- Email: [email protected]
Integration of in-hospital cardiac arrest contextual curriculum into a basic life support course: a randomized, controlled simulation study
Accepted Manuscript Title: Integration of In-Hospital Cardiac Arrest Contextual Curriculum into a Basic Life Support Course: A Randomized, Controlled Simulation Study Author: Elizabeth A. Hunt Jordan M. Duval-Arnould Nnenna O. Chime Kareen Jones Michael Rosen Merona Hollingsworth Deborah Aksamit Marida Twilley Cheryl Camacho Daniel P. Nogee Julianna Jung Kristen Nelson-McMillan Nicole Shilkofski Julianne S. Perretta PII: DOI: Reference:
S0300-9572(17)30114-4 http://dx.doi.org/doi:10.1016/j.resuscitation.2017.03.014 RESUS 7106
To appear in:
Resuscitation
Received date: Revised date: Accepted date:
16-10-2016 2-2-2017 10-3-2017
Please cite this article as: Hunt EA, Duval-Arnould JM, Chime NO, Jones K, Rosen M, Hollingsworth M, Aksamit D, Twilley M, Camacho C, Nogee DP, Jung J, Nelson-McMillan K, Shilkofski N, Perretta JS, Integration of In-Hospital Cardiac Arrest Contextual Curriculum into a Basic Life Support Course: A Randomized, Controlled Simulation Study, Resuscitation (2017), http://dx.doi.org/10.1016/j.resuscitation.2017.03.014 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Integration of In-Hospital Cardiac Arrest Contextual Curriculum into a Basic Life Support Course: A Randomized, Controlled Simulation Study
ip t
Elizabeth A. Hunt, MD, MPH, PhD1-5, Jordan M. Duval-Arnould, MPH, DrPH(c)1,2,4,5, Nnenna O. Chime, MBBS, MPH1,2, Kareen Jones, MD6,7, Michael Rosen, PhD1,2, Merona Hollingsworth, BS8, Deborah Aksamit, BSN, RN9, Marida Twilley, MSN, RNBC9, Cheryl Camacho, BS, NRP5, Daniel P. Nogee, MD1, Julianna Jung, MD1,5,10, Kristen Nelson-McMillan, MD1,2,3,5, Nicole Shilkofski, MD, MEd1,2,3,5, Julianne S. Perretta, MSEd, RRT-NPS, CHSE1,2,5 1
cr
Johns Hopkins University School of Medicine, Baltimore, Maryland, USA Department of Anesthesiology and Critical Care Medicine 3 Department of Pediatrics 4 Division of Health Sciences Informatics 5 Johns Hopkins Medicine Simulation Center, Baltimore, Maryland, USA 6 Stanford University School of Medicine, Palo Alto, California, USA 7 Department of Anesthesiology, Perioperative and Pain Medicine 8 Montefiore Einstein Center for Innovation in Simulation, Bronx, New York, USA 9 Johns Hopkins Hospital, Baltimore, Maryland, USA 10 Department of Emergency Medicine
M
an
us
2
d
Corresponding Author: Elizabeth A. Hunt Charlotte Bloomberg Children’s Center Division of Pediatric Anesthesiology and Critical Care Medicine 1800 Orleans Street Room 6321 Baltimore, MD 21287 Telephone: 410-614-0847 Email: [email protected] (can be published) No reprints will be ordered.
Ac ce pt e
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
Fax: 410-614-9878
Source of funding: None Direct Conflicts of Interest: None Financial Disclosures: Drs. Hunt and Shilkofski both have grant funding for unrelated projects from the Laerdal Foundation for Acute Care Medicine. Drs. Hunt and Mr. Duval-Arnould have granting funding for unrelated projects from the Hartwell Foundation. Dr. Hunt, Mr. Duval-Arnould and Ms. Perretta have received reimbursement for travel expenses and honoraria for speaking engagements from the Zoll Medical Corporation, with no restriction on the content and no prior review of slides. Dr. Hunt is a volunteer member of the AHA ECC Science Committee and the AHA Get With The Guidelines – Resuscitation Clinical Working Group. Key words:
cardiac arrest, cardiopulmonary resuscitation, simulation, teamwork, time sensitive, education Manuscript Word Count: 2,999 Abstract Word Count: 250 words This paper includes 3 tables and 2 figures and 6 online appendices.
1
Page 1 of 26
Objective: To compare resuscitation performance on simulated in-hospital cardiac
48
arrests after traditional American Heart Association (AHA) Healthcare Provider Basic
49
Life Support course (TradBLS) versus revised course including in-hospital skills
50
(HospBLS).
51
Design: Prospective, randomized, controlled curriculum evaluation.
52
Setting: Johns Hopkins Medicine Simulation Center.
53
Subjects: One hundred twenty-two first year medical students divided into fifty-nine
54
teams.
55
Intervention: HospBLS course of identical length, containing additional content
56
contextual to hospital environments, taught utilizing Rapid Cycle Deliberate Practice
57
(RCDP).
58
Measurements: The primary outcome measure during simulated cardiac arrest scenarios
59
was chest compression fraction (CCF) and secondary outcome measures included metrics
60
of high quality resuscitation.
61
Main Results:
62
Out-Of-Hospital Cardiac Arrest
63
HospBLS teams had larger CCF: (69%(65-74) vs 58%(53-62), p<0.001] and were faster
64
than TradBLS at initiating compressions: [median(IQR): 9 seconds(s)(7-12) vs. 22s(17.5-
65
30.5), p<0.001].
66
In-Hospital Cardiac Arrest
67
HospBLS teams had larger CCF: [73%(68-75%) vs. 50%(43-54%)), p<0.001) and were
68
faster to initiate compressions: [10s(6-11) vs. 36s(27-63), p<0.001]. All teams utilized the
69
hospital AED to defibrillate within 180 seconds per AHA guidelines, [HospBLS:
Ac ce pt e
d
M
an
us
cr
ip t
47
2
Page 2 of 26
70
122s(103-149) vs. TradBLS: 139s(116-172), p=0.09]. HospBLS teams performed more
71
hospital-specific maneuvers to optimize compressions, i.e. utilized: CPR button to flatten
72
bed: [7/30(23%) vs. 0/29(0%), p=0.006], backboard: [21/30(70%) vs. 5/29(17%),
73
p<0.001],
74
[28/30(93%) vs. 10/29(34%), p<0.001], connected oxygen appropriately: [26/30(87%) vs.
75
1/29(3%), p<0.001] and used oral airway and/or 2-person bagging when traditional bag-
76
mask-ventilation unsuccessful: [30/30(100%) vs. 0/29(0%), p<0.001].
