., Lalonde, T., & Estrada, S. (2019). Evaluation of a
new helicopter crew transport fatigue assessment. Air Medical Journal, 38(3),
198-201. https://doi.org/10.1016/j.amj.2018.11.006
Caldwell J. A., Jr (1997). Fatigue in the aviation environment: An overview of the causes
and effects as well as recommended countermeasures. Aviation, space, and
environmental medicine, 68(10), 932–938.
Certification: Pilots, Flight Instructors, and Ground Instructors, 14 CFR § 61 (1997).
https://www.ecfr.gov/current/title-14/chapter-I/subchapter-D/part-61
*Chesters, A., Grieve, P. H., & Hodgetts, T. J. (2016). Perceptions and culture of safety
among helicopter emergency medical service personnel in the UK. Emergency
Medicine Journal, 33(11), 801-806. http://dx.doi.org/10.1136/emermed-2015-
204959
*Cline, P. E. (2018). Human error analysis of helicopter emergency medical services
(HEMS) accidents using the human factors analysis and classification system
(HFACS). Journal of Aviation/Aerospace Education & Research, 28(1).
https://doi.org/10.15394/jaaer.2018.1758
45
Crognale, M. A., & Krebs, W. J. (2011). Helicopter pilot performance: Inadvertent flight
into instrument meteorological conditions. International Journal of Aviation
Psychology, 21(3), 235–253. https://doi.org/10.1080/10508414.2011.582443
*De Voogt, A., Hohl, C. H., & Kalagher, H. (2021). Fatality and operational specificity
of helicopter accidents on the ground. Aerospace Medicine and Human
Performance, 92(7), 593-596. https://doi.org/10.3357/AMHP.5801.2021
*De Voogt, A., Kalagher, H., & Diamond, A. (2020). Helicopter pilots encountering fog:
An analysis of 109 accidents from 1992 to 2016. Atmosphere, 11(9), 994.
https://doi.org/10.3390/atmos11090994
Definitions, 49 CFR § 830.2 (2022). https://www.ecfr.gov/current/title-49/subtitle-
B/chapter-VIII/part-830/subpart-A/section-830.2
Eppich, W., & Cheng, A. (2015). Promoting excellence and reflective learning in
simulation (PEARLS): Development and rationale for a blended approach to
health care simulation debriefing. Simulation in Healthcare, 10(2), 106-115.
http://doi.org/10.1097/SIH.0000000000000072
EuSim Group (2015). Simulation Instructor Course. EuSim.
https://eusim.org/courses/#EuSim
FAA Modernization and Reform Act of 2012, P.L. 112-095 (2012).
https://www.govinfo.gov/app/details/PLAW-112publ95
Fair Treatment for Experienced Pilots Act, P.L. 110-135 (Dec. 13, 2007).
https://www.govinfo.gov/app/details/PLAW-110publ135
Farrow, A., Reynolds, F. (2012). Health and safety of the older worker. Occupational
Medicine, 62, 4–11.
Federal Aviation Administration. (2020). General Aviation and Part 135 Activity Surveys
(2007-2020). Retrieved Jan. 9, 2023 from
https://www.faa.gov/data_research/aviation_data_statistics/general_aviation
Federal Aviation Administration. (2014). Helicopter air ambulance, commercial
helicopter, and Part 91 helicopter operations, 79 F.R. 9931.
https://www.federalregister.gov/documents/2014/02/21/2014-03689/helicopter-
air-ambulance-commercial-helicopter-and-part-91-helicopter-operations
Federal Aviation Administration. (2015). Helicopter air ambulance operations (Advisory
Circular No. AC 135-14B).
46
https://www.faa.gov/regulations_policies/advisory_circulars/index.cfm/go/docum
ent.information/documentid/1027108
Federal Aviation Administration. (2019). IFR operations at locations without weather
reporting, 84 F.R. 35820.
https://www.federalregister.gov/documents/2019/07/25/2019-15840/ifr-
operations-at-locations-without-weather-reporting
Federal Aviation Administration. (2022, April). Rotorcraft Monthly Accident Briefing
[PowerPoint Presentation]. Helicopter Air International, Safety Statistics.
https://rotor.org/wp-content/uploads/2022/05/07-FY2022-Apr.pdf
*Flaa, T. A., Bjorvatn, B., Pallesen, S., Røislien, J., Zakariassen, E., Harris, A., & Waage,
S. (2021). Subjective and objective sleep among air ambulance
personnel. Chronobiology International, 38(1), 129-139.
