Simulation Today Autumn 2019

Volume 1 No. 1
Autumn 2019
Simulation Today
A resource for all involved in the teaching and practice of simulation
iSimulate - Train
anywhere at any
time with our flexible
simulation systems.
In this issue
Must Read Online Resources for
EMS Simulation Training
Used across the world for Nurse /
Paramedic and Medical education
A Space to Think
Notions of Reality in Simulation
Training
www.iSimulate.com
See reverse for Resuscitation Today

CONTENTS
CONTENTS
Simulation Today
4 EDITORS COMMENT
6 FEATURE Must Read Online Resources for EMS Simulation
Training Program Success
9 FEATURE A Space to Think
15 FEATURE Notions of reality in simulation training
17 FEATURE Focused nurse-defibrillation training: A simple and
cost-effective strategy to improve survival from
in-hospital cardiac arrest
21 COMPANY NEWS
This issue edited by:
David Halliwell MSc
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COVER STORY
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The latest version - REALITi360 is a modular simulation ecosystem
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Next Issue Spring 2020
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SIMULATION TODAY - AUTUMN 2019
3

EDITORS COMMENT
EDITORS COMMENT
Simulation is an educational tool or technique which is dramatically changing as
our students embrace new ways of learning and teaching.
SIMULATION TODAY - AUTUMN 2019
“3D printing
and scanning
are becoming
common in
hospitals as
we develop
new lifelike
education
tools, and the
“make your
own” teaching
tool community
continues to
gain traction.”
Historically our thoughts were shaped by a few key individuals, whose interest in undertaking
medical simulation were driven by a desire to improve a technique or promote a particular
method of clinical practice. (An example of which is the ‘Resuscitation Annie’ – developed by
Laerdal, which was specifically developed to promote participation as the global desire to teach
resuscitation came into the public consciousness.)
But Simulation in the 21st century is very different to that of the last century. As educators we
have new tools at our disposal, we have access to cheap Augmented Reality, Mixed Reality,
Virtual Reality, all of which are being used to enhance Medical and Nursing / Paramedical AHP
education.
3D printing and scanning are becoming common in hospitals as we develop new lifelike
education tools, and the “make your own” teaching tool community continues to gain traction.
This Journal will feature many of the leading thinkers in Healthcare Simulation, and will share ideas
from the worlds of Human Factors, Education and Educational Equipment.
We will be sharing individual experiences, and showcasing leading products and engaging with
key thinkers from around the world.
We hope that this journal will be seen as a resource and is packed with sufficient information to
make it useful as a reference point for the reader.
Best Wishes
David Halliwell MSc
David Halliwell is a Senior Teaching Fellow at 2 x UK Universities, leading modules in healthcare
Simulation.
A senior NHS clinician and manager for many years, David developed many educational
programmes and learning strategies, most recently he began developing his own education
tools. Lecturing internationally – he recently won the “Best Overall Presentation” at the Simghosts
conference in Miami.
4

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innovation of healthcare simulation for educators, technologists, technicians, nurses,
doctors, midwives, allied health, patient safety leads and other healthcare professionals.
Make valuable connections, experience exciting keynotes and attend special events.
Call for Sessions
Share your expertise in a workshop,
presentation or poster. Abstract submissions
until October 30th at hpsn.com
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Your worldwide
training partner
of choice

FEATURE
MUST READ ONLINE RESOURCES
FOR EMS SIMULATION TRAINING
PROGRAM SUCCESS
Lance Baily BA, EMT-B (https://www.linkedin.com/in/lancebaily/)
Founder of HealthySimulation.com & SimGHOSTS.org
Lance@HealthySimulation.com
SIMULATION TODAY - AUTUMN 2019
In the United States, a National Association for EMS Educators
(NAEMSE) supported research article entitled “Simulation Use in
Paramedic Education Research (SUPER): A Descriptive Study” reported
on the utilization of medical simulation in EMS programs across the
Country. The publication found some shocking results, in that had some
shocking findings, in that:
“Paramedic programs reported they have or have access to a wide
range of simulation resources” but that “Simulation equipment (of any
type) reportedly sits idle and unused in (31%) of programs” due to “lack
of training”.
With the methodology of medical simulation following behind the
advances in healthcare simulation technology, combined with the
inability of programs to invest beyond equipment into instructor training
-- it is no wonder clinical simulation in EMS is slow to adopt. That’s
why administrators and EMS Training program directors must carefully
consider the need to train and educate instructors as a true cost of
providing simulation training, beyond the shiny new toys of medical
simulators.
Finding key resources is half the battle, so here below are a brief
breakdown of the 5 Top Medical Simulation resource articles available
for free on HealthySimulation.com to help EMS programs across the UK
jump start or expand their simulation programs.
HealthySimulation.com is the leading online medical simulation
resource website providing the latest news, conference highlights,
research updates, job listings, product demos and more!
1. Simulation Use in Paramedic Education Research (SUPER):
A Descriptive Study
(https://www.healthysimulation.com/7081/simulation-use-inparamedic-education-research-super-a-descriptive-study/).
The purpose of this research was to characterize the use of
simulation in initial paramedic education programs in order to assist
stakeholders’ efforts to target educational initiatives and resources.
This group sought to provide a snapshot of what simulation
resources programs have or have access to and how they are
used; faculty perceptions about simulation; whether program
characteristics, resources, or faculty training influence simulation
use; and if simulation resources are uniform for patients of all ages.
2. JEMS: Standardization of EMS Simulation Activities
Improves the Learning Experience
(https://www.healthysimulation.com/16618/jemsstandardization-of-ems-simulation-activities-improves-thelearning-experience/):
A recent JEMS publication by Aaron
Dix, NRP, MBA, CHSE, NCEE, CP-C , Jennifer McCarthy, MAS,
NRP, MICP, CHSE , and Andrew E. Spain, MA, NCEE, EMT-P
entitled “Standardization of EMS Simulation Activities Improves
the Learning Experience” concluded that “Standardization is
an essential consideration for any simulation activity” and that
“the level of standardization must be specifically chosen and
incorporated into the design to ensure that each simulation is
appropriate and useful.” Furthermore, the research found that
“Standardization within simulation activities improves quality and
the experience for learners [and] also enhances the efforts of
proper simulation design, execution and debriefing making the
effort of evidence-based practice worth it.”
3. About Ambulance Simulators
(https://www.healthysimulation.com/ambulance-simulator/):
Providing EMS students and professionals with realistic
training is crucial to their success in the field. By providing
EMS learners with the opportunity to train in the most realistic
way possible, clinical educators can reduce costs associated
with medical errors while improving provider performance.
Ambulance Simulators enable Emergency Medical Service (EMS)
professionals to realistically train for the unique challenges
of patient care within a confined and mobile space. Ranging
from simple environmental wallpaper coverings for static sim
lab rooms to fully immersive simulated ambulances on moving
hydraulic presses with realistic lights and sirens, ambulance
simulation has quickly become a key component in educating
and training EMS providers.
4. Simulation Technician Entry Level Job Description
Downloadable Template
(https://www.healthysimulation.com/18426/medicalsimulation-technician-job-description)
A Simulation Technician/
Technologist works in the field of healthcare simulation
supporting the many technical aspects of medical simulation.
Here, we take a look at the general entry level requirements of a
Sim Tech position and provide a downloadable template for your
program to use as a starting point. Additional articles related to
6

