R E S E A R C H Open Access
Use of simulation as a needs assessment to
develop a focused team leader training
curriculum for resuscitation teams
Susan Coffey Zern
, William J. Marshall
, Patricia A. Shewokis
and Michael T. Vest
Background: Many inpatients experience cardiac arrest and mortality in this population is extremely high.
Simulation is frequently used to train code teams with the goal of improving these outcomes. A key step in
designing such a training curriculum is to perform a needs assessment. We report on the effectiveness of a
simulation-based training program for residents designed using unannounced in-situ simulation cardiac arrest data
as a needs assessment.
Methods: In order to develop the curriculum for training, a needs assessment was done using in-situ simulation.
Prior to instruction, residents were assessed in their ability to lead a simulated resuscitation using a standardized
checklist. During the intervention phase, residents participated in didactic and team training. The didactic training
consisted of pharmacology review, ACLS update and TeamSTEPPS training. Residents took turns as code team
leader in three simulation sessions. Rapid cycle deliberate practice (RCDP) was employed as part of simulation
sessions. All residents returned, for post-intervention assessment. Mean pre-post test scores were analyzed to
determine if there was a significant difference.
Results: Twenty-seven residents participated. Mean pre-training assessment score was 47.6 (95% CI 37.5-57.9).
The mean post-training assessment score was 84.4 (95% CI 79.0-89.5). The mean time to defibrillation after
pads were placed in scenario with shockable rhythm decreased from 102.2 seconds (95% CI 74.0-130.5) to
56.3 (95% CI 32.7-79.8).
Conclusion: Using unannounced in-situ cardiac arrest simulations as a needs assessment, a simulation-based
training program was developed that significantly improved resident performance as team leader. Future work
is needed to determine if this improvement translates into patient benefits and is sustainable. However, in-
situ simulation is a promising tool for curriculum development.
Keywords: Cardiac Arrest, Medical Education, Advanced Cardiac Life Support, Team Training, curriculum
development, needs assessment, gap analysis
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* Correspondence: email@example.com
Department of Internal Medicine, Section of Pulmonary and Critical Care
Medicine, Christiana Care Health System, 4755 Ogletown-Stanton Road,
Medical Intensive Care Unit, 3E, Newark, Delaware 19713, USA
Sidney Kimmel Medical College, Philadelphia, PA, USA
Full list of author information is available at the end of the article
Zern et al. Advances in Simulation (2020) 5:6
Cardiac arrest affects approximately 209,000 adult pa-
tients in hospitals in the United States every year .
Additionally, national statistics show outcomes are poor
for those patients. Only 1 in 4 in hospital cardiac arrest
patients will survive to hospital discharge. Moreover,
those patients that survive often have neurological se-
quela from the event . Survival for patients who have
cardiac arrest at night and on weekends has been shown
to be worse than for patients who undergo cardiac arrest
during the work day using national data from both the
United States and the United Kingdom [3,4].
While it is typically a rare event for an individual
healthcare provider, a cardiac arrest can be called mul-
tiple times a week in our 1,100-bed private teaching hos-
pital system. Our inpatient code teams are led by a
resident physician who has completed at least one post
graduate year of training and American Heart Associ-
ation (AHA) Advanced Cardiac Life Support (ACLS)
training. These residents typically do not receive formal
training in teamwork and communication or team leader
training, yet they are expected to employ these nontech-
nical skills during a cardiac arrest event [5,6]. Although
the AHA has imbedded team leader training into the
ACLS courses, the major focus of the course continues
to be on medical management. Additionally, teamwork
and communication skills necessary to be a team leader
are not a formal component of the medical education
curriculum for medical students or residents . As a
result of limited training, this skill set is difficult to em-
ploy when the resident is involved in an emergency situ-
ation with a high mental workload, new skills, and an ad
hoc team [7,8]. The AHA 2015 ACLS guideline updates
recognize that ACLS training every two years is not suf-
ficient . However, while supporting the use of simula-
tion training in general, they acknowledge that the
optimal approach to ACLS education for resuscitation
team members is unknown and call for additional re-
search in this area.