https://doi.org/10.1080/07420528.2020.1802288
*Flaa, T. A., Bjorvatn, B., Pallesen, S., Zakariassen, E., Harris, A., Gatterbauer-Trischler,
P., & Waage, S. (2022). Sleep and sleepiness measured by diaries and actigraphy
among Norwegian and Austrian helicopter emergency medical service (HEMS)
pilots. International Journal of Environmental Research and Public
Health, 19(7), 4311. https://doi.org/10.3390/ijerph19074311
*Flaa, T. A., Harris, A., Bjorvatn, B., Gundersen, H., Zakariassen, E., Pallesen, S., &
Waage, S. (2019). Sleepiness among personnel in the Norwegian air ambulance
service. International Archives of Occupational and Environmental Health, 92(8),
1121-1130. https://doi.org/10.1007/s00420-019-01449-w
*Fletcher, A., Stewart, S., Heathcote, K., Page, P., & Dorrian, J. (2022). Work schedule
and seasonal influences on sleep and fatigue in helicopter and fixed-wing aircraft
operations in extreme environments. Scientific Reports, 12(1), 1-13.
https://doi.org/10.1038/s41598-022-08996-2
Flight Time Limitations and Rest Requirements: One or Two Pilot Crews, 14 CFR
91.1059 (2017). https://www.ecfr.gov/current/title-14/chapter-I/subchapter-F/part-
91/subpart-K/subject-group-ECFRc17623c0e0be17e/section-91.1059
Flight Time Limitations and Rest Requirements: Unscheduled One- and Two-Pilot
Crews, 14 CFR § 135.267 (2021). https://www.ecfr.gov/current/title-14/chapter-
I/subchapter-G/part-135/subpart-F/section-135.267
47
*Gardner, R. W. (2017). The effects of SMS implementation on safety culture within
helicopter emergency medical services [Master's Thesis, University of North
Dakota]. https://commons.und.edu/theses/369/
*Gaździńska, A., Jagielski, P., & Gałązowski, R. (2020). Assessment of physical activity
of members of the helicopter emergency medical service (HEMS). Emergency
Medical Service, 6(2). http://doi.org/10.36740/EmeMS202002103
General Operating and Flight Rules, 14 CFR § 91 (2022).
https://www.ecfr.gov/current/title-14/chapter-I/subchapter-F/part-91
Giannakopoulos, G. F., Kolodzinskyi, M. N., Christiaans, H. M., Boer, C., de Lange-de
Klerk, E. S., Zuidema, W. P., Wietse, P., Bloemers, F.W., & Bakker, F. C. (2013).
Helicopter emergency medical services save lives: outcome in a cohort of 1073
polytraumatized patients. European Journal of Emergency Medicine, 20(2), 79-
85.
Giannakopoulos, G. F., Lubbers, W. D., Christiaans, H. M., van Exter, P., Bet, P., Hugen,
P. J., Innemee, G., Schubert, E., de Lange Klerk, E.S.M., Goslings, C., & Jukema,
G. N. (2010). Cancellations of (helicopter-transported) mobile medical team
dispatches in the Netherlands. Langenbeck's Archives of Surgery, 395(6), 737-
745.
Glaser, J., Seubert, C., Hornung, S., & Herbig, B. (2015). The impact of learning
demands, work-related resources, and job stressors on creative performance and
health. Journal of Personnel Psychology, 14(1), 37.
*Greenhaw, R., & Vanesco, J.M.. (2021). Medical helicopter accident review: Causes
and contributing factors (Report No. DOT/FAA/AM-21/19). Federal Aviation
Administration, Office of Aerospace Medicine.
https://rosap.ntl.bts.gov/view/dot/57283
Gurubhagavatula, I., Barger, L. K., Barnes, C. M., Basner, M., Boivin, D. B., Dawson,
D., Drake, C. L., Flynn-Evans, E. E., Mysliwiec, V., Patterson, P. D., Reid, K. J.,
Samuels, C., Shattuck, N. L., Kazmi, U., Carandang, G., Heald, J. L., & Van
Dongen, H. (2021). Guiding principles for determining work shift duration and
addressing the effects of work shift duration on performance, safety, and health:
guidance from the American Academy of Sleep Medicine and the Sleep Research
Society. Journal of Clinical Sleep Medicine, 17(11), 2283–2306.
https://doi.org/10.5664/jcsm.9512
48
*Haber Kamine, T., Dhanani, H., Wilcox, S., Kelly, E., Alouidor, R., Kramer, K., Carey,
Y., Ryb, G., Putnam, A.T., Winston, E., & Cohen, J. (2022). American helicopter
emergency medical service pilots report to work despite high rates of sleepiness.