FEATURE
simulation staffing of Sim Techs and other positions can be found
on our Medical Simulation Jobs page, including where to find
Sim Techs, how to train them, and what to pay them!
5. How Vassar College Built Their Own Ambulance Simulator
(https://www.healthysimulation.com/16238/jems-covershow-vassar-college-built-their-own-ambulance-simulator/)
Ambulance Simulation for EMS students is an important aspect
of training that may be difficult to reproduce repeatedly. Not many
programs have available access to a contemporary ambulance
due to obvious cost or scheduled “active duty” cycles. Enter
Vassar College who empowered an EMT student with set building
experience to help build them their “Simbulance”, a confined but
open air ambulance simulator design with attached viewing deck!
The Simbulance project came about from the desire to provide a
more realistic simulated experience—one that includes lifting and
moving a patient to an ambulance, performing skills in the back of
an ambulance, calling in reports to the hospital and, finally, taking
the patient out of the ambulance and bringing them to the next
point of care in the ED.
Do not have space for
traditional patient
simulators?
Try VERA, your
standardised patient,
a VR solution that
allows patient
communication via
VR Headset, computer
browser or mobile device.
Looking to Attend a Simulation
Conference?
Simulation Champions across the UK should consider attending
the annual Association for Simulated Practice in Healthcare (ASPiH)
event. Learn more at https://aspih.org.uk/
Ask us for a demo
www.simulaids.eu.com/vera
info@simulaids.eu.com 01530 512425
VERA – exclusively available in the UK from Simulaids Ltd
WHY NOT WRITE FOR US?
Simulation Today welcomes the submission of clinical
papers, case reports and articles that you
feel will be of interest to your colleagues.
The publication is mailed to all resuscitation, A&E and anaesthetic departments
plus all intensive care, critical care, coronary care and cardiology units plus
Universities and Schools of Midwifery that teach Simulation.
All submissions should be forwarded to info@mediapublishingcompany.com
If you have any queries please contact the publisher Terry Gardner via:
info@mediapublishingcompany.com
SIMULATION TODAY - AUTUMN 2019
7

iSimulate - Train anywhere at any time
with our flexible simulation systems.
Used across the world for Nurse / Paramedic
and Medical education
www.iSimulate.com

FEATURE
A SPACE TO THINK
How can recent advances in cognitive load theory inform
practice in simulation-based healthcare education?
Dr Lewis Moore BSc MBBS PGCert; Student No. – 17834412
Module – MDM148 Principles and Practice of Simulation.
Introduction
Simulation is becoming a central modality in medical education with
recent evidence of educational benefit and improved patient outcomes
(1, 2). Simulation has traditionally taken its theoretical underpinning from
experiential learning (3) and constructivism (4), but the last ten years
have seen an explosion of publications attempting to use cognitive load
theory to improve simulation-based education (SBE)(5-9).
Cognitive Load Theory
Cognitive load theory (CLT) is based on the neuropsychological
observation that the human working memory is severely limited in both
capacity and time (10, 11), and states that if its limits are exceeded,
errors will be made and learning will be impaired (12). The long-term
memory, however, is effectively unlimited, information in the long-term
memory is stored in organised schema, and may be usefully accessed
with only minimal cognitive effort. CLT attempts to minimise the risk of
cognitive overload and maximise learning (13).
CLT splits cognitive workload into three types; intrinsic load which is
related to the complexity of the problem to be solved, extraneous load
which distracts from the problem and wastes cognitive resources, and
germane load (sometimes conceptualised as a sub-type of intrinsic
load) which represents cognition used to organise or categorise
information, and is thought to be a source of learning (14).
Intrinsic load is seen as highest when a problem has a high degree
of element interactivity, where many factors must be considered
simultaneously to produce a ‘correct’ answer (think long multiplication
or complex grammar). Medical care and procedures, simulated or
otherwise, are such problems; learners must assess many body
systems simultaneously using different modalities (history, examination,
imaging, bloods) while communicating effectively with a patient and
members of the team (5). The same is true in the simulation lab, and
we must be mindful that complex tasks may leave minimal cognitive
space for learning, and that small amounts of extraneous load may lead
to cognitive overload, expressed as frustration and poor performance.
The principles of CLT state that we should adjust the intrinsic load to
be appropriate to the learner, while minimising the extraneous load and
introducing or improving the germane load to maximise learning. This is
demonstrated in Figure 1.
Outline of this Essay
This essay will initially explore the design principles that were taken
from the wider education community and applied to medical education
- more specifically, to SBE. It will then explore the science of measuring
cognitive load (CL), the effect of emotion on CL, and finally will
examine studies which have used CLT principles to design educational
interventions and test their efficacy.
Cognitive Load Theory in Simulation-Based
Education
Fraser et al. adapted the primary CLT literature (12) derived from the
classroom setting in disciplines such as mathematics and engineering,
and previous attempts to make CLT relevant to medical education (5)
for use in medical SBE, making many practical recommendations (7) as
explored below.
Figure 1 – Graphical representation of cognitive limits and different
states of optimisation. (Adapted from Sweller J, Van Merrienboer JJ,
Paas FG. Cognitive architecture and instructional design. Educational
psychology review. 1998;10(3):251-6)
Minimising Extraneous Load
Extraneous load (EL) is the enemy in CLT; neither relevant to the task
at hand nor educationally useful, making its reduction a core goal in
educational design. EL is primarily conceptualised as deriving from
information that is presented to the learner sub-optimally, and the
strategies for minimising EL therefore focus on this.
The split attention effect is the observation that the requirement to
obtain information from multiple sources simultaneously, and to usefully
integrate these, produces more CL than if the information was in a single
source. A large body of evidence in the CL literature outside medicine
(15) demonstrates that if all information is presented in a single form or
location, then learning is enhanced via reduction of extraneous load.
Summarising all relevant information on a card would reduce CL but
impair realism, clearly there is a balance to be struck depending on the
SIMULATION TODAY - AUTUMN 2019
9

