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Presented by
Courtney Brown, MSN, CRNA
Clinical Education Coordinator
Wake Forest University Baptist Medical Center
Simulation: the history
Aviation industry, nuclear power plants,
anesthesia
 1967: Abrahamson, Denson, & Wolf

 SIM 1 project

1988: David Gaba introduced CASE
Definitions

David Gaba (Stanford University):
“Simulation is a technique, not a
technology, to replace or amplify real
experiences with guided experiences,
often immersive in nature, that evoke or
replicate substantial aspects of the real
world in a fully interactive fashion”
Gaba (2007)
Definitions

Pamela Jeffries (Johns Hopkins
University SON): “Simulations are
defined as activities that mimic the
reality of a clinical environment and are
designed to demonstrate procedures,
decision-making, and critical thinking
through techniques such as role playing
and the use of devices such as
interactive videos or mannequins”
Jeffries, (2005)
Definitions

S. Barry Issenberg (University of Miami):
“In general, medical simulations aim to
imitate real patients, anatomic regions,
or clinical tasks, or to mirror the real-life
situations in which medical services are
rendered”
Issenberg & Scalese (2008)
Definitions
Fidelity: The degree to which an
electronic system accurately reproduces
the sound or image of its input signal
(Merriam-Webster)
 Fidelity is also synonymous to realism

Level of Fidelity
Examples
Low fidelity
Patient actors
Simulated interviews
Written problems
Task trainers
Intubation mannequins
Spinal and epidural trainers
Venipuncture arms
CVP insertion
High Fidelity
SimMan (Laedal)
HPS (METI)
Virtual reality
Turcato, Robertson, & Covert (2008)
The Simulation Environment
Environment fidelity: the degree the
simulator replicates motion cues, visual
cues, or sensory information from the task
environment
 Engineering fidelity: the degree to which
the simulation device or training setting
reproduces the physical characteristics of
the real task
 Psychologic fidelity: the degree to which
the trainee perceives the simulation to be
believable for the tasks

Issenberg & Scalese (2008)
Types of Simulation

Task trainers:
inexpensive, great for skill
attainment or evaluation
 Examples: plastic arms for
venipuncture, head or neck
for intubation techniques,
Resusci-Anne (chest
compressions and
ventilation)
Types of Simulation

Computer-enhanced mannequin: very expensive
($30,000- $250,000); full body, reproduce anatomy,
normal and pathophysiologic function
 Examples: Human patient simulator (HPS) from Medical
Education Technologies (METI); SimMan from Laerdal
Types of Simulation

Virtual reality: user interactions are within
the a simulated virtual world which can
range from computer-generated
environments to CAVE simulations that
allow for goggles and sensor-containing
gloves
 Examples: virtual emergency department,
trauma resuscitation scenarios, or virtual
delivery rooms to assess neonates
Simulation in Nurse Anesthesia
Programs
Turcato, Robertson & Covert (2008)
Virtual Reality Emergency Room
Crisis Resource Management

Manser, Harrsion, Gaba, & Howard
(2009):
 Observational study of 24 paired crews
 Higher performing crews:
○ Less task distribution
○ More situation assessment
 Low performing skills
○ Split into sub-crews
○ No shared plan
Crisis Resource Management
Team-focus
 Crisis management skills
 Can be Interdisciplinary
 Atul Gawande, MD: Medicine is a team sport


In Situ Simulation: takes place on the patient
unit itself (Miller et al., 2008)
Crisis Resource Management

Knudson et al. (2008), seven key
elements:
1. Command
2. Leadership
3. Communication
4. Situation awareness
5. Workload management
6. Resource management
7. Decision making
Mobile simulation and OnDemand
On-demand simulation available at
Harvard Medical School
 Mobile simulation

Theories
John Dewey
 David Kolb
 Albert Bandura
 George Miller

Kaakinen & Arwood (2009)
Kolb
Bandura
Miller
Michelson & Manning (2008)
Gaba’s Dimensions
Gaba’s Dimensions
Jeffries Simulation Framework
The Creation of a Simulation
Know your purpose:
1.
 Teach nurse anesthesia students the
physiologic signs and symptoms and treatment
of an intraoperative bronchospasm
The unit of participation
2.

