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Educated Hand Publishing LLC 
“The Science Behind the Art” 
Volume 6 - No. 2 2018 

Anesthesia eJournal - Online
ISSN 2333-2611

Page 7

Student Registered Nurse Anesthetists: Impact of Structured High-fidelity Simulation on 
Anesthesia Ready Time

Michele M. Ballister, DNP, CRNA, APRN, CHSE

Affiliation:
Assistant Professor at Medical University of South Carolina, Charleston, SC.

Funding/Conflict of Interest Disclosure: 
None

KEYWORDS:  anesthesia, nurse anesthesia, simulation, high-fidelity simulation, anesthesia ready time

INTRODUCTION
Nurse anesthesia educators are challenged to provide innovative training programs that prepare student registered nurse 
anesthetists (SRNAs) to care for a diverse patient population that is living longer with multiple comorbidities.1 Use of 
simulation, including lifelike mannequins, interactive computer programs, and actors role-playing as patients, has gained 
increasing popularity in health care programs, especially nursing schools, around the world.2 In 2012, 96% of nurse anesthesia 
programs reported the use of simulation within the curriculum.3

The nurse anesthesia program (NAP) at a large academic medical center strives continually to increase the quality of student 
experiences. In class sizes ranging from 26 to 30 students, SRNAs complete 12 months of classroom instruction followed 
by 16 months of clinical training. Within that time, each student must complete a certain number of surgical cases plus a 
required number of specific skills. These cases, required by the Council on Accreditation of Nurse Anesthesia Programs, 
involve skills as simple as preparing medications in syringes and as complex as managing a patient with multiple traumatic 
injuries.4

While the NAP program has partnered with many hospitals throughout both South Carolina and Georgia to provide 
students the necessary clinical experiences, often these institutions will not accept a student until after the student’s third or 
fourth month of clinical training. Anesthesia department administrators contend that novice SRNAs slow the fast pace of 
the operating room (OR) because they require too much instruction. Unfortunately, this strictly subjective observation greatly 
limits early student experiences.

Abstract
Introduction: Student registered nurse anesthetists (SRNAs) at a large academic medical center are limited in clinical 
training experiences owing to the subjective perception by local anesthesia department administrators of decreased oper-
ating room efficiency with SRNA involvement. The purpose of this project was to utilize structured high-fidelity simula-
tion (HFS) to increase basic skill proficiency in SRNAs and evaluate the impact of the simulation within the first month 
of clinical training.
Methods: Utilizing the Iowa Model of Evidence-Based Practice to Promote Quality Care, a 5-week structured HFS 
program was inserted into the nurse anesthesia curriculum before the SRNAs’ first clinical rotation. The program pro-
moted basic anesthesia skill proficiency through the assimilation of previously taught and tested technical skills. In-room 
times and anesthesia ready times of all SRNA cases involving general anesthesia with the placement of an endotrache-
al tube during September 2012 and 2013 were compiled by use of retrospective chart review. Using the calculation of 
elapsed time between in-room time and anesthesia ready time (IRTART), the clinical performance of 2 consecutive 
classes of SRNAs was compared, one with structured HFS training and one without.
Results: The mean IRTART for both groups was similar at 20 minutes with a standard deviation of 10 minutes. The 
IRTARTs from both groups were within the institution’s operative norm.
Conclusion: Structured HFS did not impact the anesthesia ready time of new-to-practice SRNAs. However, the in-
formation collected during implementation of HFS and data analysis can be used to develop future avenues to improve 
current processes for structured HFS and clinical training opportunities.

AEJ



Anesthesia eJournal          www.anesthesiaejournal.com
Volume 6 - No. 2 2018 Page 8