FEATURE
SIMULATION TODAY - AUTUMN 2019
expertise of the learner and the desired realism of the scenario. With this
principle in mind, educators can make this a conscious choice and even
produce different versions of the same scenario with different levels of
realism and visuospatial cognitive demand.
Contrary to this, the expertise reversal effect (14) describes how the
opposite may be true for expert learners who may feel alienated if they
are given physiological data written down, and cannot see, for instance,
individual waveforms on the monitor which they may usually rely on.
The worked example effect suggests that being shown how to complete
a task carries more educational value, or is at least much more efficient
than solving the problem independently(16). In simulation this is
conceptualised in several ways; for instance a skilled assistant may
interpret blood gas or ultrasound images. If these skills are not explicit
learning objectives and cannot be performed ‘automatically’ by the
learner, then they can reasonably be outsourced to help prevent overload.
Another implementation of this principle would be to allow learners
to retry a scenario they had struggled with after some reflection and
feedback (17). This mirrors Kolb’s experiential learning (3) cycling
between action and reflection.
Adjusting Intrinsic Load
As learners gain expertise, they develop schemas allowing them to
organise and simplify information, making a task such as assessing
a patient with chest pain daunting or difficult (high intrinsic CL) for
a medical student but very simple (minimal intrinsic CL) for even a
relatively-junior paramedic or emergency medicine physician. Because
of this, we must carefully design tasks to ensure that the intrinsic load is
are neither inherently too complex nor too mundane for the learner, as
this would impair learning.
The pretraining effect (18) encourages that we prepare students
adequately for a simulated experience; showing them the monitoring
equipment, where they might find pulses on the Laedral SimMan 3G,
the location of drugs and equipment, and the format in which they can
expect briefing and assistance. Providing this information will prevent
these otherwise small questions from building into an overwhelming fog
of uncertainty.
Germane Load
Reduction and optimisation of other forms of CL theoretically allow us
to leave some of the learner’s working memory to learn or to structure
the task (19). Some suggestions regarding how this can be done are
to introduce structural assessments like ABCDE, 4 H’s and 4T’s or to
ask the learner to explain their thought process as they go along. While
adding another simultaneous task will necessarily improve cognitive
workload, this approach is thought to guide the learner towards the
most important ideas and information, and improve outcomes. If the
learner asks themselves these questions in a similar ‘real-life’ situation,
their outcomes should theoretically be better.
What Does it Add?
As a purveyor, organiser and consumer of medical education on
nearly a daily basis, the author has become increasingly aware of
the prevalence of disparity between the difficulty of an educational
intervention and the needs and abilities of the learners. While it may
seem like common sense to teach at the right level of detail, this
is often not the case, or is made very challenging by large gaps in
seniority between the learner and educator (and therefore assumed
knowledge) or by the wide range of ability in a cohort of learners. The
above principles allow or indeed encourage simulationists and other
educators to identify the needs and abilities of the learner, and adjust
the intervention accordingly. They may help us not to deliver SBE badly,
but can they lead us to excellence? While these tools may be useful for
some, they seem undeserving of the hype that CLT has generated in the
recent years.
A summary of CLT-based recommendations for SBE can be found in
Appendix 1.
Measuring Cognitive Load
The scientific method suggests that if CL indeed exists, then there
should be a way to measure it (20) and observe its effects. Only if CL
can be measured reliably can we draw meaningful conclusions about
its effects.
How is CL Measured?
As a cognitive phenomenon, the obvious method to measure CL is
self-reporting. Paas (21) pioneered this in the educational psychology
domain and his validated CL scale (1 – very very low to 9 – very
very high) is widely used in medical education. NASA created their
own tool, NASA-TLX, for assessing mental workload (22), which is a
distinct concept but widely thought to be analogous to cognitive load.
Problems associated with self-reporting include the intrusive nature
of the sampling, the disruptive nature of pausing a task for a learner
to complete a questionnaire (itself adding to CL), or the reporting
happening after the exercise, introducing recall bias. CL is sometimes
inferred from surrogate physiological measurements such as heart
rate (23), EEG (24) or pupillary tracking or dilation (25). Physiological
measurements give little indication as to absolute CL, but indicate
fluctuations over time (8). The final way that CL is measured is by asking
learners to perform a secondary task alongside the main intervention,
such as pressing a button when a vibrating stimulus is applied to
their arm (26). The response time (or other performance measure) is
hypothesised to indicate the CL engaged in the primary task.
Validity of CL Measurements
Naismith and Cavalcanti produced a systematic review (8) of the SBE
literature correlating cognitive load measurements and educational
outcomes or task performance. Included studies were rated out of 5
for the validity of their measurement techniques, using a tool previously
created by Cook et al. (27). Of the 35 studies compared across all
domains, 6 showed that higher cognitive load was associated with
better learning or performance outcomes (positive association), 8
showed a negative association and 14 were neutral. In the studies from
the medical education literature, there were no studies with positive
association, 5 negative, and 7 neutral. The studies showing negative
association between CL and performance came from studies with a
higher mean validity score (See Figure 2).
The overarching message of this review is that the scientific community
does not have an agreed- upon standard for how to measure cognitive
10