Although resuscitation training is a common need, it
is a complex undertaking for many institutions .
Curriculum development as described by Kern, needs to
address multiple steps. One of the steps in developing
the curriculum is determining the needs assessment.
This step allows for an understanding of the differences
between the learner’s expected performance versus their
actual performance . While traditionally simulation
is used for training or for an intervention, it can also be
used to determine gaps in knowledge, skill and abilities.
Using in-situ simulation to perform a needs assessment
can inform curriculum development targeted to a spe-
cific learner group. We hypothesized that simulation can
be used as an effective tool for the purpose of developing
The goal of this study was to determine if a needs as-
sessment performed using in-situ simulation would be
an effective method for simulation-based resuscitation
curriculum development, as measured by improved resi-
dent performance. We choose time to defibrillation as
the primary performance outcome because it is easily
measured, objective, and associated with clinically im-
In order to accurately define the needs assessment for
resuscitation curriculum development, we used in-situ
simulation sessions. We conducted five unannounced
in-situ cardiac arrest simulations throughout our hos-
pital system. We specifically focused on the behavior of
the team leader, as the curriculum would be designed to
train only the team leader. Since our hospital resuscita-
tion team is a contingency team the residents are a
stable member and as such could have a substantial im-
pact on overall team effectiveness.
In each of the in-situ simulations, a resident physician
was the team leader. Team Leader behavior was ob-
served by S.C.Z., W.M. and M.V. We evaluated each
simulated in-situ cardiac arrest using ACLS guidelines
and the TeamSTEPPS Team Performance Observation
Tool . Table 1shows the areas of opportunity noted
in at least four of five in-situ simulations. The areas of
opportunity informed curriculum development for our
intervention. Our intervention as described below was
Table 1 Results of in situ Evaluation Parameters for Needs
TeamSTEPPS Performance Observation - Areas of Opportunity
Team Leader did not Identify themselves as leading the resuscitation
Team Leader did not assign roles and responsibilities
Team leader failed to maintain situational awareness throughout the
Team Leader did not foster communication to ensure team members
have a shared mental model
Team Leader failed to collaborate with team members
Team Leader did not provide timely and constructive feedback to team
members, i.e. rate and quality of chest compressions
Closed Loop Communication was lacking or non-existent during the
AHA ACLS Guidelines –Areas of Opportunity Noted
Quality of chest compressions varied with team leader failing to monitor
Airway management was not assessed
Time to initial shock was variable
Cardiac rhythm was not announced to the team
AHA: American Heart Association, ACLS: Advanced Cardiac Life Support
Zern et al. Advances in Simulation (2020) 5:6 Page 2 of 7
designed to ensure that the areas of opportunity noted
during our needs assessment, would be taught and
We conducted a pretest-posttest study to evaluate the
impact of a new, annual resident resuscitation team
leader training curriculum designed based on needs as-
sessment using in-situ simulation. The course was con-
ducted in the Virtual Education and Simulation Training
(VEST) Center at the Christiana Care Health System.
This study was submitted to the Christiana Care Institu-
tional Review Board and was determined to be exempt.
Participants were resident physicians completing their
first post graduate year (PGY-1) of residency. They were
required to be previously certified in Basic Life Support
(BLS) and ACLS. All PGY-1 residents in internal and
family medicine programs in the spring of 2016 at Chris-
tiana Care were required to participate in the training.