3.
Groups of 3 (team)
Know your participants:
 First semester, inexperienced, nurse anesthesia
students. They are all former ICU nurses.
The Creation of a Simulation
The health care domain:
4.

High Stakes, OR environment
The providers:
5.

Student nurse anesthetists
The knowledge, skills, or behaviors
chosen to address:
6.

Decision-making skills, attitudes, behavior,
communication
The Creation of a Simulation
7.
The age of the patient:
 A 65 year old female
8.
The technology required:
 A human patient simulator with the ability to
increase airway resistance and has monitoring
9.
The site required:
 A physical environment that replicates the
operating room
10. The extant of direct participation:
 Direct hands-on participation, immersive
The Creation of A Simulation
11.
The feedback method accompanying
 Real-time mentoring and immediate
feedback with start and stop of simulation
Set-up
Bring students in, provide background
information (chart)
 Offer time for questions/answers
 Have all emergency equipment
necessary for simulation readily
available (including epinephrine,
albuterol in emergency drugs in second
drawer)
 State on the intercom, “Simulation is
beginning”

Create a Patient







Patient Name:
Name, age, and gender:
Chief Complaint:
History of Present Illness:
Past Medical History:
Past Surgical / Anesthetic
History:
Review of Systems:






CNS:
Cardiovascular:
Pulmonary:
Renal / Hepatic:
Endocrine:
Heme/Coag:










Current Medications:
Physical Examination:
General:
Weight, Height:
Vital Signs:
Airway:
Lungs:
Heart:
Laboratory, Radiology,
and other relevant
studies:
Hematocrit:
Our patient…

Annie A. Mess
 65 yo female for laparoscopic
cholecystectomy. C/o abdominal pain for 2
weeks with increasing intensity
 PMH: GERD, Seasonal allergies, Obesity,
and osteoarthritis of the left knee
 PSH: Left knee replacement one year prior
done under a spinal technique, no
anesthesia complications
Our patient…


Annie A. Mess:
ROS:
 CNS: Negative
 Cardiovascular:
Negative; denies
CP
 Pulmonary:
Seasonal allergies;
not currently
 Renal / Hepatic:
GERD
 Endocrine: Obesity
 Heme/Coag:
Negative
Takes prilosec daily (took
last night); PRN sudafed
 Overweight female in no
acute distress
 5’5”, 90 kg
 HR 70, BP 125/70, SPO2
97%
 Airway: MP 3, OA 3, TMD
2
 Lungs: Clear, but distant
 Heart: RRR, no murmurs,
rubs or gallups
 EKG: NSR, 68

Simulation Software
Prewritten versus Simulation user written
 First, choose a background patient

 Built into the HPS software
 Can write as well

Then, choose the scenario
 “Bronchospasm with Hypoxia”
Allow participants to nest and get “into” the
mode
 Initiate the scenario and monitor

Time Frame
Patient changes
Outcomes expected/
Transitions
Course of Simulation
Preinduction:
Chart
None
HPS: Choose Stannette
patient
Q/A
Introduce team
Focused assessment
Medication last dose
NPO status
Last surgery
Severity of GERD
Discuss anesthetic choices
“Your simulation is beginning”
Induction
HPS:
Monitor drugs chosen
Monitor patient need for pressors
Initiate “Bronchospasm/Hypoxia”
Scenario
start
HPS:
Increase airway resistance
Decrease SPO2 (shunt
fraction)
Increase HR
Increase CO2 production
Call for “Help”
Team communication
Listen to lung sounds
Take patient off ventilator
100% FiO2, increase Vapor setting
Give albuterol
Consider epinephrine
Monitor for resolution r/t
management
“Your simulation has ended”
Debriefing
Self assessment
 Feedback via dialogue
 Reflection
 Video replay
 Timing is irrelevant
 Repetition if time avails