77
Conclusion: A hospital focused BLS course utilizing RCDP was associated with
78
improved performance on hospital-specific quality measures compared to the traditional
79
AHA course.
[28/30(93%) vs. 8/29(28%), p<0.001], lowered bedrails:
an
us
cr
ip t
stepstool:
83 84 85 86 87 88 89
d
82
Ac ce pt e
81
M
80
90 91 92
3
Page 3 of 26
93 Introduction:
95
Each year, approximately 200,000 patients in the United States have an in-hospital
96
cardiac arrest (IHCA) with attempted resuscitation.1 Girotra reported increase in survival
97
to discharge from IHCA between 2000 and 2009 for both adults (13.7% to 22.3%) and
98
children (14.3% to 43.4%), with no increase in neurologic disability.2.3 The increasing
99
neurologically intact survival rates are encouraging. However, further examination
100
reveals significant variation across hospitals in both survival rates and magnitude of
101
improvement over time.4,5 Given these reports take into account patient demographics
102
and case mix severity, this suggests hospital-level variation contributes to variability in
103
patient survival and represents an opportunity to further improve patient outcomes.
M
an
us
cr
ip t
94
104
Ornato et al analyzed the American Heart Association’s (AHA) Get-With-The-
106
Guidelines-Resuscitation
107
resuscitation system errors and survival to discharge.6 For example, GWTG-R defines an
108
error for any IHCA with an initial shockable rhythm not defibrillated within 2 minutes, as
109
this interval is associated with survival outcomes,6-9 and also varies between hospitals.10
110
Other rescuer performance variables associated with cardiac arrest survival include: time
111
to initiation of compressions11, pre-, peri- and post-shock pauses,12-14 chest compression
112
fraction,15 rate16,17 and depth.17
d
105
Ac ce pt e
(GWTG-R) IHCA registry, reporting an association between
113 114
Historically, AHA Healthcare Provider BLS courses have not taught learners how to
115
navigate hospital-specific challenges. For example, a patient who collapses on a hard, flat
4
Page 4 of 26
sidewalk requires different strategies than an IHCA in a hospital bed with elevated head,
117
bedrails, lying on a soft mattress that deflects downward with compressions. The
118
traditional curriculum requires rescuers to perform CPR on the floor with no inclusion of
119
other possible environments. The 2015 AHA guidelines now calls for contextualization
120
of training scenarios to be relevant to the “learner’s real world setting”.18 Altering the
121
manner in which we teach BLS to match the manner in which it most likely to be used by
122
our learners may build resiliency and improve resuscitation performance. However, we
123
are unaware of literature examining the impact of increasing the level of environmental
124
realism during BLS curricula on performance during IHCA.
an
us
cr
ip t
116
125
We hypothesized students completing a traditional AHA Healthcare Provider BLS
127
course would perform well on a simulated OOHCA, but less well when confronted with a
128
typical IHCA. Our objectives were to: 1) measure whether learners participating in
129
existing AHA Healthcare Provider (TradBLS) courses met key resuscitation outcome
130
measures in an IHCA scenario, 2) evaluate learning outcomes of the TradBLS course
131
compared to a revised course (HospBLS) amended to include contextually relevant
132
curriculum specific to the hospital environment and 3) assess for unintended
133
consequences of added hospital content, i.e. worse performance on OOHCA scenarios.
d
Ac ce pt e
134
M
126
135
Materials and Methods:
136
Study Design
137
A prospective, randomized, controlled evaluation of an educational intervention was
138
conducted. The population was first-year medical students at The Johns Hopkins
5
Page 5 of 26
University School of Medicine (JHUSOM) who enrolled into one of six sessions most
140
convenient for their schedule. Each session had 21 available slots. All were conducted
141
over a three-month period. After enrollment was complete, each session was randomized
142
to control or intervention. Block randomization in a single block of six, with an opaque
143
envelope containing study arm assignments in ratio of 1:1, was utilized to ensure equal
144
allocation of subjects with three TradBLS and three HospBLS courses. Participation was
145
mandatory as this was a quality assurance exercise to determine which course would
146
continue in the JHUSOM curriculum in subsequent years. This project was approved by
147
the JHUSOM Institutional Review Board as an Educational Quality Assurance
148
evaluation.
an
us
cr
ip t
139
M
149 Educational Intervention
151
The curricula being compared were both video-guided and instructor-led, i.e. TradBLS
152
versus a course of equal length, identical OOHCA content, plus additional objectives and
153
curriculum focused on managing IHCA (“HospBLS”). The latter included goals related
154
to effective bag-mask-ventilation, use of in-hospital equipment and crisis resource
155
management. Both courses utilized the 2010 AHA instructor materials and were
156
completed per AHA guidelines.19 After demonstrating to Senior AHA Leadership how
157
the revised curriculum met the Healthcare Provider BLS objectives, we were permitted to
158
distribute AHA certification cards for our experimental course.
Ac ce pt e
d
150
159 160
The additional IHCA-specific objectives were taught using the Rapid Cycle Deliberate
161
Practice (RCDP) educational approach.20 Existing AHA BLS faculty were recruited as
6
Page 6 of 26
instructors, a subset learned the new objectives and the RCDP technique for the high-
163
fidelity simulation IHCA stations. Prior to the study sessions, this group taught the
164
HospBLS course in an apprentice model with ongoing feedback until they achieved
165
mastery as faculty of this course. All six courses had a lead instructor who developed the
166
intervention content and a co-instructor, who together assured completion of key learning
167
objectives and appropriate time management. See Appendix A, B, C for an overview of
168
the HospBLS curriculum, list of TradBLS learning objectives and highlight of additional
169
learning objectives in the HospBLS course, and a HospBLS course timetable.
us
cr
ip t
162
an
170 Assessment Tools and Outcome Measures
172
Upon arrival to the Johns Hopkins Medicine Simulation Center, each student completed a
173
pre-course demographic survey. After completion of the course, students completed the
174
standard AHA BLS course skills testing, multiple choice question (MCQ) post-course
175
exam and course evaluation tool. Study assessments included:
177 178 179 180 181 182
d
Ac ce pt e
176
M
171
1) Additional MCQs to Assess IHCA knowledge: Five MCQs were created by course faculty, assessed for readability and face
validity by a group of senior medical students and assessed for construct validity
by a resuscitation scientist and a group of physicians with specialized training in critical care and emergency medicine, all of whom are involved in resuscitation research and education.