Curriculum description and intervention
The curriculum started with a pre-assessment of the res-
ident’s skills in the simulation center. This was done
after curriculum was set and was separate from the in-
situ simulations used for the needs assessment. Each
resident was assessed on their ability to lead a cardiac
arrest with a standardized interprofessional team. A
team of confederates was trained to play the roles of a
respiratory care provider, a medical intensive care nurse,
a bedside nurse and three medical students using a stan-
dardized scenario. The scenario’s objectives and check-
list evaluation were based on the gaps noted in the in-
situ needs assessment. In each scenario, two errors were
purposely made by the standardized team; one was in-
accurate closed loop communication by the MICU nurse
and the other was a medical student slowing down the
rate of chest compressions. METIman® pre-hospital
model or nursing model, patient simulator (CAE Health-
care) was used. The resident was blinded to the areas of
assessment as the team leader. The session was termi-
nated at the end of the third cycle of chest compres-
sions. Each pre-assessment was video recorded and
evaluated using a checklist, by one of two trained evalua-
tors. After running the cardiac arrest, each resident was
given a rhythm recognition test using HEARTSIM 200,
rhythm generator (Laerdal) where they had 20 seconds
to report each rhythm to an evaluator.
For the intervention, all the residents received the
same training including both didactic and TeamSTEPPS®
simulation training. The residents were split into two
groups (Group A and Group B) specifically to ensure
that the groups were small in size, not to assess order of
the training. Figure 1outlines the agenda. One group
attended didactic lectures for 1½ hours which included
pharmacology review, ACLS update and review, and spe-
cial situations (i.e., caring for coding pregnant patients).
They were given an electronic multiple-choice test to as-
sess their knowledge of the content (content exam).
The other group attended TeamSTEPPS® didactic
training session by a TeamSTEPPS® master trainer, fo-
cusing on the role of the team leader. They then partici-
pated in three simulation scenarios with rapid cycle
deliberate practice for 1 ½ hours. TeamSTEPPS® is an
evidence-based systematic training, developed by the De-
partment of Defense (DOD) and the Agency for Health-
care Research and Quality (AHRQ), used to improve
and integrate teamwork and communication into health-
care delivery. There are five tenets of TeamSTEPPS®;
Fig. 1 Class divided to keep groups small for teaching purposes. Both groups received same intervention
Zern et al. Advances in Simulation (2020) 5:6 Page 3 of 7
team structure, communication, leading teams, situ-
ational monitoring and mutual support . These key
principles are important for a resident to understand, ex-
hibit and support as the resuscitation team leader.
After the TeamSTEPPS® didactic session, the residents
then took turns being the team leader in three simula-
tion scenarios (Table 2) with a standardized resuscitation
team of trained confederates assuming the roles of the
typical members who would normally respond, RCP,
MICU Nurse, Bedside nurse, and three people to provide
chest compression. The focus of the simulation scenar-
ios was teamwork and communication. Rapid cycle de-
liberate practice (RCDP) was employed as part of the
session with the faculty facilitators stopping the session
for skills that required immediate correction, further
practice or opportunities to highlight something done
exceptionally well, as was described in Hunt, et al 2014
. Only one resident at a time was the team leader,
the other residents were in the room watching them lead
the code but were not permitted to speak or assist in
anyway. Each simulation session was performed in a dif-
ferent room with a different patient case. Each resident
participated as the leader in one of the three scenarios.
The resident led a cardiac arrest scenario and received
immediate correction or praise for their performance.
We chose RCDP as a means of debriefing to ensure that
the residents were able to practice the new skills many
times and learn vicariously while watching their peers.
All residents individually returned to the simulation
center between three to five weeks later for a post-
intervention assessment. The same scenario used for the
pre-assessment was used again. The team leader was ex-
pected to run the cardiac arrest with a standardized in-
terprofessional team, and the standardized scenario.
Each assessment was video recorded, evaluated by
checklist by one of two trained evaluators using the
same checklist as the pre-assessment. The resident was
debriefed after the cardiac arrest. Overall scores were
compared pre and post training.