Air Medical Journal, 41(5), 432-434. https://doi.org/10.1016/j.amj.2022.07.005
Hardy, D.J., Parasuraman, R. (2017). Cognition and flight performance in older pilots.
Journal of Experimental Psychology Applications, 3(4), 313-48.
Helicopter Air Ambulance, 14 CFR § 135 (Subpart L) (2014).
https://www.ecfr.gov/current/title-14/chapter-I/subchapter-G/part-135/subpart-L
Helicopter Hospital Emergency Medical Evacuation Service (HEMES), 14 CFR §
135.271 (2021). https://www.ecfr.gov/current/title-14/chapter-I/subchapter-
G/part-135/subpart-F/section-135.267
Helicopter Terrain Awareness and Warning System (HTAWS), 14 CFR § 135.605
(2017). https://www.ecfr.gov/current/title-14/chapter-I/subchapter-G/part-
135/subpart-L/section-135.605
*Hinkelbein, J., Schwalbe, M., & Genzwuerker, H. V. (2010). Helicopter emergency
medical services accident rates in different international air rescue systems. Open
Access Emergency Medicine, 2, 45. https://doi.org/10.2147%2Foaem.s9120
Hosny, S. G., Johnston, M. J., Pucher, P. H., Erridge, S., & Darzi, A. (2017). Barriers to
the implementation and uptake of simulation-based training programs in general
surgery: A multinational qualitative study. Journal of Surgical Research, 220,
419-426. https://doi.org/10.1016/j.jss.2017.07.020
Key, K. K., Hu, P. T., Choi, I, & Schroeder, D. J. (Under Review). Safety culture
assessment and promotion in aviation: A literature review (Technical Report).
Federal Aviation Administration, Office of Aerospace Medicine.
Lunde, A., & Braut, G. S. (2019). The concept of overcommitment in rescue operations:
Some theoretical aspects based on empirical data. Air Medical Journal, 38(5),
343–349. https://doi.org/10.1016/j.amj.2019.05.008
*Lunde, A., & Braut, G. S. (2019). Overcommitment: Management in helicopter
emergency medical services in Norway. Air Medical Journal, 38(3), 168-173.
https://doi.org/10.1016/j.amj.2019.03.003
Malterud, K. (2001). Qualitative research: Standards, challenges, and guidelines. The
Lancet, 358(9280). 483–488. https://doi.org/10.1016/S0140-6736(01)05627-6
49
Malterud, K. (2012). Systematic text condensation: A strategy for qualitative
analysis. Scandinavian Journal of Public Health, 40(8), 795-805.
https://doi.org/10.1177/140349481246503
Martinsen, J. (2015). Observation and rating HEMS crew in non-technical skills, CRM
medical simulation in Norwegian air ambulance. Scandinavian Journal of
Trauma, Resuscitation and Emergency Medicine, 23(2), 1.
https://doi.org/10.1186/1757-7241-23-S2-A21
Minotra, D., & Feigh, K. (2017, September). Eliciting knowledge from helicopter pilots:
Recommendations for revising the ACTA method for helicopter landing tasks. In
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
(Vol. 61, No. 1, pp. 242-246). SAGE Publications.
https://doi.org/10.1177/15419312136015
Minotra, D., & Feigh, K. M. (2020). An analysis of cognitive demands in ship-based
helicopter-landing maneuvers. Journal of the American Helicopter Society, 65(4),
1-11. https://doi.org/10.4050/JAHS.65.042009
*Müller, A., Prohn, M. J., Huster, K. M., Nowak, D., Angerer, P., & Herbig, B. (2014).
Pilots’ age and incidents in helicopter emergency medical services: a 5-year
observational study. Aviation, Space, and Environmental Medicine, 85(5), 522-
528. http://doi.org/10.3357/ASEM.3861.2014
National Transportation Safety Board. (2019). Annual summary of US civil aviation
accidents (2007-2019). Retrieved on Jan. 9, 2023 from
https://www.ntsb.gov/safety/data/Pages/Data_Stats.aspx
National Transportation Safety Board (2006). Special Investigation Report on Emergency
Medical Services Operations (Report No. NTSB/SIR-06/01). NTSB, Washington,
DC.