183 184
2) High-Fidelity Simulation Scenarios:
7
Page 7 of 26
185
Students participated as teams of two or three in two 5-minute summative
186
assessments. (Appendix D)
187
OOHCA scenario:
188
A woman (Resusci Anne
189
baseball park, and was found unresponsive and pulseless by a study confederate
190
who asked the learners for help.
191
IHCA scenario:
192
A man (SimMan
193
a hospital gown, head on a pillow, head of bed up, side rails up) became gray and
194
unresponsive, thus two confederate nurses call for help.
us
cr
ip t
Simulator) collapsed on the bathroom floor at a
an
3G) in a hospital bed, in a simulated hospital room (manikin in
M
195
The primary outcome measure was the chest compression fraction (CCF) based on
197
observations that students confronted with a simulated IHCA struggle with navigating the
198
environment, causing both delays and frequent pauses in chest compressions. Secondary
199
outcome measures included time elapsed from call for help and entry of participants into
200
room to: 1) initiation of chest compressions and 2) first defibrillation, as well as
201
knowledge and performance of IHCA-specific CPR quality process measures, i.e. use of
202
stepstool, backboard, “CPR lever” to automatically flatten hospital bed, maneuvers in
203
response to being unable to effectively ventilate with one-person bagging (i.e. either two-
204
person BMV and/or placement of oral airway), oxygen tubing connected to oxygen flow
205
meter, and proper flow rates for oxygen.
Ac ce pt e
d
196
206 207
Effect Size Calculation
8
Page 8 of 26
A convenience sample of 122 first-year medical students divided into teams of two
209
projected 30 teams per study arm. Pilot data from previous TradBLS courses had a
210
mean(±standard deviation) CCF of 0.50(±0.08). Assuming an alpha of 0.05, beta of 0.2,
211
our sample size gave us 80% power to detect a clinically significant difference in the
212
CCF as small as .06.
ip t
208
cr
213 Data Abstraction
215
Two video angles were captured for all scenarios to facilitate review. Two different sets
216
of reviewers abstracted data from the video recordings of the IHCA and OOHCA
217
summative assessments. The reviewers used custom-built software designed to facilitate
218
accurate and efficient data collection. Data captured were automatically exported to
219
comma-separated values (CSV) file, combined and transferred to Stata/IC 13 (StataCorp
220
LP, College Station, TX) for statistical analysis, eliminating risk of transcription errors.
221
Reviewers were blinded to study group allocation of the participants. For each set of
222
videos, 20% were scored by both reviewers independently in order to calculate inter-rater
223
reliability.
an
M
d
Ac ce pt e
224
us
214
225
Data Analysis
226
Proportions were calculated for categorical variables and compared using the chi square
227
statistic. Means and standard deviations were calculated for continuous variables with t-
228
test comparison of means reported. If data were not normally distributed, then medians
229
and interquartile ranges were reported and groups were compared utilizing the Wilcoxon
230
Rank Sum test. A p-value < 0.05 was considered significant. For inter-rater reliability,
9
Page 9 of 26
correlation coefficients were calculated on the 20% overlap samples for all primary
232
outcome measures. The study methods adhered to the CONSORT 2010 and simulation-
233
based guidelines.21,22 (Appendix E, F)
234
Results:
235
One hundred twenty-two students were enrolled and divided into fifty-nine teams. All
236
students completed each assessment, either as an individual or part of a team. The two
237
groups were similar at baseline in terms of training and experience except more TradBLS
238
students were BLS instructors whereas more of the HospBLS students had assisted with
239
real-life CPR in the past. (Table 1) However, there were too few of these students for us
240
to control for these differences in our analysis. All students passed the AHA MCQ test
241
and skills assessment necessary to receive their BLS cards – the results of this evaluation
242
are not included as part of the results.
d
243
M
an
us
cr
ip t
231
Knowledge
245
The HospBLS group was significantly more likely to identify a set of a priori identified
246
maneuvers to improve quality of in-hospital CPR. The HospBLS group was also more
247
likely to identify ideal oxygen flow rates and maneuvers to attempt when unable to
248
effectively ventilate. (Table 2)
249
Ac ce pt e
244
250
Simulation Skills Performance
251
Overview of TradBLS Team Performance
252
All TradBLS students passed the AHA skills stations and met the overarching objectives,
253
i.e. started chest compressions and defibrillated the manikin in both the OOHCA and
10
Page 10 of 26
IHCA high-fidelity summative assessments. However, in the IHCA assessment 25% of
255
TradBLS teams took more than a minute to start compressions and few teams performed
256
any maneuvers to optimize quality of compressions for a patient in a hospital bed.
257
Regarding airway management, only one team connected oxygen tubing to the flow
258
meter and chose an appropriate flow rate. None of the TradBLS teams independently
259
noticed the manikin’s chest was not rising in response to bagging, and once pointed out to
260
them by a confederate, no teams performed any maneuvers beyond repositioning the
261
mask in an attempt to address the insufficient ventilation. (Tables 3-5)
263
Detailed Comparison of TradBLS and HospBLS Simulation Performance
264
Out-Of-Hospital Cardiac Arrest
265
All teams started compressions and successfully operated a public access AED. However,
266
HospBLS teams had larger CCF: [69% (65-74) vs 58% (53-62), p<0.001], were faster at
267
initiating compressions: [median: 9 seconds (IQR:7-12) vs. 22 (18-31), p<0.001], and had
268
shorter pre-shock pauses. (Table 5)
269
In-Hospital Cardiac Arrest
270
HospBLS teams had larger CCF and were quicker to initiate compressions. (Figures 1
271
and 2) In addition, HospBLS teams were more likely to perform IHCA-specific
272
maneuvers to optimize compressions: utilize CPR button to quickly flatten bed, lower
273
side rails, and utilize backboard and stepstool. All teams utilized the AED to defibrillate
274
within 180 seconds per AHA guidelines, [HospBLS: 122 sec (103-149) vs. TradBLS: 139
275
(116 vs. 172), p=0.09]. HospBLS teams were more likely to optimize airway
276
management: connect oxygen tubing and use appropriate flow rate [87% (26/30) vs. 3%
Ac ce pt e
d
M
an
262
us
cr
ip t
254
11
Page 11 of 26
(1/29), p<0.001]. Most remarkably, none of the TradBLS teams used any maneuvers
278
beyond repositioning the mask (oral airway and/or 2-person approach to assist with
279
bagging) when traditional BMV was unsuccessful, whereas every HospBLS team did so:
280
[100% (30/30) vs. 0% (0/29), p<0.001]. (Tables 3 and 4)
ip t
277
281 Inter-rater reliability
283
Pairwise inter-rater assessments of initiation of compression time (0.99), defibrillation
284
time (0.99) and compression fraction (0.90) were strongly correlated, p <0.05.
us
cr
282
an
285 Discussion:
287
Our data highlight that students who completed a TradBLS course based on the 2010
288
AHA guidelines met existing AHA learning objectives.19 However, other than
289
rudimentary BMV skills they did not appear to acquire any BLS skills that differentiate
290
the lay provider from the healthcare provider and were not prepared to manage issues
291
common to IHCA, such as resuscitating patients in a bed rather than on the floor. Both
292
the training and skill assessments of traditional courses were conducted in a fashion that
293
is incongruent with the manner in which CPR is actually performed during IHCAs.