FEATURE
load. Many studies modify the Paas or NASA-TLX instruments, or create
their own with little or no attempt to validate them before using them
to draw conclusions. Physiology or even observer rating is also used
without any solid evidence of validity. The literature does not compare
‘like with like’ and therefore, the heterogeneity of these results is
unsurprising.
CL as Meta-Examination
Aldekhyl et al. (28) used an ultrasound-based simulation to assess
sonographic competence of 29 clinicians of varying seniority. CL
was approximated by tracking eye movements while the participants
attempted to obtain suitable images. It was found that higher gaze-shift
rate, indicating higher cognitive load was negatively associated with
performance. The more experienced clinicians, having consolidated
their knowledge, find it easier to obtain the images, and therefore CL
is low, whereas those with less experience can perform the task, but at
greater cognitive expense. This observation is profoundly striking as it
opens a new door for assessment of clinical competence; we would
clearly prefer to employ an anaesthetist who could calmly complete a
crossword while delivering a safe anaesthetic than one who nervously
watched the monitor throughout. This does however seem somewhat
perverse and intrusive; as a profession, we are used to being assessed
and examined, but wearing a heart rate monitor and eye-tracking
equipment during a clinical station would seem very dystopian at a job
interview.
Summary
The ability to reliably measure a variable is a prerequisite to
understanding its importance. It has been demonstrated that while
many studies have purportedly measured ‘cognitive load’ they have
measured a wide variety of different things. A consensus on how CL is
to be measured, and its experimental validation, must be made a priority
by the research community for the quality of evidence to improve.
Emotion and Cognitive Load
Cognitive load theorists have attempted to integrate emotion into CLT,
with emotion being classified as intrinsic load in, for instance, a breaking
bad news scenario (7), and extrinsic when general ‘stress’ appears to
shrink the size of the usable working memory (31).
In an observational study, Fraser et al. asked 84 undergraduate
medical students to rate their emotional state and cognitive load in
an SBE scenario (32), finding that students with a higher perceived ‘
invigoration’ also experienced higher CL, and were significantly less
likely to correctly identify clinical signs (regression coefficient 0.63, 95%
CI 0.28–0.99; p = 0.001).
The same authors decided to use CLT to attempt to answer an ongoing
debate in SBE: should the mannikin die during sim scenarios (33)?
While death of the mannikin is necessary for practicing cardiac arrest
management, it is sometimes used as feedback for poor performance,
and while some see this as highly realistic and motivating feedback,
others feel that it is a potentially damaging violation of the safe learning
environment that simulation attempts to provide (34). The study in
question (35) used a randomised controlled trial to assess the effect
of unexpected manikin death on emotion, cognitive load, and distant
learning outcomes. 112 undergraduate medical students undertook a
simulation scenario involving salicylate poisoning. They were randomly
assigned to 2 groups whose scenarios differed only in the last 3
minutes; one group with a good patient outcome and the second with
sudden deterioration and death. The students’ self-rated emotions were
significantly poorer and subjective cognitive load significantly higher
in the unexpected death cohort (see Figure 3). Three months after
the simulation, the students faced the same scenario in a summative
objective structured clinical examination (OSCE). Those that were in
the mannikin death group were significantly less likely (70.9% vs 86.9%:
OR of 0.37, 95% CI, 0.14-0.95; P = 0.04) to be rated as competent by
the examiner and pass the station (see Figure 3). While it may seem
appropriate for some for the mannikin to die, this study gives strong
evidence to support the view that the emotional impact of this outcome
will impair learning, and therefore should not be routinely used in
simulation practice.
In the broader psychological literature, the relationship between emotion
and learning has been studied extensively, and certain principles are
held to be true. Positive emotions can stimulate motivation, enhance
creativity, and improve learning outcomes (7, 29), while negative
emotions affect learning unpredictably, sometimes acting to heighten
the relevance and therefore recall of a memory, and other times thought
to overwhelm the ability to learn (30).
Figure 2 – The studies that identify a negative relationship between
cognitive load and learning outcomes used, on average, the more valid
measurement tools. (Taken from Naismith LM, Cavalcanti RB. Validity
of cognitive load measures in simulation-based training: a systematic
review. Academic Medicine. 2015;90(11):S24-S35)
Cognitive Load in Practice
Educational Intervention Designed using CLT Principles
Andersen et al. tested CLT-based design in a small randomised
controlled trial to teach surgical skills in a virtual reality (VR) simulation
(36). Eighteen medical students underwent an hour of training in
performing mastoidectomy on a freely available VR training package
(See Figure 4).
Half trained using traditional instructions, and half trained using CLTdesigned
instructions, comprised of worked examples and partially
completed procedures. Students were then assessed by expert
examiners for competence in performing this procedure. Students who
studied worked examples reported higher CL (52% vs 41%, p = 0.02),
and performed less well in examination (13.0 vs 15.4, p < 0.005) than
those studying with traditional instructions.
This study adds to the evidence that higher cognitive load impairs
learning. The study detracts, however, from the suggestion that worked
SIMULATION TODAY - AUTUMN 2019
11

FEATURE
Figure 3
examples provide lower CL and improved outcomes. It is important not
to draw too many conclusions from a small study, and to appreciate
that there are many factors involved in cognitive load and learning
outcomes. Perhaps the worked examples were difficult to navigate in
the software interface, or perhaps there were too many sections to get
through in the allotted hour? The study highlights the use of including
CL analysis when assessing the usefulness of a training intervention.
CL Analysis of Other SBE Interventions
Other authors have used CL solely as an adjunct in their analysis of
an education intervention. Dankbaar et al. tested a computer-based
simulation game against other interventions for the acquisition of
emergency care and resuscitation skills (37). All 61 students were
trained using an e- learning module and were then randomised into
three groups to receive either a) no further training, b) 2 hours of paperbased
practice cases, or c) 2 hours of computer-based simulation,
and were later tested in a manikin-based simulation. The clinical
competence of control, paper, and simulation groups were scored
at 7.5, 7.9 and 7.2 respectively (p= 0.12); adding a further 2 hours
of different forms of study did not significantly improve the students’
resuscitation skills, and cognitive load was not reported significantly
differently between the groups.
The author included a CL questionnaire as part of the analysis;
interestingly, the questionnaire has subsections for intrinsic cognitive
load (‘’the content of the e-module was very complex’’), extraneous
cognitive load (‘’the explanations were very unclear’’), and germane
cognitive load (“the e-module really enhanced my understanding of the
problems that were discussed’’). The author cited Paas (38) and stated
that the scale was previously validated, but appears to have missed
the point entirely: the cited article makes no reference to the ability of
learners to be able to self-assess subtypes of CL, and the questions
indicate a general misunderstanding of CL theory. As discussed in the
section on measurement of CL, authors appear unaware of the need to
use validated instruments, and feel it appropriate to modify or design
their own questionnaires without any validation. Aside from this, it seems
highly appropriate to use CL measurements as part of the assessment
of simulation or other interventions in medical education. If learning
outcomes are poor, then cognitive overload is one possible explanation,
and should be easily picked up on a post-course questionnaire.
Conclusion
There has been a large amount of publication activity concerning CLT
in the SBE literature in the last 5 years. The initial recommendations
from the wider literature have been adapted and applied practically
to healthcare SBE to some effect. While there have been some efforts
to standardise measurement of CL, authors often design their own
unvalidated instruments, which is a clear weakness of the current body
of literature, requiring further research. CLT can help us to understand
certain specific questions in simulation practice (Should we allow
manikins to die?) and may provide an intermediary for the link between
emotion and educational attainment. CLT is not panacea for educational
design, but is a tool that can help us to avoid cognitive overload, which
is one of several potential reasons for poor outcomes from educational
interventions.
References
1. Cook DA, Hatala R, Brydges R, Zendejas B, Szostek JH, Wang
AT, et al. Technology-enhanced simulation for health professions
education: a systematic review and meta-analysis. Jama.
2011;306(9):978-88.
SIMULATION TODAY - AUTUMN 2019
Figure 4 – A virtual reality training software for performing mastoidectomy.
(Taken from Andersen SAW, Mikkelsen PT, Konge L, Cayé-Thomasen P,
Sørensen MS. The effect of implementing cognitive load theory-based
design principles in virtual reality simulation training of surgical skills: a
randomized controlled trial. Advances in Simulation. 2016;1(1):20)
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Emotion, cognitive load and learning outcomes during simulation
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simulated death. Simulation in Healthcare. 2013;8(1):8-12.
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skill in statistics: A cognitive-load approach. Journal of
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Sørensen MS. The effect of implementing cognitive load theorybased
design principles in virtual reality simulation training
of surgical skills: a randomized controlled trial. Advances in
Simulation. 2016;1(1):20.
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SIMULATION TODAY - AUTUMN 2019
13