Bond et al. (2008)
Best Evidence in Medical Education
(BEME)










Feedback: MOST important
Repetitive practice
Range of difficulty level: progressive
Multiple learning strategies
Clinical variation
Controlled environment
Individualized learning
Defined Outcomes/Benchmarks
Simulator realism/Validity
Curricular integration
Issenberg & Scalese (2008)
Choices, choices, choices







Simulation – Defaults to the Patient Profile (patient
information and medical history)
Scenario – Play or Edit scenarios
Condition – Set parameters for assessment and trauma.
Drugs – Administer drugs
Fluids – Affect plasma and blood volumes and urine
output
Cardiovascular – Set a wide array of parameters
affecting cardiovascular physiology
Respiratory – Control airway, lung and respiratory
parameters
Assessment
Bowel Sounds – Normal, Hyperactive,
Hypoactive
 Breath Sounds – Normal, Wheezing,
Rales, Muffled
 Heart Sounds – Normal, S3, S4, S3 and
S4, Early Systolic Murmur, Mid Systolic
Murmur, Late Systolic Murmur, Pan
Systolic Murmur, Late Diastolic Murmur

Drugs
Narcotics
 Hypnotics
 Neuromuscular Blockers
 Antagonists
 Cardiovascular
 ACLS

Simulation Center Ingredients
The simulation area
 The control room
 The debriefing area
 An area for storage of equipment
 Video and audio equipment

Easy, right?

Drawbacks to full-scale simulations:
 Technical difficulties
 Team dynamics issues
 Communication issues
 Unpredictable at times
 Necessity to orientation to environment
 “Buy-in”
Simulation Centers

Center for Immersive and Situation-based
Learning
 Stanford University

Center for Medical Simulation
 Harvard Medical School

Peter M. Winter Institute for Simulation
Education and Research (WISER)
 University of Pittsburg Medical Center

Center for Applied Learning
 Wake Forest University Baptist medical Center
Cannon-Diehl (2009)
SMARTER Approach
Rosen, Salas, Silvestri, Wu, & Lazarra (2008)
Forms of Evaluations

Checklists: Did they, or didn’t they?
 Binary (performed or not)
 Incremental (performed, performed well,
performed poorly)
 Easy, can be timed
 Objective Structured Clinical Examinations
(OSCEs)

Rating scales
 Global (Likert) versus Criterion-based
Scoring rubrics
 Formative versus summative

Bould, Crabtree & Naik (2009)
Forms of Evaluations
Form
Reliability
Validity
Ease of
Use
Comprehensiven
ess
Direct
Observation
Poor reliability
Face validity
+++
Potentially
Checklists
Excellent
reliability
Construct
validity
++
Depends on
checklist
Global scales
Excellent
reliability
Construct
validity
++
Depends on
content
Multiple
stations
Excellent
reliability
Construct
validity
Expensive Potentially
Timely
Graduate Medical Education
Simulation-based assessment has been
used since the OSCEs with simulation
patient actors since the 1980s!
 Accreditation Council for Graduate Medical
Education (ACGME)

 Outcomes Project to assess the quality of GME
 Simulation is listed as a key assessment tool