294
Though all content from the 2010 AHA curricula are essential, our HospBLS learning
295
objectives addressed additional essential skills for those working in the hospital
296
environment. Our data highlight that managing IHCAs is not intuitive and thus requires
297
direct instruction. Our HospBLS learners developed a shared mental model (i.e.
298
compatible understanding amongst team members of roles, tasks, and the situation) of an
299
IHCA “high performing team”, i.e. how a larger team of 3 to 6 people (as is frequently
Ac ce pt e
d
M
286
12
Page 12 of 26
the situation in a hospital) will quickly assemble themselves into a well-oiled machine to
301
manage the first few minutes of an IHCA.23 These findings have three central
302
implications for future Healthcare Provider BLS training related to content as well as
303
delivery method.
ip t
300
304
First, in addition to foundational resuscitation skills targeted in traditional BLS programs,
306
a broader range of contextual skills are trainable, and may impact critical resuscitation
307
outcomes. These skills include recognizing and managing environmental factors unique
308
to the hospital setting (e.g. use of available hospital equipment, adapting chest
309
compression technique to the design of a hospital bed, etc…).24,25 Specifics of these
310
competencies may vary by hospital, as factors such as physical layout, equipment
311
models, and procedural considerations can impact CPR performance. However, a general
312
framework of the types of factors to address in training could be developed. This
313
framework, along with appropriate curriculum design guidance, would allow local
314
trainers to customize contextual aspects of BLS training while maintaining alignment
315
with a national curriculum. In terms of operationalizing this content beyond medical
316
students, our institution has one version of this contextual curriculum for medical
317
students who have not previously worked in the hospital setting, another for new nurses
318
on orientation, another for Security Officers, and another for ICU staff. The idea is that
319
the curriculum has three levels, i.e. 1) core AHA BLS content on psychomotor skills of
320
chest compressions, BMV and defibrillation, 2) core content which is contextually
321
relevant to performing high quality BLS within the hospital setting and 3) extra content
322
contextually relevant to that population’s environment and role within that environment.
Ac ce pt e
d
M
an
us
cr
305
13
Page 13 of 26
323
It is exciting to note the 2015 AHA guidelines section on education now includes
324
contextualization as a “core educational concept”.18
325 Second, practicing CPR under a broader range of conditions may be beneficial in its own
327
right. The variability of practice effect is a phenomenon wherein acquisition of skill and
328
transfer of training are improved when an individual or team practices those skills under a
329
wider array of conditions. This effect is well-documented for simple procedural26 and
330
problem solving skills,27 as well as more complex team performance issues.28 Traditional
331
BLS courses are highly standardized, which is desirable to ensure every learner
332
completing the course has reached the same targeted level of proficiency. However, when
333
the traditional BLS course is the only version available for both new and advanced
334
learners in re-certification, this limits the resilience of the learner in the face of variability
335
in practice, and effectively restricts learners’ ability to advance beyond fundamentals.
336
There appears to be value in an ‘advanced’ BLS course, one that addresses the same core
337
clinical skills as the ‘basic’ course, but in more varied and complex situations. Taken
338
together, these two issues of contextual competencies and practice variability provide
339
direction for the maturation of BLS curricula. For the lay provider, BLS is basic.
340
Learners meet minimum thresholds of performance and that is the end of development.
341
Our study’s findings suggest it is worth considering BLS from a continuous professional
342
development perspective, where the fundamentals of BLS are elaborated upon in
343
different contexts. Advanced learners may gain more value from practicing skills in
344
different types of situations, tailored to the needs of a variety of learner groups versus the
345
current “one-size-fits-all” approach.
Ac ce pt e
d
M
an
us
cr
ip t
326
14
Page 14 of 26
346 Third, it is essential to stress the time-critical and high-stakes nature of cardiac arrest
348
during training. Small delays can adversely impact patients. Therefore, it is not
349
appropriate to leave the contextual skills for ‘on the job training,’ per current practice.
350
Teams that operate with a shared mental model perform better.29,30 Team training31 and
351
team planning32 enable teams to reach high levels of shared mental models and
352
performance. One promising path forward for BLS involves identifying those aspects of
353
performance that can be optimized and (i.e. ‘one best way’ clearly defined) standardized
354
across all settings, as well as those that should be defined and standardized locally.
355
Teams can then engage in repeated training to build shared mental models and efficiency.
356
Sullivan described the use of RCDP to perform 15-minute in situ simulation sessions to
357
drill ward nurses on the first few minutes of a ward IHCA.33 We suspect the key element
358
associated with the success of the HospBLS course is not necessarily the length of the
359
course, but explicit inclusion of skills specific to IHCA with opportunities to try again
360
(i.e. RCDP) until fundamental skills are mastered. Mastery learning techniques are
361
increasingly associated with improved educational outcomes, with specific reports in
362
relation to resuscitation topics.33-36
cr
us
an
M
d
Ac ce pt e
363
ip t
347
364
This study has several important limitations. First, while the HospBLS curriculum was
365
taught within the same time previously allocated for standard BLS for our students, this
366
three-hour course is longer than ultra-brief courses described in the literature.37 Lee
367
recently demonstrated while BLS skills can be learned in shorter courses, longer courses
368
were associated with improved performance.38 Second, the HospBLS course can be more
15
Page 15 of 26
resource-intensive than traditional BLS courses, secondary to the high-fidelity simulators,
370
simulated clinical environment and increased faculty to student ratios. However, we now
371
teach the course with traditional faculty-to-student ratios for AHA courses of 1:6 and
372
lower-fidelity simulators that still provide realistic practice opportunities. Requiring
373
students to navigate the highly realistic simulated hospital environment and equipment
374
may be the most important aspects of a contextual IHCA curriculum. Finally, we did not
375
obtain reliable data on depth and rate of compressions and thus cannot comment on the
376
impact of the adapted curriculum on that aspect of quality CPR, nor can we comment on
377
translation of skills into the actual patient environment.
an
us
cr
ip t
369
378 Conclusions:
380
Medical students participating in a traditional BLS course did not perform well in a
381
simulated IHCA. Our data support use of RCDP to teach BLS curricula that is
382
contextually relevant to both the in and out-of-hospital setting as components of the
383
standard AHA Healthcare Provider BLS course.
d
Ac ce pt e
384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399
M
379
16
Page 16 of 26
ip t cr
References:
us
1. Merchant RM, Yang L, Becker LB, et al; American Heart Association Get With The Guidelines-Resuscitation Investigators. Incidence of treated cardiac arrest in hospitalized patients in the United States. Crit Care Med. 2011 Nov;39(11):2401-6.