Descriptive statistics and assumptions for parametric
tests were calculated for the following variables car-
diac arrest pre-test and post-test scores; rhythm
visible-time to shock delivered (RVTSD) pre-test and
post-test scores; content exam and rhythm recogni-
tion test. If the normality assumptions were violated,
then appropriate non-parametric tests were calculated.
To determine the effectiveness of the intervention,
parametric paired t-tests were used to compare pre
and post test scores on the code blue and RVTSD
tests. The content exam (electronic multiple choice
test) and rhythm tests were administered only once
and a criterion of 80% competency or better was used
for passing. A one sample t-test was calculated for
the content exam and rhythm test. Effect sizes were
calculated and used to aid in interpretation of the
data. The effect size index for the paired t-test and
one-sample t-test is Cohen’sd
interpreted as d
= 0.20, 0.50 and > 0.80 as small,
medium and large effects, respectively. To assess any
order effects of the grouping of participants, we cal-
culated independent samples t-tests (two-tailed) with
a significance criterion of α= 0.05. Since there were
multiple tests employed, we used a Bonferroni adjust-
ment to control for Type I error inflation (alpha/6 =
0.0083). The significance criterion for all tests was set
at α= 0.05. Number Cruncher Statistical Software
(NCSS ver. 9; www.ncss.com) was used for the
Table 2 Team Work and Communication Scenarios using Rapid Cycle Deliberate Practice (RCDP) Debriefing
Case Rhythm Scenario
1 PEA Arrest Adult patient was admitted overnight for deep tissue infection on left leg. He recently had a subclavian central line inserted.
Breath sounds are decreased on right side of the chest one minute into the code.
•Cardiac Arrest starts with bedside nurse in the room doing compressions
•Code Team comes in with the resident team leader
•After two minutes the confederate Respiratory Care Provider comments that ventilating has gotten more difficult
2 Slow V
Adult patient is admitted for lumbar discectomy. He has peripheral IV access.
•Cardiac arrest starts with multiple nurses in the room
•Pads are on the chest
•CPR is in progress
•Defibrillator is in AED mode and is still on
•Code team comes in with the team leader
3 PEA Arrest Adult patient was admitted overnight with concern for sepsis. He has peripheral IV access. Patient was noted to have elevated
lactate levels as per bedside nurse report.
•Cardiac arrest starts with bedside nurse in the room
•No pads are on the patient
•Code team comes in with the team leader
•After the first rhythm check the MICU nurse states that the IV is lost and not working
PEA –Pulseless Electrical Activity, V Tach –ventricular tachycardia, CPR –cardiopulmonary resuscitation, AED –automatic electrical defibrillator, IV –
Zern et al. Advances in Simulation (2020) 5:6 Page 4 of 7
A total of 27 residents completed the training; 14 were
female and 13 male, there were internal medicine (n=
12), combined internal medicine/pediatrics (n= 4) family
medicine (n=6) and there were combined internal medi-
cine/emergency medicine residents or family medicine/
emergency medicine (n=5). Sixty-one percent reported
having attended five or more cardiac arrests, in clinical
care within the past year.
The competency level was set at 80% for the all assess-
ments. An 80% or better performance is typically noted as
the criterion for competent performance . Descriptive
statistics and 95% confidence intervals are reported in
Table 3for all measures. The effect of simulation training
with rapid cycle deliberate practice significantly improved
cardiac arrest performance overall [t(26) = -6.248, p<
= -1.20] and time to shock delivery (RVTSD)
[t(26) = 3.127, p =0.004, dz = 0.60) specifically. Cardiac ar-
rest scores showed a large effect while RVTSD scores re-
sulted in a moderate-to-large effect. A significant effect
was detected for the mean content exam [t(26) = 2.93, p =
= 0.56] indicating that the content exam (elec-
tronic multiple choice test) was able to reliably discrimin-
ate between high performing residents and low
performing residents. No significant difference was de-
tected for the rhythm test [t(26) = 0.132, p 0.448, d
0.03] showing that there was no reliable discrimination
between the high performing and low performing resi-
dents based on the rhythm test. There was no difference
in performance related to whether residents were assigned
to group A or group B (p>0.05).