FEATURE
Appendix 1 – Summary of CLT Principles for SBE Design
SIMULATION TODAY - AUTUMN 2019
(Taken from Fraser KL, Ayres P, Sweller J. Cognitive load theory for the design of medical simulations. Simulation in Healthcare. 2015;10(5):295-307.)
14

FEATURE
NOTIONS OF REALITY IN
SIMULATION TRAINING
Mike Davis PhD MEd DASE Cert Ed FAcadMEd
Freelance consultant in continuing medical education, Blackpool UK
Introduction
Have you ever felt emotional about a seriously ill or traumatised
patient, especially when you thought that you or your team were not
managing as well as you might? Have you, on the death of the patient
– maybe a 2 year old caught up in something totally unexpected and
suddenly deteriorating in spite of you all doing everything you can – felt
distressed, tearful, ashamed, that you were not able to save a life?
I saw this happen in a large-scale simulation event (Davis et al 2008)
conducted as part of preparation for deployment to the British military
hospital in Afghanistan. A mannikin 2-year old with multiple blast injuries
died under the care of a paediatric trauma specialist and her team.
You might wonder why that would happen. Or you may have
experienced that sense of reality that can emerge from a wellconstructed
and presented simulation. This paper intends to explore
why a plastic dummy can generate those responses, by exploring the
nature of reality that a simulation can create.
Aspects of reality
The question we need to address is: to what extent does the physical
reality contribute significantly to the simulated experience? For the
military, this is an important component, but only accounts for 2 of the
9 criteria for judging the potential impact of the HOSPEX simulation
environment.
Sociological reality
The vast majority of professional life is conducted in multi-professional
teams but simulation can become somewhat of a silo-endorsing
activity by virtue of its success and subsequent adoption as part
of undergraduate and postgraduate study in single professional
groups. It is not uncommon, therefore, to find groups of, say medical
or paramedic students fulfilling multiple roles in the management of
a clinical case in a sim suite. Sociological reality is more likely to be
manifested in in situ simulations, where HCPs experience a clinical case
in their own, multi-disciplinary environment.
Sociological reality in simulation is a product of deliberate efforts to
ensure that people experiencing the event are doing so by playing
themselves in role, and that the roles reflects the variety of contribution
to that event. This serves the purpose of reinforcing the nature of the
role and keeps participants in their comfort zone, by virtue of the fact
that they are either:
There is widespread acceptance that there are three types of reality that
we experience in the simulated environment:
playing themselves in a familiar situation (i.e. one designed to reinforce
good practice and support others’ learning
• physical
• sociological, and
• psychological
and I am going to explore these in turn and then examine the ways in
which they can combine to recreate what we loosely call “real life”.
Physical reality
There are increasingly sophisticated attempt to replicate a human being
by virtue not only of the appearance, but also of the ways in which that
can be enhanced by the manifestation of appropriate clinical features:
sounds, discharges, words etc. Mannekins range in sophistication from
simple plastic dolls with limited capacity for movement and no sounds,
to chillingly realistic representations of human life, like the recent release
of the geriatric patient by Simulaids, described in their literature as
having:
“realistic patient positioning, flexibility and superior range of motion
[… capable of simulating] over 35 nursing and medical procedures”
(simulaids.eu.com; [accessed 5th July 2019])
or
playing themselves in an unfamiliar situation (i.e. but one that they could
reasonably be expected to face)
In either case, the sociological reality reinforces the team nature and
the multiple responsibilities within the simulated case being managed,
thereby making the simulation more life-like.
Psychological reality
This is a bi-product of every aspect of the way in which simulation is
created and has been neatly summarised by GP and medical educator
Lizzie Norris as “a busy brain”. Interestingly, it is just as likely to arise
from an almost equipment free, small group simulation as it is from
something taking place with the most sophisticated simulation suite.
Among the early ambitions of the designers of the European Trauma
Course (ETC), for example, was the capacity to arrive in a setting
with minimal equipment and personnel and still teach a team-based
approach to trauma management, by virtue of creating an intellectual
SIMULATION TODAY - AUTUMN 2019
15