M
an
2. Girotra S, Nallamothu BK, Spertus JA, Li Y, Krumholz HM, Chan PS; American Heart Association Get with the Guidelines–Resuscitation Investigators. Trends in survival after in-hospital cardiac arrest. N Engl J Med. 2012 Nov 15;367(20):191220.
d
3. Girotra S, Spertus JA, Li Y, Berg RA, Nadkarni VM, Chan PS; American Heart Association Get With the Guidelines–Resuscitation Investigators. Survival trends in pediatric in-hospital cardiac arrests: an analysis from Get With the GuidelinesResuscitation. Circ Cardiovasc Qual Outcomes. 2013 Jan 1;6(1):42-9. 4. Merchant RM, Berg RA, Yang L, Becker LB, Groeneveld PW, Chan PS; American Heart Association's Get With the Guidelines-Resuscitation Investigators. Hospital variation in survival after in-hospital cardiac arrest. J Am Heart Assoc. 2014 Jan 31;3(1):e000400.
Ac ce pt e
400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443
5. Girotra S, Cram P, Spertus JA, et al; American Heart Association's Get With the Guidelines®‐Resuscitation Investigators. Hospital variation in survival trends for inhospital cardiac arrest. J Am Heart Assoc. 2014 Jun 10;3(3):e000871. 6. Ornato JP, Peberdy MA, Reid RD, Feeser VR, Dhindsa HS; NRCPR Investigators. Impact of resuscitation system errors on survival from in-hospital cardiac arrest. Resuscitation. 2012 Jan;83(1):63-9. 7. Hazinski MF, Shuster M, Donnino MW, et al. Highlights of the 2015 American Heart Association Guidelines Update for CPR and ECC. Available at: https://eccguidelines.heart.org/wp-content/uploads/2015/10/2015-AHA-GuidelinesHighlights-English.pdf. Accessed September 21, 2016.
17
Page 17 of 26
8. Herlitz J, Aune S, Bång A, et al. Very high survival among patients defibrillated at an early stage after in-hospital ventricular fibrillation on wards with and without monitoring facilities. Resuscitation. 2005 Aug;66(2):159-66.
ip t
9. Chan PS, Krumholz HM, Nichol G, Nallamothu BK; American Heart Association National Registry of Cardiopulmonary Resuscitation Investigators. Delayed time to defibrillation after in-hospital cardiac arrest. N Engl J Med. 2008 Jan 3;358(1):9-17.
cr
10. Chan PS, Nichol G, Krumholz HM, Spertus JA, Nallamothu BK; American Heart Association National Registry of Cardiopulmonary Resuscitation (NRCPR) Investigators. Hospital variation in time to defibrillation after in-hospital cardiac arrest. Arch Intern Med. 2009 Jul 27;169(14):1265-73.
us
11. Herlitz J, Bang A, Alsen B, Aune S. Characteristics and outcome among patients suffering from in hospital cardiac arrest in relation to the interval between collapse and start of CPR. Resuscitation.2002;53:21– 27.
M
an
12. Edelson DP, Abella BS, Kramer-Johansen J, et al. Effects of compression depth and pre-shock pauses predict defibrillation failure during cardiac arrest. Resuscitation. 2006 Nov;71(2):137-45.
d
13. Sell RE, Sarno R, Lawrence B, et al. Minimizing pre- and post-defibrillation pauses increases the likelihood of return of spontaneous circulation (ROSC). Resuscitation. 2010 Jul;81(7):822-5. 14. Cheskes S, Schmicker RH, Verbeek PR, et al; Resuscitation Outcomes Consortium (ROC) investigators.The impact of peri-shock pause on survival from out-of-hospital shockable cardiac arrest during the Resuscitation Outcomes Consortium PRIMED trial. Resuscitation. 2014 Mar;85(3):336-42.
Ac ce pt e
444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489
15. Christenson J, Andrusiek D, Everson-Stewart S, et al; Resuscitation Outcomes Consortium Investigators. Chest compression fraction determines survival in patients with out-of-hospital ventricular fibrillation. Circulation. 2009 Sep 29;120(13):1241-7. 16. Idris AH, Guffey D, Pepe PE, et al; Resuscitation Outcomes Consortium Investigators. Chest compression rates and survival following out-of-hospital cardiac arrest. Critical Care Med. 2015 Apr;43(4):840-8. 17. Talikowska M, Tohira H, Finn J. Cardiopulmonary resuscitation quality and patient survival outcome in cardiac arrest: A systematic review and meta-analysis. Resuscitation. 2015 Nov;96:66-77. 18. Bhanji F, Donoghue AJ, Wolff MS, Flores GE, Halamek LP, Berman JM, Sinz EH, Cheng A. Part 14: Education: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation. 2015 Nov;132(18 Suppl 2):S561-73.
18
Page 18 of 26
19. Berg RA, Hemphill R, Abella BS, Aufderheide TP, Cave DM, Hazinski MF, Lerner EB, Rea TD, Sayre MR, Swor RA. Part 5: adult basic life support: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation. 2010 Nov;122(18 Suppl 3):S685-705.
ip t
20. Hunt EA, Duval-Arnould JM, Nelson-McMillan KL, et al. Pediatric resident resuscitation skills improve after "rapid cycle deliberate practice" training. Resuscitation. 2014 Jul;85(7):945-51.
cr
21. www.consort-statement.org, accessed 10/14/2016.
us
22. Cheng A, Kessler D, Mackinnon R, et al. Reporting Guidelines for Health Care Simulation Research: Extensions to the CONSORT and STROBE Statements. Simul Healthc. 2016 Aug;11(4):238-48.
an
23. Hunt EA, Walker AR, Shaffner DH, Miller MR, Pronovost PJ. Simulation of inhospital pediatric medical emergencies and cardiopulmonary arrests: highlighting the importance of the first 5 minutes. Pediatrics. 2008 Jan;121(1):e34-43.