In the debriefing, the residents commented that in the
pre assessment the confederate team was difficult to lead
and seemed to lack content knowledge and skill in re-
suscitation. Their comments at the post assessment were
entirely different; they felt that the team was much bet-
ter trained and more knowledgeable regarding resuscita-
tion. They initially did not attribute this to their
improved leadership skills. However, we used the same
simulation case and standardized team of confederates
for pre and post assessments so that we controlled the
team’s performance and ensured that it was not signifi-
cantly different between the two assessments.
The use of in-situ simulation to determine a needs as-
sessment enabled the simulation curriculum to incorpor-
ate the exact problems and barriers the resident would
experience in clinical care. It ensured that we were
teaching to the actual gaps in knowledge and skills. We
addressed issues that the residents demonstrated during
the gap analysis such as closed loop communication,
maintaining situational awareness and assigning roles
and responsibilities. Importantly, after training in these
leadership skills we observed an improvement in the
clinically important outcome of time to defibrillation.
Needs assessments in medical education are often
done using data gathered from surveys, structured inter-
views, observations of clinical practice, or peer review
data . Focus groups have been described as a method
to assess needs for simulation based emergency training
. The incorporation of input from multiple stake-
holders (insurers, educational institutions, funders, em-
ployers, regulators) has also been described in the
development of simulation curriculum . In addition
to the above methods for gathering data to inform cur-
riculum development, in-situ simulation can be consid-
ered an additional option. To our knowledge, this is the
first time that using simulation to perform both a needs
assessment and an intervention has been reported.
By using in-situ simulation as a needs assessment tool,
we developed a focused curriculum to meet the needs of
our residents, rather than just repeating training in
ACLS. While AHA acknowledges that every 2 years
training in ACLS is not sufficient, the best approach to
training during that interim 2-year period is unknown.
We believe that in-situ simulation alone is unlikely to
correct deficits. However, using in-situ simulation to
identify gaps and addressing them with a focused cur-
riculum informed by this assessment, has potential to be
an effective approach. We are currently using in-situ
simulation for needs assessment for other areas of emer-
gency response including pediatric, surgical, neurologic
and obstetric emergencies. Future work will be needed
to determine the optimal time frame to repeat in-situ
simulation for the purpose of re-assessing the need for
curriculum developed in this fashion.
Table 3 Descriptive Statistics and 95% Confidence Intervals of the Dependent Measures
Variable Time Mean + SD 95% Confidence Interval (LL, UL)
Cardiac arrest team leader performance Pre-test 47.6 + 25.9 (37.3, 57.9)
Cardiac arrest team leader performance Post-test 84.3 + 13.3 (79.0, 89.5)
RVTSD Pre-test 102.2 + 21.4 (74.0, 130.5)
RVTSD Post-test 56.3 + 59.5 (32.7, 79.8)
Rhythm Test Once 80.4 + 14.5 (74.6, 86.1)
Content Exam Once 86.0 + 10.7 (81.8, 90.3)
RVTSD –rhythm visible time to shock delivered, SD –standard deviation, LL –lower limit, UL –upper limit. Con tent Exam was an electronic multiple choice exam
Zern et al. Advances in Simulation (2020) 5:6 Page 5 of 7
We found that training of the team leader in ACLS
and teamwork and communication skills using Team-
STEPPS® with RCDP can improve team performance in
simulated cardiac arrest. Prior work has shown improve-
ments in clinical outcomes of pediatric patients after
simulation based code team training . Our study dif-
fered in that we focused our intervention only on the
resident code team leaders. This is important because
many institutions, including ours, are faced with training
thousands of healthcare providers to respond to cardiac
arrest emergencies. While we believe that training the
actual responding team is optimal, when this is not lo-
gistically possible, our data suggest that training focused
on the team leader may still have a positive impact.