FEATURE
and emotional environment within which participants could explore their
competence at their limits of prior experience.
While physical and sociological reality arise from the environment and
the invited participants, psychological reality is the product of the nature
of the experience as it unfolds and this depends significantly on the
extent to which information flow is realistic and timely.
Information flow
Information flow is the shorthand depiction of all of the sensory data that
arise from a clinical case. In the case of the human patient being treated
in resus, for example, this would be all of the information that is evident
from receiving the patient, taking an SBAR handover from paramedics,
to the outcomes of investigations arising from an A to E primary survey.
This would include what the patient says (if they are talking), as well as
any visual signs (bleeding, etc) and the results of any interventions like
blood test results, CT scans, X` rays.
The key difference between the mannikin and a patient is that in the
former case, the facilitator of the simulation has to provide timely
feedback as to the features that would emerge from a human patient.
This might emerge, in a sophisticated mannikin as a consequence of a
technical intervention; in a basic mannikin, it would be announced in a
timely way by the facilitator. The key ingredient here is “timely”, providing
the lead clinician running the scenario with information that was a
product of the leader’s interventions, e.g.
responsible for developing language skills in teenage pupils. We were
looking for ways to develop linguistic competence in pupils by engaging
them in challenging linguistic environments and we came across an
activity called “Bafa Bafa”, which involved learners exploring significant
cultural diversity. While BafaBafa created a fictional world, it was one
that was negotiated using complex linguistic skills that students,
functioning slightly beyond their comfort zones, had to negotiate, both
in the activity of the game itself, but also in the debrief that followed.
Those pupils demonstrated amazing commitment to being an Alpha or
a Beta and subjected their experience in those roles to critical scrutiny in
the debrief that followed. Their confidence and competence in a range
of complex linguistic skills flourished as they lived out the reality that the
game demanded of them. That reality, however, had no equipment and
the sociological reality was the “real” reality of their community. The buy
in, however, was the product of “the busy brain”.
References
Davis M, Driscoll P, Hanson J, Wieteska S (2008), The Advanced Life
Support Group’s View of HOSPEX. JR Army Med Corps 154(3): 206-208
Dr Mike Davis is a freelance consultant in continuing medical education
based in Blackpool. He works predominantly in the life support
community and has educator roles with Generic Instructor Course
(ALGS/RC(UK)), ATLS and ETC.
He is one of the authors (with Jacky Hanson, Mike Dickinson,
Lorna Lees and Mark Pimblett) of “How to teach using simulation in
healthcare”, published by Wiley-Blackwell in 2017.
SIMULATION TODAY - AUTUMN 2019
Team leader: (to circulation team member) Could you take the blood
pressure, please?
Circulation: (putting on and inflating cuff)
Facilitator (after appropriate pause): It’s 90 over 40.
etc
The key issue in offering a simulation in this way is that learners
managing the clinical case are expected to undertake tasks in an
appropriate sequence, taking an appropriate amount of time, and
eliciting (in a low fidelity setting), appropriate clinical signs from the
facilitator of the event, or, in a more sophisticated environment, picking
up those signs from the mannikin or a monitor.
Integrating realities
Whatever is offered in terms of physical and sociological reality, the
success or otherwise of a simulation is dependent on the extent to
which the learners engage in the psychological reality of the simulation:
they enter into what the 19th century poet, Samuel Taylor Coleridge,
called “the willing suspension of disbelief”. This psychological state
capitalising to a greater or lesser extent on the physical and social
manifestations of the simulation, lays the foundations for the buy-in: it is
real because it feels real and there is sufficient demand being made on
the participants’ minds that they have sufficient but not overwhelming
cognitive load for them to maintain their focus on the unfolding story
instead of thinking “This is a plastic mannikin”.
I first got involved in simulation training as an English teacher
HELLO, MY
NAME IS
I am the
first Patient
Communication
Simulator (PCS).
Ask us for a demo
www.simulaids.eu.com/alex
info@simulaids.eu.com 01530 512425
ALEX – exclusively available in the UK from Simulaids Ltd
16

FEATURE
FOCUSED NURSE-DEFIBRILLATION TRAINING:
A SIMPLE AND COST-EFFECTIVE STRATEGY TO IMPROVE
SURVIVAL FROM IN-HOSPITAL CARDIAC ARREST
John A Stewart
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine 2010 18:42 https://doi:10.1186/1757-7241-18-42 © 2010 Stewart
Reproduced with permission from the Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine
Abstract
Time to first defibrillation is widely accepted to correlate closely with
survival and recovery of neurological function after cardiac arrest due
to ventricular fibrillation or ventricular tachycardia. Focused training of
a cadre of nurses to defibrillate on their own initiative may significantly
decrease time to first defibrillation in cases of in-hospital cardiac arrest
outside of critical care units. Such a program may be the best single
strategy to improve in-hospital survival, simply and at reasonable cost.
Introduction
Survival from in-hospital cardiac arrest has not improved over the halfcentury
since the advent of basic cardiopulmonary resuscitation (CPR)
and defibrillation [1,2]. Survival rates remain about 18% at best, and
survival is lower on general units than in critical-care areas [3].
Explanations for this lack of progress often invoke co-morbidity, [2]
and proposals for change have frequently focused on preventing
presumably futile resuscitation attempts by means of do-not-resuscitate
orders [4]. Medical emergency teams have increasingly been
implemented to respond to early signs of deterioration and prevent
progression to cardiac arrest [5]. But tachyarrythmic arrests (ventricular
fibrillation (VF) and ventricular tachycardia (VT)) are typically sudden,
and this subset of arrests comprises the cases with a real chance of
survival--if defibrillation is accomplished quickly. The most important
change in out-of-hospital resuscitation over the past quarter-century has
been the renewed focus on early defibrillation by first responders, and
the best approach to improving in-hospital survival may be simply to
bring effective early defibrillation into the hospital [6].
Organizing and delivering the full range of advanced cardiovascular life
support (ACLS) treatments with code teams is an expensive, complex,
and daunting undertaking [7] that has little relation to outcomes--
because survival for presenting rhythms other than VF and VT is dismal,
both outside and inside the hospital. A program focused on saving lives
would look much different: it would devote resources to treatments with
proven effectiveness (primarily early defibrillation), up to the point of
clearly diminishing returns. To improve survival from in-hospital arrests,
a more effective approach to in-hospital defibrillation is needed.
Discussion
A defibrillator originally was a large and cumbersome device which had
to be moved from the critical care unit to arrests in other areas of the
hospital. Trained emergency personnel were usually at the scene of
an arrest by the time the defibrillator arrived. During the 1970s and
1980s there was a trend toward greater numbers of more portable
defibrillators in hospitals, and a defibrillator on every nursing unit is
now the norm. But training did not keep pace with availability: In the
mid-1980s this author brought the problem of delayed in-hospital
defibrillation to the attention of several people active in the American
Heart Association’s (AHA) Emergency Cardiac Care programs, and in
1992 published a description of a nurse-defibrillation training program
using manual defibrillators [8]. Later, those AHA-affiliated authors
began addressing the issue but linked nurse defibrillation closely with
the purchase and use of automated external defibrillators (AEDs)
[9]. The American Heart Association/International Liaison Committee
on Resuscitation’s stance continues to be that AEDs are the key to
achieving early defibrillation in hospitals [10].
The AHA’s promotion of AEDs for in-hospital use is not well supported
by present evidence [11]. A large recent study from Detroit, the best to
date, showed no improvement in time to defibrillation or survival after
hospital-wide introduction of AED-capable defibrillators, at a cost of
$2 million [12]. In addition, serious concerns have been raised about
AED technology in the past few years, centering on the requirement
for a “hands-off” period for rhythm analysis that has been shown to
decrease survival [6].
Inaccurate time data presents another impediment to implementation
of nurse-defibrillation programs because the true extent of the
delayed-defibrillation problem is obscured. Studies based on data
from the National Registry of Cardiopulmonary Resuscitation (NRCPR)
report median times of 0 minutes [1]. These time intervals, based
on handwritten code records, are unrealistically short [13]. NRCPR
researchers have recognized this, [14] but inaccurate time data
continue to be reported with little or no reservation [15]--though the
problem could be solved fairly simply [16].
Several factors, then-limitations of AED technology, unrealistically short
time-interval data, and of course cost [13]--serve to impede hospitals
in addressing the problem of delayed defibrillation. A recent article
provided some counterbalance to these factors: the investigators
reported that delayed in-hospital defibrillation was a relatively frequent
problem and that it lowered survival, although again the extent of
the problem was obscured by use of NRCPR data [17]. (A main
recommendation in the accompanying editorial was to buy more AEDs
[18].)
In recent years, there has been much interest in the 3-phase model of
VF arrest proposed by Weisfeldt and Becker, which posits that after
about 4 minutes treatment may be improved by a period of basic CPR
SIMULATION TODAY - AUTUMN 2019
Correspondence: jastewart325@gmail.com
17