The anesthesia ready time (ART) is a timestamp noted in 
the electronic health record (EHR) that is used to determine 
anesthesia efficiency. It is defined as the “time when a surgical 
patient has a sufficient level of anesthesia established to begin 
surgical preparation.”5 Anesthesia efficiency can be estimated 
by the elapsed time between ART and the time the patient 
is brought into the surgical suite (in-room time). Because a 
surgery cannot begin until the patient is properly anesthetized, 
any setback the SRNA encounters in anesthetizing the patient 
delays the start of the procedure. Many basic anesthesia skills are 
utilized during the induction sequence of a general anesthetic. 
An increased proficiency in basic skills can ensure that SRNA 
performance does not hinder surgical start times.
Purpose of the Study
This project had a dual purpose. The first was to utilize structured 
high-fidelity simulation (HFS) to increase basic skill proficiency 
in SRNAs before the start of clinical training. The second was to 
evaluate the impact of structured HFS training on the time from 
in-room time to ART (IRTART) of SRNAs during their first 
month of clinical training. It was hypothesized that structured 
HFS would improve SRNA performance and decrease SRNA 
IRTART.
Review of the Literature
An abundance of the literature focuses on simulation in health 
care education. Spanning both quantitative and qualitative 
designs, examples of the use of simulation include teaching 
specific tasks, increasing practical knowledge, developing critical 
thinking skills, increasing student confidence, and decreasing 
participant anxiety. For this study, evidence of HFS as a teaching 
tool for foundational skills was examined to include which 
elements to include as well as examples of implementation of 
simulation.
Noted by the Institute of Medicine as a learning enhancement 
tool,6 HFS is a training method that exposes SRNAs to a variety 
of situations they will face as providers in the OR both as trainees 
and later as CRNAs. With the use of a computerized mannequin 
(human patient simulator), a variety of scenarios can be created 
that offer the SRNA an opportunity to interact with different 
patient conditions and to experience surgical situations and 
complications in real time.7 An ideal environment for experiential 
learning, HFS offers SRNAs the opportunity for intervention and 
reflection to determine what actions are most relevant to clinical 
practice.8 Most importantly, HFS allows for uninhibited student 
learning without threats to patient safety, threats to quality of 
care, or fear of blame.9

A 2005 review highlighted 10 essential elements of simulation: 
feedback, repetitive practice, integration of simulation in curricula, 
a range of levels of difficulty, multiple learning strategies, 
a controlled environment, individualized learning, clinical 
variation, defined outcomes, and simulator validity.10 Additional 
recommendations include a faculty demonstration to visually 
define the outcomes for participants.11 Use of these elements 
within nursing education varies. A 2010 survey of International 
Nursing Association of Clinical Simulation members noted 
structural differences in theory utilization, videotaping of 
sessions, debriefing practices, substitution for clinical time, and 
equipment.2 The literature does not support a standard theory or 

framework for integration of simulation within a curriculum nor 
does it recommend a specific evaluation tool.2

In 2011, Meyer et al utilized many of the recommended essentials 
when implementing simulation into an undergraduate nursing 
curriculum.12 With scenarios of progressing difficulty, nursing 
students repeatedly experienced situations and performed skills 
common in pediatrics.12 Simulation-trained students earned 
higher and more consistent scores on a Likert-style tool, leading 
Meyer et al to conclude that student clinical performance 
was increased as a direct result of simulation.12 This finding 
suggested positive skill transfer from the simulator to the clinical 
environment through the use of recommended elements.
With the purpose of this study being to improve basic skill 
proficiency, all the essential elements were incorporated into 
the simulation program except for varied levels of difficulty. 
Repetition of skills was patterned after Meyer’s study and the 
skills most common within a general anesthetic induction were 
incorporated. For this study, feedback was defined as immediate 
debriefing following the completion of a simulation.11

Theoretical Framework
The Iowa Model of Evidence-Based Practice to Promote Quality 
Care (Iowa Model)13 served as the theoretical framework for this 
study. Beginning with the identification of a clinical problem, 
the model provides a step-by-step guide for implementing 
change. The model starts with critical questions focused on how 
the clinical problem impacts the institution and what, if any, 
foundational research is available. If sufficient evidence exists, the 
model promotes implementation of change and then evaluation 
to determine if change is appropriate for adoption into practice. 
If not, the framework redirects improvement efforts toward 
soliciting more information or narrowing the initial focus of the 
clinical problem. The unique questions built into the framework 
require repeated reflection and review at different stages of the 
process, thereby keeping the project on target with goals and 
ensuring orderly completion of necessary steps. Answering the 
questions, in sequence, keeps the project narrowly focused.
METHODS
Participants
After institutional review board approval, this process 
improvement plan utilized a comparative study design. The 
intervention group consisted of 10 SRNA volunteers who had 
just completed the didactic portion of a front-loaded nurse 
anesthesia curriculum. The comparison group was the SRNAs of 
the prior year who did not receive structured HFS training.
The intervention group participants committed to a HFS 
program that began with orientation to the simulator and viewing 
a faculty demonstration video. Orientation included informed 
consent, explanation of the purpose of the project, and participant 
expectations. The video provided a standard of performance and 
demonstrated the skills that participants would use to successfully 
negotiate the scenarios.
Scenarios
SRNAs trained once a week for 5 weeks with the Laerdal 
SimMan 3G (SimMan), a high-fidelity computerized interactive 
mannequin, to assimilate the information taught in prior skill labs 
to include: anesthesia machine check, medication preparation, 
airway equipment preparation, and anesthesia induction. 