We noted that many cycles of deliberate practice were
needed for residents to effectively employ TeamSTEPPS®
skills. Using simulation scenarios with RCDP allowed
the residents to practice the expected technical and non-
technical skills over and over until they became a habit.
Our goal was to make sure the newly learned Team-
STEPPS® concepts and tools would be solidly incorpo-
rated into each resident’s repertoire, i.e. assessing chest
compressions, assigning roles and responsibilities, etc.
RCDP may be particularly effective debriefing method to
use in a focused simulation developed using in-situ
simulation as a needs assessment tool.
Our study has several limitations. First, we cannot de-
termine the impact our training had on actual patients.
Second, while all post-graduate year one medicine resi-
dents at our institution participated, this was a small
study at one institution, and it would be important to
know if the same findings could be replicated in larger
studies at other institutions. Also, all participants re-
ceived training, so the lack of a control group is a limita-
tion of this study. Future work will need to determine
the durability of this training and impact on actual pa-
tients. Lastly, the training sequence may have had an im-
pact on resident learning and retention.
In conclusion, a novel code team leader training course
using in-situ simulation data to develop the curriculum
and combining TeamSTEPPS® principals and ACLS sci-
ence update can provide sustained improvement in resi-
dent performance as code team leaders.
ACLS: Advanced Cardiac Life SupportRCDPRapid Cycle Deliberate
PracticeAHAAmerican Heart AssociationTeamSTEPPSTeam Strategies and
Tools to Enhance Performance and Patient SafetyBLSBasic Life
SupportMICUMedical intensive care unitRCPRespiratory care
providerDODDepartment of DefenseAHRQAgency for Healthcare Research
and QualityRVTSDRhythm Visible-time to shock delivered
SCZ, WJM and MTV contributed to design of the study and data collection.
PAS performed statistical analysis. All authors contributed to the analysis of
data and drafting of manuscript. All authors contributed to manuscript
revisions and approved the final version of manuscript.
SCZ is Director of Simulation, Virtual Education and Simulation Training
(VEST) Center, Christiana Care Health System. WJM is Simulation Specialist
Coordinator, Virtual Education and Simulation Training (VEST) Center,
Christiana Care Health System. He is also a nurse with extensive experience
in emergency medicine and an ACLS instructor. PAS is Professor, College of
Nursing and Health Professions, School of Biomedical Engineering, Science
and Health Systems, and School of Education at Drexel University. MTV is a
critical care physician at Christiana Care Healthcare System and an Assistant
Professor of Medicine at Sidney Kimmel Medical College.
No external source of funding
Availability of data and materials
The datasets generated and/or analyzed during the current study are not
publicly available due to need to protect the privacy of the trainees who
participated but are available from the corresponding author on reasonable
Ethics approval and consent to participate
This study was submitted to the Christiana Care Institutional Review Board
and was determined to be exempt.
Consent for publication
The authors declare that they have no competing interests.
Virtual Education and Simulation Training (VEST) Center, Christiana Care
Health System, 4755 Ogletown-Stanton Road, Ammon MEC LE86B, Newark,
Delaware 19718, USA.
Nutrition Sciences Department, College of Nursing
and Health Professions; School of Biomedical Engineering, Science and
Health Systems, and Department of Teaching, Learning & Curriculum, School
of Education, Drexel University, 3rd Floor, Room 382, Parkway Building, 1601
Cherry Street, Mail Stop 31030, Philadelphia, PA 19102, USA.
Internal Medicine, Section of Pulmonary and Critical Care Medicine,
Christiana Care Health System, 4755 Ogletown-Stanton Road, Medical
Intensive Care Unit, 3E, Newark, Delaware 19713, USA.
Medical College, Philadelphia, PA, USA.
Received: 15 September 2019 Accepted: 14 May 2020
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