FEATURE
before defibrillation [19]. The model has no relevance for in-hospital
defibrillation because 1) the goal should be to defibrillate in less
than 4 minutes (the AHA has established a benchmark of less than 3
minutes for all in-hospital arrests [20]), and 2) with multiple rescuers
typically available, all hospital protocols call for basic CPR while the
defibrillator is being brought to the scene. Therefore, defibrillation
at the earliest possible moment remains the best approach for inhospital
tachyarrythmic arrests.
Doing anything in the first moments of a code is emotionally
difficult, but defibrillation is no more difficult than other tasks
nurses are expected to perform in codes; certainly it is easier than
performing effective basic CPR. The main rationale for AED use--
the presumed need for advanced rhythm identification skills with
manual defibrillators--is without foundation: the basic distinction,
between an organized monitor rhythm and a chaotic pattern, is easily
learned [21]. Another barrier to rapid defibrillation is the presumed
danger to caregivers in administering a shock. However, dangers
of defibrillation have long been overstated (no documented deaths
or serious injuries in over 50 years) and safety has been further
improved by the use of hands-free pads [22]. The basic procedure of
defibrillation, whether with manual defibrillators or AEDs, is both easy
and safe.
In-hospital defibrillation training programs will have the capability to
conduct unannounced drills for practice and performance testing.
Many hospitals use “mock codes” to practice all aspects of code
response; these are fairly complex productions involving a good
deal of planning and disruption of daily work routines. Drills for
defibrillation training can be conducted much more simply--one
learner at a time--and preserve the element of unexpectedness
that is a critical condition of performance. Such drills should prove
valuable, both as a stimulus for learning and as an evaluation
tool. Each learner could be required to perform competently in a
surprise simulation 2 to 4 weeks after training, thereby providing
a more valid test, and the participants’ general foreknowledge of
the surprise testing should reinforce the training by encouraging
continued mental rehearsal.
The procedural skill of defibrillation can be taught primarily by
repeated physical simulation, but the training program should also
include a didactic component. This component will emphasize the
extreme time-dependence of defibrillation and will aim to counter
misconceptions about defibrillation, particularly regarding safety
issues for caregivers and patients [23]. This component can likely
be mastered through self-study, with a text or computer-based
tutorial.
SIMULATION TODAY - AUTUMN 2019
The real problem comes not from the inherent difficulty of the task,
but from the conditions of performance. Defibrillation is necessarily
performed in a life-threatening situation, without warning and under
intense time pressure [23]. Such stressors, in combination with the
rarity of the event for a particular caregiver, can cause a significant
decrease in skill. Demonstrating mastery in a single simulation in a
classroom setting is not sufficient to ensure adequate retention and
competent performance in an actual code. Clinical competence in
defibrillation calls for overtraining: requiring practice well beyond
the first competent performance by repeated performance in
simulations and to a higher standard than may be required in an
actual code. This is analogous to aspects of military training (e.g.,
disassembling and reassembling a rifle while blindfolded). Two- to
three-hour sessions with four to five trainees in each session should
be sufficient for this component of the training.
Affective aspects of defibrillation training also make it advisable
to select a group of highly motivated learners. Participants in an
in-hospital defibrillation program will be committing themselves to
training intensively and maintaining competence for long periods of
time without actually using the skill--but when called upon they will
be expected to perform quickly and competently under very stressful
conditions [23]. This level of personal commitment should not--and
indeed, cannot--be expected of all nurses. But it is unnecessary to
train all nurses in a facility, and indeed it is inadvisable to do so: a
select group of nurses can be trained that their first responsibility
in a code is to initiate monitoring and defibrillation while other
staff do CPR, thus avoiding the role confusion that is known to
be a significant problem with code team performance [24]. It may
be possible to rely mainly on volunteers, thereby increasing the
probability that training will succeed. The inherent emotional appeal
of defibrillation--the very real prospect of restoring a patient’s life
quickly, cleanly, and dramatically--can act as an inducement for
volunteers as well as a powerful source of motivation during training.
A study of the training program’s effectiveness should be preceded
by a period for gathering baseline data on times to first monitoring
and first defibrillation, [16] in order to gauge any Hawthorne
effect in the subsequent study. A prospective, controlled study
can be conducted by recruiting trainees to achieve randomization
across shifts and units, so that any given unit will be staffed with
a trained nurse approximately half of the time. If mean times to
defibrillation are shortened in the experimental group (arrests with
a defibrillation-trained nurse on the unit), survival can be tracked
in a longer and/or larger study. The proportion of successful
defibrillations should increase, and the number of shockable
rhythms should also increase due to earlier monitoring--before
deterioration to asystole [25].
If the program proves effective, hospital-wide implementation can
be accomplished by training perhaps one-fourth to one-third of
nurses. Full coverage can be ensured with a backup system if the
hospital pages codes overhead or if all defibrillation-trained nurses
carry code pagers, thus allowing them to respond to code calls on
adjoining units (and leave if coverage is already in place). Likewise,
defibrillation-trained nurses can be instructed to return to their
routine duties after the code team arrives.
Conclusions
The link between early defibrillation and survival is beyond
dispute. A program focused on early defibrillation by nurses can
be relatively easy to implement and cost-effective, and holds the
promise of saving many lives.
Competing interests
The author declares that he has no competing interests.
18