M
24. Lee DH, Kim CW, Kim SE, Lee SJ. Use of step stool during resuscitation improved the quality of chest compression in simulated resuscitation. Emerg Med Australas. 2012 Aug;24(4):369-73.
d
25. Oh J, Chee Y, Lim T, Cho Y, Kim IY. Chest compression with kneeling posture in hospital cardiopulmonary resuscitation: A randomised crossover simulation study. Emerg Med Australas. 2014 Dec;26(6):585-90.
Ac ce pt e
490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535
26. Holladay CL, Quinones MA. Practice variability and transfer of training: the role of self-efficacy generality. Journal of Applied Psychology. 2003 Dec;88(6):1094. 27. de Croock MB, van Merriënboer JJ, Paas FG. High versus low contextual interference in simulation-based training of troubleshooting skills: Effects on transfer performance and invested mental effort. Computers in Human Behavior. 1998 May 25;14(2):249-67. 28. Gorman JC, Cooke NJ, Amazeen PG. Training adaptive teams. Human Factors: The Journal of the Human Factors and Ergonomics Society. 2010 Jul 23. 29. Mathieu JE, Heffner TS, Goodwin GF, Salas E, Cannon-Bowers JA. The influence of shared mental models on team process and performance. Journal of Applied Psychology. 2000 Apr;85(2):273. 30. DeChurch LA, Mesmer-Magnus JR. The cognitive underpinnings of effective teamwork: a meta-analysis. Journal of Applied Psychology. 2010 Jan;95(1):32.
19
Page 19 of 26
31. Salas E, Diaz Granados D, Klein C, et al. Does team training improve team performance? A meta-analysis. Human Factors: The Journal of the Human Factors and Ergonomics Society. 2008 Dec 1;50(6):903-33.
ip t
32. Stout RJ, Cannon-Bowers JA, Salas E, Milanovich DM. Planning, shared mental models, and coordinated performance: An empirical link is established. Human Factors: The Journal of the Human Factors and Ergonomics Society. 1999 Mar 1;41(1):61-71.
us
cr
33. Sullivan NJ, Duval-Arnould J, Twilley M, Smith SP, Aksamit D, Boone-Guercio P, Jeffries PR, Hunt EA. Simulation exercise to improve retention of cardiopulmonary resuscitation priorities for in-hospital cardiac arrests: A randomized controlled trial. Resuscitation. 2015 Jan;86:6-13. 34. McGaghie WC. Mastery learning: it is time for medical education to join the 21st century. Academic Medicine. 2015 Nov;90(11):1438-41.
M
an
35. Eppich WJ, Hunt EA, Duval-Arnould JM, Siddall VJ, Cheng A. Structuring feedback and debriefing to achieve mastery learning goals. Academic Medicine. 2015 Nov;90(11):1501-8.
d
36. Barsuk JH, Cohen ER, Wayne DB, Siddall VJ, McGaghie WC. Developing a Simulation-Based Mastery Learning Curriculum: Lessons From 11 Years of Advanced Cardiac Life Support. Simulation in Healthcare. 2016 Feb;11(1):52-9. 37. Panchal AR, Meziab O, Stolz U, et al. The impact of ultrabrief chest compressiononly CPR video training on responsiveness, compression rate, and hands-off time interval among bystanders in a shopping mall. Resuscitation. 2014 Sep;85(9):128790.
Ac ce pt e
536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569
38. Lee JH, Cho Y, Kang KH, Cho GC, Song KJ, Lee CH. The Effect of the Duration of Basic Life Support Training on the Learners' Cardiopulmonary and Automated External Defibrillator Skills. Biomed Res Int. 2016;2016:2420568. Epub 2016 Jul 27.
20
Page 20 of 26
Table 1
Table 1. Demographics of Individual Participants HospBLS
(Control)
(Intervention)
(n=60)
(n=62)
% (n)
% (n)
48%(29)
Previous ECC certification BLS
52%(31)
48%(30)
us
Male
cr
Baseline Characteristics
ip t
TradBLS
53%(33)
2% (1)
ACLS
2% (1)
3% (2)
97%(58)
95%(59)
8% (5)
0% (0)
3% (2)
15% (9)
0% (0)
2% (1)
EMT
0% (0)
5% (3)
Respiratory Therapist
2% (1)
0% (0)
Life Guard
0% (0)
5% (3)
Other
2% (1)
3% (2)
an
PALS
M
Neither PALS or ACLS
Real-life CPR role
Ac ce p
Nurse
te
Assisted with real-life CPR
d
BLS Instructor
0% (0)
Page 21 of 26
Table 2
Table 2. Knowledge Assessment of Individual Participants
(Control)
(Intervention)
(n=60)
(n=62)
% (n)
%(n)
P Value
ip t
Compressions
HospBLS
cr
Assessment Topic
TradBLS
Correct identification of methods to
us
improve quality of chest compressions*
27%(16)
87%(54)
<0.001
Identified at least 5 methods
58%(35)
100%(62)
<0.001
18%(11)
77%(48)
<0.001
17%(10)
90%(56)
<0.001
92%(55)
98%(61)
0.09
Respirations
M
Correct identification of 2-person BMV to
improve ventilation when chest rise is not
d
visible^
Ac ce p
Defibrillation
te
Correct identification of 15L/min O2 flow during use with BMV
an
Identified all 6 methods
Correct identification of AED as single first piece of equipment to request
*In MCQ assessment, the following six choices were considered methods that can be used to improve quality of chest compressions: 1) Lowering the head of the bed, 2) Lowering the bed, 3) Compressor standing on a step stool, 4) Positioning compressor’s shoulders above the patient, 5) Locking compressor’s elbows, 6) Putting patient on a hard surface, i.e. back board ^ BMV = Bag-Mask-Ventilation
Page 22 of 26
Table 3
Table 3. Team Performance in Simulated Cardiopulmonary Arrests Simulation Scenario
TradBLS
HospBLS
Outcome Measures
(Control)
(Intervention)
(n=29)*
(n=30)*
22 (18-31)
9 (7-12)
<0.001
0% (0)
67%(20)
<0.001
0.58 (0.53-0.62)
0.69 (0.65-0.74)
<0.001
7% (2)
63%(19)
<0.001
15 (14-21)
0.05
36 (27-63)
10 (6-11)
<0.001
0% (0)
63%(19)
<0.001
0.5 (0.43-0.54)
0.73 (0.68-0.75)
<0.001
3% (1)
43%(13)
<0.001
0% (0)
23% (7)
0.006
Lowered bedrails, %(n)
34%(10)
93%(28)
<0.001
Utilized backboard, %(n)
17% (5)
70%(21)
<0.001
Utilized stepstool, %(n)
28% (8)
93%(28)
<0.001
3% (1)
87%(26)
<0.001
Chest Compression Fraction+, median (IQR)
an
Verbalized Cycle Number, %(n)
Out-of-Hospital: Defibrillation
In-Hospital: Chest Compressions
te
Compressions by 10s, %(n)
d
Time to starting, median (IQR), s
Chest Compression Fraction+,
Ac ce p
median (IQR)
22 (15-27)
M
Pre-shock Pause, median (IQR), s
Verbalized Cycle Number, %(n)
Utilized CPR button to flatten bed, %(n)
cr
Compressions by 10s, %(n)
us
Time to starting, median (IQR), s
ip t
Out-of-Hospital: Chest Compressions
P Value
In-Hospital: Airway Optimization Attached O2 with appropriate flow, %(n)
Page 23 of 26
Used oral airway and/or 2-person
0% (0)
100%(30)
<0.001
139 (117-172)
122 (103-149)
0.09
79%(23)
87%(26)
0.45
18 (12-25)
13 (6-11)
0.07
bagging, %(n)
Time to defib, median (IQR), s Defibrillation by 180s, %(n) Pre-shock Pause, median (IQR), s
ip t
In-Hospital: Defibrillation
cr
*Unit of analysis is at the 2-person team level; Wilcoxon rank sum for median, Chi square for proportions
us
+Chest Compression Fraction is defined as the amount of time during which the simulated patient was
Ac ce p
te
d
M
an
pulseless and receiving chest compressions.