Anesthesia eJournal          www.anesthesiaejournal.com
Volume 6 - No. 2 2018 Page 9

Although the tasks may be considered noncomplex, completing 
them in succession and in the proper order can be a challenge 
for novice SRNAs. The simulation exercises focused on these 
skills and enhanced performance through repetition. A section 
of the SRNA skills laboratory was arranged similarly to an OR 
and included a functional anesthesia machine with ventilator, 
the mannequin, an operating table, a stocked anesthesia cart, and 
distilled water for medication simulation.
The scenario began with the SRNA bringing the mannequin 
to the OR and transferring the mannequin to the surgical table 
and ended when the participant secured the breathing tube. The 
performance of the SRNA was immediately analyzed by using 
both the scenario script and the video recording as references. 
Time was allotted for facilitator-student feedback and questions. 
All SRNAs completed the same scenarios, were video recorded, 
received feedback, and deleted their videos before exiting the 
simulator. SRNA performance was not graded as part of the NAP 
curriculum.
Data Collection and Analysis
Participants completed the simulation experience in July 2013. 
Beginning the week of September 1, 2013, participants reported 
to the OR of a level I trauma center for their first month of 
clinical training. The OR had 22 operating suites and offered 
students experiences in neurosurgery, orthopedics, urology, 
gynecology, organ transplantation, reconstructive plastic surgery, 
head and neck surgery, and pediatrics. During 1:1 clinical 
training with a CRNA, students completed all the skills reviewed 
in the simulator course on every general-anesthetic case they 
participated in.
Documentation of all OR cases, regardless of SRNA 
participation, included recording of the in-room time and ART. 
The elapsed time between these 2 points indicated the amount 
of time it took the anesthesia providers to prepare the patient for 
surgery and was called the IRTART. Because these times exist in 
all OR records, we could compare the times for the September 
2013 SRNAs (intervention group) with the September 2012 
SRNAs (control group).

The retrospective analysis used information routinely recorded 
during all surgical cases within the institution’s EHR. The study 
team utilized the filter and report feature of the EHR to identify 
SRNA cases in September 2012 and September 2013. Records 
were filtered for date, SRNA name, general anesthesia procedures 
with an endotracheal tube, the in-room time, and the ART. The 
report function of the EHR produced a de-identified spreadsheet 
that listed the in-room time, ART, and the year the procedure 
was performed. IRTART in minutes was calculated from the 
recorded times. Data analysis consisted of a t-test with calculation 
of the mean and SD of the IRTART in minutes by a statistician.
RESULTS
All 10 participants in the intervention group completed the 
entire simulation program. Because of space limitations at the 
clinical site, 9 students reported to the OR at the level I trauma 
center and completed their first clinical rotation in September 
2013. The average age in the intervention group was 28 years 
(range, 25-31 years), and 7 participants (78%) were female. All 
of the participants in the intervention group had between 2.5 
and 7 years of nursing experience, predominantly in critical care 
environments. Demographic information for the control group 
was not reported because those SRNAs were not consented for 
the project.
Influential factors outside of the intervention were minimized by 
comparing the 2 SRNA classes at the onset of clinical training 
and in the same clinical site. All raw data points were obtained 
directly from the EHR. To maintain consistency in comparison, 
only general anesthesia cases with placement of an endotracheal 
tube were included in the retrospective chart review.  
Data collection yielded 127 records from September 2012 
(control group) and 116 records from September 2013 
(intervention group). There was no statistically significant 
difference in SRNA performance between the 2 groups. The 
mean IRTART for both groups was 20 minutes with an SD of 
10 minutes (p=0.482). Therefore, the IRTARTs of 68% of general 
anesthesia cases requiring an endotracheal tube involving SRNAs 
on their first clinical rotation were between 10 and 30 minutes 
(Table 1).

Table 1. Mean ART in Minutes by Group

Group No. of Records Mean ART, min SD SEM
SRNAs in 2012 127 20.04 10.09 0.90
SRNAs in 2013a 116 20.10 10.02 0.93
Abbreviations: ART, anesthesia ready time; HFS, high-fidelity simulation; SRNA, student registered nurse anesthetist.
aSRNAs in 2013 participated in the structured HFS program.