American Board of Emergency Medicine
 7 patients (5 single and 2 multiple) for high
stakes examinations
ACGME Outcomes Project
1.
2.
3.
4.
Incorporation of a set of general
competencies to organize curricula.
Support for programs through identification
and development of useful, reliable, and
valid methods for assessing attainment of
the competencies.
Development of model resident evaluation
systems to provide examples of
dependable evaluation.
Support of a resources support system.
http://www.acgme.org/Outcome
The Six Competencies
1.
Patient Care
2.
Medical Knowledge
3.
Professionalism
4.
Systems-based Practice
5.
Practice-based Learning and
Improvement
6.
Interpersonal and Communication
Skills
http://www.acgme.org/Outcome
Examples of a Checklist:
Knowledge
Rosen, Salas, Silvestri,
Wu, & Lazarra (2008)
Examples of a Checklist: Skill
Rosen, Salas, Silvestri,
Wu, & Lazarra (2008)
ACGME Components of
Assessment
1.
2.
3.
4.
5.
6.
7.
Assessment is consistent with
curriculum/program objectives.
The educational objectives are representative
of the educational domains of interest.
Multiple assessment approaches/instruments
are employed.
Multiple observations are conducted.
Multiple observers/raters provide
assessments.
Performance is assessed according to prespecified standards or criteria.
Assessment is fair.
http://www.acgme.org/Outcome/assess/Toolbox.pdf
Simulation: Procedural Skills
Kahol, Vanipuram & Smith
(2009)
Practice makes perfect

Issenberg et al. (1999): “The most
important identifiable factor separating
the elite performer from others is the
amount of “deliberate practice.” This
includes practice undertaken over a long
period of time to attain excellence as
well as the amount of ongoing effort
required to maintain it.”
Simulation experience:
More is More
McGaghie, Issenberg, Petrusa, & Scalese (2006):
Multiple-scenario Assessments
Murray, Boulet< Avidan, Kras, Henrichs, Woodhouse, and Evers (2007)
Impact on Safety Climate

Cooper et al (2008): “Contrary to our
expectations, the study gives no evidence
that CRM faculty training produced any
overall improvement in safety climate in the
experimental hospitals, compared to the
control hospitals.”
Patient Safety
1.
2.
3.
4.
5.
6.
7.
8.
Safety priority
Reporting
mistakes
Safety valued
Emergency
teamwork
Mgmt support
Safe workload
Asking for help
Reveal mistakes
Crisis Resource Management
MOSES course (UK): Multidisciplinary
obstetric simulated emergency
scenarios
 MOES system: Mobile obstetric
emergencies simulator

Retention rates
Crisis Resource Management

How often should CRM be practiced?
Simulation Research
Evidence still lacking

Outcomes research (Issenberg et al., 2005)
 BEME systematic literature review
 Focus was on education
Evidence still lacking

Outcomes research (Issenberg et al.,
2005)
Evidence still lacking

Outcomes research (Issenberg et al.,
2005)
Evidence still lacking

Outcomes research (Issenberg et al.,
2005)
Newer Evidence Promising
Barriers for Educators
Turcato, Robertson, & Covert (2008)
1. Time
2. Cost
3. Distance from Program
4. Scheduling
5. Lack of technical support
6. Lack of laboratory space
7. Lack of full-time equivalents
8. Administration unsupportive
Oregon: A Case Study
Collaborative Project
 Oregon Simulation Alliance
 Objective: address the demand for quality
simulation by making expertise available
and developing a statewide system.
 Members: Representatives from the
Governor’s office, organizations VPs, Area
Healthcare Education Centers (AHECs)
officials, public/private universities, the
Department of Public Health, and simulation
experts
Oregon: A Case Study

Outcomes:
○ Over $1,000,000 in funding for equipment,
○
○
○
○
○
simulation specialist training, and faculty
development
Education to help programs implement
Simulation training courses
16 simulation specialists trained
A statewide summit (networking; process
evaluation)
New simulation facilities
Oregon: A Case Study

Lessons learned:
 Need to encumber funds immediately after
site visits instead of concurrently (had to
accelerate site visits’ timeline)
 Hold awardees accountable for their use of
equipment (one member institution was not
meeting expectations)
 Hire a permanent director for the alliance
Oregon 2005
Seropian et al (2006)
Other interesting findings

Halamek (2008)
 NeoSim program developed
 First simulation-based training program in
neonatal medicine
 Steering committee: developed a list of
characteristics desired in a cost-effective
neonatal simulator
 Became the first RFP in simulator history
that a professional body rather than industry
drove the development of a simulator
The Public
IOM “To Err is Human”
 Recent evidence that Simulation works

 Captain Sullenberger
 “Doing the jobs we were
trained to do”
Simulation Professional
Organizations