Page 24 of 26
Figure 1
pt ce
Ac
63
36
27
11 6
9.5 Page 25 of 26
0
Compression Start Time (seconds) 60 80 40 20
100
ed
IHCA Time to Initiation of Chest Compressions TradBLS vs. HospBLS (median, IQR) p<0.001
TradBLS
HospBLS
54%
ce
pt
ed
IHCA Chest Compression Fraction TradBLS vs. HospBLS (median, IQR) p<0.001
Ac
0 10 20 30 40 50 60 70 80 90 100
Chest Compression Fraction (%)
Figure 2
75% 68%
73%
50%
43%
Page 26 of 26
TradBLS
HospBLS
S0300-9572(17)30114-4 http://dx.doi.org/doi:10.1016/j.resuscitation.2017.03.014 RESUS 7106
To appear in:
Resuscitation
Received date: Revised date: Accepted date:
16-10-2016 2-2-2017 10-3-2017
Please cite this article as: Hunt EA, Duval-Arnould JM, Chime NO, Jones K, Rosen M, Hollingsworth M, Aksamit D, Twilley M, Camacho C, Nogee DP, Jung J, Nelson-McMillan K, Shilkofski N, Perretta JS, Integration of In-Hospital Cardiac Arrest Contextual Curriculum into a Basic Life Support Course: A Randomized, Controlled Simulation Study, Resuscitation (2017), http://dx.doi.org/10.1016/j.resuscitation.2017.03.014 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Integration of In-Hospital Cardiac Arrest Contextual Curriculum into a Basic Life Support Course: A Randomized, Controlled Simulation Study
ip t
Elizabeth A. Hunt, MD, MPH, PhD1-5, Jordan M. Duval-Arnould, MPH, DrPH(c)1,2,4,5, Nnenna O. Chime, MBBS, MPH1,2, Kareen Jones, MD6,7, Michael Rosen, PhD1,2, Merona Hollingsworth, BS8, Deborah Aksamit, BSN, RN9, Marida Twilley, MSN, RNBC9, Cheryl Camacho, BS, NRP5, Daniel P. Nogee, MD1, Julianna Jung, MD1,5,10, Kristen Nelson-McMillan, MD1,2,3,5, Nicole Shilkofski, MD, MEd1,2,3,5, Julianne S. Perretta, MSEd, RRT-NPS, CHSE1,2,5 1
cr
Johns Hopkins University School of Medicine, Baltimore, Maryland, USA Department of Anesthesiology and Critical Care Medicine 3 Department of Pediatrics 4 Division of Health Sciences Informatics 5 Johns Hopkins Medicine Simulation Center, Baltimore, Maryland, USA 6 Stanford University School of Medicine, Palo Alto, California, USA 7 Department of Anesthesiology, Perioperative and Pain Medicine 8 Montefiore Einstein Center for Innovation in Simulation, Bronx, New York, USA 9 Johns Hopkins Hospital, Baltimore, Maryland, USA 10 Department of Emergency Medicine
M
an
us
2
d
Corresponding Author: Elizabeth A. Hunt Charlotte Bloomberg Children’s Center Division of Pediatric Anesthesiology and Critical Care Medicine 1800 Orleans Street Room 6321 Baltimore, MD 21287 Telephone: 410-614-0847 Email: [email protected] (can be published) No reprints will be ordered.
Ac ce pt e
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
Fax: 410-614-9878
Source of funding: None Direct Conflicts of Interest: None Financial Disclosures: Drs. Hunt and Shilkofski both have grant funding for unrelated projects from the Laerdal Foundation for Acute Care Medicine. Drs. Hunt and Mr. Duval-Arnould have granting funding for unrelated projects from the Hartwell Foundation. Dr. Hunt, Mr. Duval-Arnould and Ms. Perretta have received reimbursement for travel expenses and honoraria for speaking engagements from the Zoll Medical Corporation, with no restriction on the content and no prior review of slides. Dr. Hunt is a volunteer member of the AHA ECC Science Committee and the AHA Get With The Guidelines – Resuscitation Clinical Working Group. Key words:
cardiac arrest, cardiopulmonary resuscitation, simulation, teamwork, time sensitive, education Manuscript Word Count: 2,999 Abstract Word Count: 250 words This paper includes 3 tables and 2 figures and 6 online appendices.
1
Page 1 of 26
Objective: To compare resuscitation performance on simulated in-hospital cardiac
48
arrests after traditional American Heart Association (AHA) Healthcare Provider Basic
49
Life Support course (TradBLS) versus revised course including in-hospital skills
50
(HospBLS).
51
Design: Prospective, randomized, controlled curriculum evaluation.
52
Setting: Johns Hopkins Medicine Simulation Center.
53
Subjects: One hundred twenty-two first year medical students divided into fifty-nine
54
teams.
55
Intervention: HospBLS course of identical length, containing additional content
56
contextual to hospital environments, taught utilizing Rapid Cycle Deliberate Practice
57
(RCDP).
58
Measurements: The primary outcome measure during simulated cardiac arrest scenarios
59
was chest compression fraction (CCF) and secondary outcome measures included metrics
60
of high quality resuscitation.