Operating Requirements: Commuter and on Demand Operations and Rules Governing
Persons on Board Such Aircraft, 14 CFR § 135 (2022).
https://www.ecfr.gov/current/title-14/chapter-I/subchapter-G/part-135?toc=1
Operating Requirements: Domestic, Flag, and Supplemental Operations, 14 CFR § 121
(2022). https://www.ecfr.gov/current/title-14/chapter-I/subchapter-G/part-
121?toc=1
Operations: Foreign Air Carriers and Foreign Operators of U.S.-Registered Aircraft
Engaged in Common Carriage, 14 CFR, 129 (2022).
https://www.ecfr.gov/current/title-14/chapter-I/subchapter-G/part-129?toc=1
50
*Radstaak, M., Geurts, S. A. E., Beckers, D. G. J., Brosschot, J. F., & Kompier, M. A. J.
(2014). Work stressors, perseverative cognition and objective sleep quality: A
longitudinal study among Dutch helicopter emergency medical service (HEMS)
pilots. Journal of Occupational Health, 56(6), 469-477.
https://doi.org/10.1539/joh.14-0118-OA
*Ramee, C., Speirs, A., Payan, A. P., & Mavris, D. (2021). Analysis of weather-related
helicopter accidents and incidents in the United States. In AIAA Aviation 2021
Forum (p. 2954). https://doi.org/10.2514/6.2021-2954
*Rasmussen, K., Langdalen, H., Sollid, S. J., Abrahamsen, E. B., Sørskår, L. I. K.,
Bondevik, G. T., & Abrahamsen, H. B. (2019). Training and assessment of non-
technical skills in Norwegian helicopter emergency services: A cross-sectional
and longitudinal study. Scandinavian Journal of Trauma, Resuscitation and
Emergency Medicine, 27(1), 1-10. https://doi.org/10.1186/s13049-018-0583-1
Rasmussen, K., & Sollid, S. J. (2015). The HEMS medical crew survey. In Scandinavian
Journal of Trauma, Resuscitation and Emergency Medicine (Vol. 23, No. 2, pp.
1-2). BioMed Central.
Reason, J. (1997). Managing the Risks of Organizational Accidents (1st ed.). Routledge.
https://doi.org/10.4324/9781315543543
*Rikken, Q. G., Mikdad, S., Mota, M. T. C., De Leeuw, M. A., Schober, P., Schwarte, L.
A., & Giannakopoulos, G. F. (2021). Operational experience of the Dutch
helicopter emergency medical services (HEMS) during the initial phase of the
COVID-19 pandemic: Jeopardy on the prehospital care system? European
Journal of Trauma and Emergency Surgery, 47(3), 703-711.
https://doi.org/10.1007/s00068-020-01569-w
Rosenlof, K. (2020). Metro aviation thrives in a tough environment. Aviation
International News Online. https://www.ainonline.com/aviation-news/general-
aviation/2020-01-24/metro-aviation-thrives-tough-environment
Ruskin, K. J. (2019). Helicopter air ambulance services. Current Opinion in
Anesthesiology, 32(2), 252-256. http://doi.org/10.1097/ACO.0000000000000700
Salthouse, T. (2012). Consequences of age-related cognitive declines. Annual Review of
Psychology, 63, 201–226
Sollid, S. J., Dieckman, P., Aase, K., Søreide, E., Ringsted, C., & Østergaard, D. (2019).
Five topics health care simulation can address to improve patient safety: Results
51
from a consensus process. Journal of Patient Safety, 15(2), 111.
https://doi.org/10.1097%2FPTS.0000000000000254
*Speirs, A., Ramée, C., Payan, A. P., Mavris, D., & Feigh, K. M. (2021). Impact of
adverse weather on commercial helicopter pilot decision-making and standard
operating procedures. In AIAA Aviation 2021 Forum (p. 2771).
https://doi.org/10.2514/6.2021-2771
Stone, L. W. (1993). The aging military aviator: A review and annotated bibliography.
*Strauss, M., Dahmen, J., Hutter, S., Brade, M., & Leischik, R. (2021). Rescue
operations lead to increased cardiovascular stress in HEMS crewmembers: A
prospective pilot study of a German HEMS cohort. Journal of Clinical
Medicine, 10(8), 1602. https://doi.org/10.3390/jcm10081602
*Zakariassen, E., Waage, S., Harris, A., Gatterbauer-Trischler, P., Lang, B., Voelckel,
W., Pallesen, S., & Bjorvatn, B. (2019). Causes and management of sleepiness
among pilots in a Norwegian and an Austrian air ambulance service—A
comparative study. Air Medical Journal, 38(1), 25-29.
https://doi.org/10.1016/j.amj.2018.11.002