Society for Simulation in Healthcare (SSH)
 Have a Journal: Simulation in Healthcare
 Founded by Dr. David Gaba
 2007: “the biggest step for simulation going
forward will not be technological, but will be
organizational”
Advanced Initiatives in Medical Simulation
(AIMS)
 International Meeting on Medical
Simulation

Gaba & Raemer (2007)
Professional Medical
Organizations
American College of Surgeons
 Accreditation Council for Graduate
Medical Education
 American Society of Anesthesiologists
 American Board of Anesthesiologists
 Society for Academic Emergency
Medicine

Professional Nursing
Organizations
National League of Nurses
 National Council of State Boards of
nursing
 American Association of Colleges of
Nursing
 American Association of Nurse
Anesthetists
 American Association of Critical Care
Nurses

Government Agencies
The US Food and Drug Administration
 The Agency for Healthcare Research &
Quality (AHRQ)
 16 states have legislature allowing high
fidelity simulation in lieu of clinical clock
hours; 17 have legislation pending

Malpractice Insurance

Harvard Medical School
 2-tier rate structure for anesthesiologists
 6% less for those who participated in ACRM
Cooper et al. (2008)
Web sources for simulation

Society of Simulation in Healthcare
 http://www.ssih.org/SSIH/SSIH/Home/

International Nursing Association for Clinical
Simulation and Learning
 http://www.inacsl.org/INACSL_2010/

Society in Europe for Simulation Applied to
Medicine
 http://www.sesam-web.org/

Advanced Initiatives in Medical Simulation
(AIMS)
 http://www.medsim.org/
Cannon-Diehl (2009)
Web sources for simulation

Center for Immersive and Situationbased Learning
 http://cisl.stanford.edu/

Center for Medical Simulation
 http://www.harvardmedsim.org/

SIMS Medical Academy
 http://www.simsacademy.info/

University of Pittsburg, WISER
 http://www.wiser.pitt.edu/
Cannon-Diehl (2009)

Pennsylvania
State University
has a mobile
simulation
program
Key Points






Simulation is a valuable tool for skill
acquisition and maintenance
Crisis Resource management imparts team
coordination skills
Evaluation tools are still under
development (checklists/global pairs)
More Outcomes research needed
Multiple scenarios should be used for high
stakes evaluation
Perhaps a culture of continued crisis
competence would yield better results than
biennial competence testing
Closing Quote

Gaba, “no industry in which human lives
depend on skilled performance of
responsible operators has waited for
unequivocal proof of the benefit of
simulation before embracing it.”
References





Accreditation Council for Graduate Medical Education (2000).
Toolbox of Assessment Methods. Retrieved from
http://www.acgme.org/Outcome/assess/Toolbox.pdf
Bond, W., Kuhn, G., Binstadt, E., Quirk, M., Tews, M., Dev,
P., & Ericsson, A. (2008). The use of simulation in the
development of individual cognitive expertise in emergency
medicine. Academic Emergency Medicine, 15, 1037-1045.
Bould, MD., Crabtree, NA., & Naik, VN. (2009). Assessment
of procedural skills in anesthesia. British Journal of
Anesthesia, 103 (4), 472-483.
Cannon-Diehl, MR. (2009). Simulation in healthcare and
nursing. Critical Care Nursing Quarterly, 32 (2), 128-136.
Cooper, JB., Blum, RH., Carrol, JS., Dershwitz, M., Feinstein,
DM., Gaba, DM., Morey, JC., & Single, AK. (2008).
Differences in safety climate among hospital anesthesia
departments and the effect of a realistic simulation-based
training program. Anesthesia & Analgesia, 106 (2), 574-584.
References