FEATURE
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ADVERTORIAL FEATURE
STANDARDIZED TRAINING OF PATIENT
COMMUNICATION TECHNIQUES WITH
ADVANCED SIMULATION TECHNOLOGY
Balazs Moldovanyi, M.Sc. Computer Engineering, MBA; Ádám Helybély, M.Sc. Computer Engineering,
MBA; Hugo Azevedo, BSc, Applied Mathematics, MS, Biomedical Engineering; Michelle Castleberry, BSc,
Professional Communication
The Patient Communication Simulator
Summary Statement: As Healthcare Simulationists we constantly
ask ourselves, where do we start improving our training for the nurses,
physicians, and allied healthcare professionals of 2050 through
healthcare simulation today? Patient simulators needs both an ongoing
evolution along the traditional dimensions or realism, dependability
and affordability as well as a revolution to broaden the potential of
simulation. Integrating Artificial Intelligence (AI) driven communication
technologies into simulators for training healthcare professionals of the
future will be revolutionary.
A Patient Communication Simulator is a device that integrates
verbal communication functionality into a traditional full-body patient
simulator by merging physiology simulation and communication training
modalities into a single scenario-driven instructor controlled experience.
In this article, we are evaluating the first commercially available Patient
Communication Simulator (PCS) and its future potential.
Key Words: Communication, Speech Recognition, AI, Science Fiction
How will the nurses, physicians, and allied healthcare professionals
of 2050 differ from their peers fifty years earlier? Future healthcare
professionals of 2050 will be making enhanced decisions. Enhanced
decisions through collaborative consultation; think: increased
telemedicine. Enhanced decisions with information at their fingertips;
think: wearable computing. Enhanced Decisions supported by
technology; think: AI & machine learning. Correspondingly, future
healthcare professionals of 2050 will have escalated the human
element, which will be proportionally more important for care of the
future patient and success of future health care teams; thus, furthering
efforts towards achieving the balance of ‘Art and Science of Medicine’.
Simulation can be qualitatively better as a tool, by not only training
to make triage decisions, but simultaneously allowing learners to
understand the fundamentals in human-interactions. Training must
improve for a stronger connection to the patient. Simulation must be
more relatable. The time to start moving in that direction is now.
Building on today’s needs with more advanced technology, The Patient
Communication Simulator (PCS) is the first of its kind, infused with
features and functions that a mere decade ago sounded like sciencefiction.
ALEX is a revolutionary new product that integrates AV enhanced
communication into a general purpose, full-body patient simulator, with
the objective of aiding in the training of non-technical skills.
SIMULATION TODAY - AUTUMN 2019
Today, a significant portion of simulation-based training is for a
healthcare system specializing in acute, curative, episodic issues.
Learners are trained to make emergency, high pressure decisions in
the fraction of a second. This skill will remain critical in healthcare; but
the call to action is clear, it’s time to do more and do better than just a
quantitative reformation.
Patient simulators have been proven to be efficient and low-risk tools
for several elements of the training of healthcare professionals, from
procedural skill development to team communication.
Simultaneously, trained standardized patients have introduced similar
standardization and consistency in simulated patient-professional
encounters, focusing on communication and physical interactions.
The next generation of patient simulators are devices that can merge
the benefits of these distinctly different approaches into a seamlessly
integrated experience, further enhancing the realism of the simulation
hence better facilitating its ultimate educational goals.
Using pre-programmed scenarios to drive not only the physiological
data but also the spoken responses and reactions of the patient, a
previously unattainable level of learning and standardization, is possible
across a larger number of dimensions of the simulation experience.
Is this the revolution and evolution we’ve been waiting for? Does this
balance art and science of medicine? Yes, it is the natural progression
in technology to help train healthcare professionals for the future.
simulaids.eu.com/alex | simulaids.eu.com/vera | http://blog.pcs.ai
ALEX fuses today’s most impactful
emerging technologies into a truly
remarkable new teaching tool, opening
an exciting new chapter in patient
simulation. ALEX is a cloud connected
patient simulator with an eye camera,
and Speech Recognition capabilities.
20

COMPANY NEWS
CAE
CAE Healthcare Introduces the CAE Luna
infant patient simulator
In 2019 CAE Healthcare officially released CAE
Luna, an innovative infant simulator designed
to fulfill clinical training requirements for
neonatal and infant care for health conditions
requiring expedient, life-saving team actions.
CAE Luna can be configured for essential
infant nursing skills or for more advanced
international Pediatric Advanced Life
Support (PALS) and Neonatal Resuscitation
Program (NRP) and S.T.A.B.L.E. Program
training requirements. The simulator
includes Simulated Clinical Experiences
(SCEs) for easy integration of simulationbased
curriculum into clinical education for
infant care.
Discover true innovation in simulation with
CAE Luna at https://caehealthcare.com/
patient-simulation/luna/
CAE Luna is the first completely wireless and
tetherless baby simulator manufactured by
CAE Healthcare. An advanced patient simulator
offering physiological modeling that responds to
clinical interventions just as an actual newborn
child would, CAE Luna realistically represents a
neonate from birth to 28 days after delivery.
CAE Luna can be operated in hospitals or
educational settings with a laptop, and without
power cords or cables. The IV ports, peripheral
arterial catheter site and umbilical cord allow
professional caregivers to safely practice
administering medications and fluids, while the
advanced airway and tracheostomy site allows
for repeated practice of delicate procedures
without risk.
WHY NOT WRITE FOR US?
Simulation Today welcomes the submission of clinical
papers, case reports and articles that you
feel will be of interest to your colleagues.
The publication is mailed to all resuscitation, A&E and anaesthetic departments
plus all intensive care, critical care, coronary care and cardiology units plus
Universities and Schools of Midwifery that teach Simulation.
All submissions should be forwarded to info@mediapublishingcompany.com
If you have any queries please contact the publisher Terry Gardner via:
info@mediapublishingcompany.com
SIMULATION TODAY - AUTUMN 2019
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