Anesthesia eJournal          www.anesthesiaejournal.com
Volume 6 - No. 2 2018 Page 10

DISCUSSION
The structured HFS scenarios were designed to increase SRNA 
basic anesthesia skills with the intent that students would require 
less step-by-step instruction during their first clinical rotation. 
The program aimed to provide participants with a systematic 
approach to induction of general anesthesia that could be 
augmented for specific procedures when necessary in the clinical 
environment. This was accomplished by using scenarios with 
5 different surgical procedures commonly encountered by new 
SRNAs. All 5 cases were nonemergent procedures for healthy 
patients and required the same anesthesia induction plan.
The SRNA control group did not receive structured HFS 
training. HFS was available to them but it was not mandated 
nor was it highly structured. For example, an afternoon skills 
lab included multiple stations and students self-selected the 
amount of time spent with each skill. HFS experiences varied, 
the simulations lacked objectives, and scenarios were dependent 
on the instructors. There was no standard amount of time the 
students spent in HFS and participation required self-motivation.
The project’s orientation process provided the intervention group 
with a standard of performance for the basic skills of equipment 
preparation, medication preparation, and the steps of anesthesia 
induction. While provider skill level is an element, many other 
things influence the amount of time required to safely anesthetize 
a patient, such as the surgical procedure; the patient’s size, age, 
and weight; and the need for an endotracheal tube and any 
additional intravenous, arterial, or central access or monitoring 
devices. All of these factors and tasks can impact the time 
anesthesia providers require to anesthetize a patient.14

No benchmarks exist within the literature or anesthesia 
professional organizations that state what an IRTART should be 
for a specific surgical procedure, diagnosis, or presenting patient 
condition.14 This simulation program does not account for every 
situation or factor that may impact an IRTART but promotes 
repetition of the portions of an anesthetic that are within the 
provider’s control, such as ensuring the presence and function 
of airway equipment. Therefore, the percentage of SRNAs with 
IRTART beyond 30 minutes may have experienced a delay 
related to something other than their basic skill level. This cannot 
be determined without additional data collection.
The medical center’s OR surgical schedule begins at 0730 
every weekday. For a procedure scheduled to start at 0730, 
the anesthesia provider is expected to bring the patient to the 
assigned OR suite by 0700, allowing approximately 30 minutes 

for the induction of anesthesia. The clinical performance of both 
groups of nurse anesthesia students, those with and without 
structured HFS before the onset of clinical training fell within 
the scheduled 30-minute time frame. While an impact of 
structured HFS was not seen with the comparison of IRTARTs, 
the data and statistical analysis highlight the positive performance 
of the majority of students within the institution’s established 
acceptable time frame for the anesthetic preparation of a patient.
The results of this project support 3 main conclusions. First, the 
current NAP curriculum prepares students to perform within this 
OR’s accepted time frame of efficiency at the start of their clinical 
training. This is highlighted by the very similar performance of 
both groups during the first month of their initial OR rotation. 
Second, the ART did not indicate an effect of structured HFS on 
the training of nurse anesthetists. It is possible that both groups 
performed equally because the HFS training did not have an 
impact or that ART is not sensitive to differences in individual 
performance. A larger sample size or a different measurement 
tool may better identify changes in student proficiency as a result 
of HFS. Third, the 2 years of consistent average ARTs between 
10 and 30 minutes can be used to partially counter the argument 
that novice nurse anesthesia students decrease OR efficiency. The 
presence of basic skills on arrival to the clinical setting allows 
preceptors to tailor training to other factors that impact timely 
performance.
In summary, NAP students have limited clinical training 
opportunities as a result of unconfirmed observations of 
anesthesia department administrators that SRNAs decrease OR 
efficiency because they require too much instruction. Guided by 
the Iowa Model, we inserted a 5-week, structured HFS program 
into the NAP curriculum before the students’ first clinical 
rotation. The program promoted basic anesthesia skill proficiency 
through the assimilation of previously taught and tested technical 
skills. Using the calculation of IRTART, we compared the clinical 
performance of SRNAs who underwent the structured HFS 
training with that of SRNAs with unstructured HFS training. 
In conclusion, the structured HFS did not impact the ART of 
new-to-practice SRNAs, although the IRTARTs of both groups 
were similar and within the institution’s operating norms. The 
information gained during the implementation of HFS and the 
data analysis period can be used to develop future avenues to 
improve current processes. Further studies identifying clinical 
indicators sensitive to HFS are necessary before cause and effect 
can be determined.

Acknowledgement: Special thanks to Angela Mund, DNP, CRNA, Dorothy Coley, MHS, CRNA, Raymon White, MSNA, CRNA, 
Andrea Iksic, MSNA, CNRA  and Patricia Aysse, MSN, RN for your effort and dedication to this project.  I would also like to sincerely 
thank Debra Shearer, EdD, MSN, FNP-BC, Bernard Gilligan, DNP, CRNA, Andy Battacharya, MHS and the DNP faculty at Villanova 
University for their guidance and support of this project.  



Anesthesia eJournal          www.anesthesiaejournal.com
Volume 6 - No. 2 2018 Page 11

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