DeAnda, A., & Gaba, DM. (1990). Unplanned incidents during
comprehensive anesthesia simulation. Anesthesia & Analgesia,
71, 77-82.
Ericsson, KA. (2004). Deliberate practice and the acquisition
and maintenance of expert performance in medicine and
related domains. Academic Medicine, 79 (Supp), S70- S81.
Fitts, PM., & Posner, MI. (1979). Human Performance.
Westport: Greenwood Press.
Friedman, Z., Siddiqui, N., Katznelson, R., Devito, I., Bould,
MD., & Naik, V. (2009). Clinical impact of epidural anesthesia
simulation on short- and long-term learning curve. Regional
Anesthesia and Pain Medicine, 34 (3), 229-231.
Gaba, D. (2007). The future vision of simulation in healthcare.
Quality & Safety in Healthcare, 13(Supp1), i2-i10.
Gaba, DM., & DeAnda, A. (1989). The response of anesthesia
trainees to simulated critical incidents. Anesthesia & Analgesia,
68, 444-451.
References






Gaba, DM, & DeAnda, A. (1988). A comprehensive anesthesia
simulation environment. Anesthesiology, 69, 387-394.
Gaba, D., & Raemer, D. (2007). The tide is turning: organizational
structures to embed simulation in the fabric of healthcare. Simulation in
Healthcare, 2(1), 1-3.
Halamek, LP. (2008). The simulated delivery-room environment as the
future modality for acquiring and maintaining skills in fetal and neonatal
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Hoadley, TA. (2009). Learning advanced cardiac life support: A
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Holzman, RS., Cooper, JB., Gaba, DM., Philip, JH., Small, SD., &
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Isaacson, JJ., 7 Stacy, AS. (2009). Rubrics for clinical evaluation:
Objectifying the subjective experience. Nurse Education in Practice, 9:
134-140.
References





Issenberg, SB, & Scalese, RJ. (2008). Simulation in health care
education. Perspectives in Biology & Medicine, 51(1), 31-46.
Issenberg, SB., McGaghie, WC., Hart, IR., Mayer, JW., Felner, JM.,
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Issenberg, SB., McGaghie, WC., Petrusa, ER., Gordon, DL., &
Scalese, RJ. (2005). Features and uses of high-fidelity medical
simulations that lead to effective learning: a BEME systematic
review. Medical Teacher, 27 (1), 10-28.
Jeffries, P. (2005). A Framework for designing, implementing, and
evaluate simulations used as teaching strategies in nursing.
Nursing Education Perspectives, 96-103.
Kaakinen, J., & Arwood, E. (2009). Systematic review of nursing
simulation literature for use of learning theory. International Journal
of Nursing Education Scholarship, 6(1), 1-20.
References





Kahol, K., Vankipuram, M., & Smith, M. (2009). Cognitive
simulators for medical education and training. Journal of
Biomedical Informatics, 42, 593-604.
Knudson, MM., Khaw, L., Bullard, K., Dicker, R., Cohen, MJ.,
Staudenmayer, K. . . Krummel, T. (2008). Trauma training in
simulation: Translating skills from SIM time to real time. The
Journal of Trauma, 64 (2), 255-264.
Lammers, RL. (2008). Learning and retention rates after training
in posterior epistaxis management. Academic Emergency
Medicine, 15, 1181-1189.
Lammers, RL., Davenport, M., Korley, F., Griswold-Theodorson,
S., Fitch, M., Narang, A. . . . Robey, WC. (2008). Teaching and
assessing procedural skills using simulation: metrics and
methodology. Academic Emergency Medicine, 15: 1079-1087.
Manser, T., Harrison, TK., Gaba, DM., & Howard, SK. (2009).
Coordination patterns related to high clinical performance in a
simulated anesthetic crisis. Anesthesia & Analgesia, 108 (5),
1606-1615.
References





McGaghie, WC., Issenberg, SB., Petrusa, ER., & Scalese, RJ.
(2006). Effect of practice on standardised learning outcomes in
simulation-based medical education. Medical Education, 40:
792-797.
McLaughlin, S., Fitch, MT., Goyal, D., Hayden, E., Yang Kauh,
C., Laack, T. . . Gordon, JA. (2008). Simulation in graduate
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