61
Main Results:
62
Out-Of-Hospital Cardiac Arrest
63
HospBLS teams had larger CCF: (69%(65-74) vs 58%(53-62), p<0.001] and were faster
64
than TradBLS at initiating compressions: [median(IQR): 9 seconds(s)(7-12) vs. 22s(17.5-
65
30.5), p<0.001].
66
In-Hospital Cardiac Arrest
67
HospBLS teams had larger CCF: [73%(68-75%) vs. 50%(43-54%)), p<0.001) and were
68
faster to initiate compressions: [10s(6-11) vs. 36s(27-63), p<0.001]. All teams utilized the
69
hospital AED to defibrillate within 180 seconds per AHA guidelines, [HospBLS:
Ac ce pt e
d
M
an
us
cr
ip t
47
2
Page 2 of 26
70
122s(103-149) vs. TradBLS: 139s(116-172), p=0.09]. HospBLS teams performed more
71
hospital-specific maneuvers to optimize compressions, i.e. utilized: CPR button to flatten
72
bed: [7/30(23%) vs. 0/29(0%), p=0.006], backboard: [21/30(70%) vs. 5/29(17%),
73
p<0.001],
74
[28/30(93%) vs. 10/29(34%), p<0.001], connected oxygen appropriately: [26/30(87%) vs.
75
1/29(3%), p<0.001] and used oral airway and/or 2-person bagging when traditional bag-
76
mask-ventilation unsuccessful: [30/30(100%) vs. 0/29(0%), p<0.001].
77
Conclusion: A hospital focused BLS course utilizing RCDP was associated with
78
improved performance on hospital-specific quality measures compared to the traditional
79
AHA course.
[28/30(93%) vs. 8/29(28%), p<0.001], lowered bedrails:
an
us
cr
ip t
stepstool:
83 84 85 86 87 88 89
d
82
Ac ce pt e
81
M
80
90 91 92
3
Page 3 of 26
93 Introduction:
95
Each year, approximately 200,000 patients in the United States have an in-hospital
96
cardiac arrest (IHCA) with attempted resuscitation.1 Girotra reported increase in survival
97
to discharge from IHCA between 2000 and 2009 for both adults (13.7% to 22.3%) and
98
children (14.3% to 43.4%), with no increase in neurologic disability.2.3 The increasing
99
neurologically intact survival rates are encouraging. However, further examination
100
reveals significant variation across hospitals in both survival rates and magnitude of
101
improvement over time.4,5 Given these reports take into account patient demographics
102
and case mix severity, this suggests hospital-level variation contributes to variability in
103
patient survival and represents an opportunity to further improve patient outcomes.
M
an
us
cr
ip t
94
104
Ornato et al analyzed the American Heart Association’s (AHA) Get-With-The-
106
Guidelines-Resuscitation
107
resuscitation system errors and survival to discharge.6 For example, GWTG-R defines an
108
error for any IHCA with an initial shockable rhythm not defibrillated within 2 minutes, as
109
this interval is associated with survival outcomes,6-9 and also varies between hospitals.10
110
Other rescuer performance variables associated with cardiac arrest survival include: time
111
to initiation of compressions11, pre-, peri- and post-shock pauses,12-14 chest compression
112
fraction,15 rate16,17 and depth.17
d
105
Ac ce pt e
(GWTG-R) IHCA registry, reporting an association between
113 114
Historically, AHA Healthcare Provider BLS courses have not taught learners how to
115
navigate hospital-specific challenges. For example, a patient who collapses on a hard, flat
4
Page 4 of 26
sidewalk requires different strategies than an IHCA in a hospital bed with elevated head,
117
bedrails, lying on a soft mattress that deflects downward with compressions. The
118
traditional curriculum requires rescuers to perform CPR on the floor with no inclusion of
119
other possible environments. The 2015 AHA guidelines now calls for contextualization
120
of training scenarios to be relevant to the “learner’s real world setting”.18 Altering the
121
manner in which we teach BLS to match the manner in which it most likely to be used by
122
our learners may build resiliency and improve resuscitation performance. However, we
123
are unaware of literature examining the impact of increasing the level of environmental
124
realism during BLS curricula on performance during IHCA.
an
us
cr
ip t
116
125
We hypothesized students completing a traditional AHA Healthcare Provider BLS
127
course would perform well on a simulated OOHCA, but less well when confronted with a
128
typical IHCA. Our objectives were to: 1) measure whether learners participating in
129
existing AHA Healthcare Provider (TradBLS) courses met key resuscitation outcome
130
measures in an IHCA scenario, 2) evaluate learning outcomes of the TradBLS course
131
compared to a revised course (HospBLS) amended to include contextually relevant
132
curriculum specific to the hospital environment and 3) assess for unintended
133
consequences of added hospital content, i.e. worse performance on OOHCA scenarios.
d
Ac ce pt e
134
M
126
135
Materials and Methods:
136
Study Design
137
A prospective, randomized, controlled evaluation of an educational intervention was
138
conducted. The population was first-year medical students at The Johns Hopkins
5
Page 5 of 26
University School of Medicine (JHUSOM) who enrolled into one of six sessions most
140
convenient for their schedule. Each session had 21 available slots. All were conducted
141
over a three-month period. After enrollment was complete, each session was randomized
142
to control or intervention. Block randomization in a single block of six, with an opaque
143
envelope containing study arm assignments in ratio of 1:1, was utilized to ensure equal
144
allocation of subjects with three TradBLS and three HospBLS courses. Participation was
145
mandatory as this was a quality assurance exercise to determine which course would
146
continue in the JHUSOM curriculum in subsequent years. This project was approved by
147
the JHUSOM Institutional Review Board as an Educational Quality Assurance
148
evaluation.
an
us
cr
ip t
139
M
149 Educational Intervention
151
The curricula being compared were both video-guided and instructor-led, i.e. TradBLS
152
versus a course of equal length, identical OOHCA content, plus additional objectives and
153
curriculum focused on managing IHCA (“HospBLS”). The latter included goals related
154
to effective bag-mask-ventilation, use of in-hospital equipment and crisis resource
155
management. Both courses utilized the 2010 AHA instructor materials and were
156
completed per AHA guidelines.19 After demonstrating to Senior AHA Leadership how
157
the revised curriculum met the Healthcare Provider BLS objectives, we were permitted to
158
distribute AHA certification cards for our experimental course.
Ac ce pt e
d
150
159 160
The additional IHCA-specific objectives were taught using the Rapid Cycle Deliberate
161
Practice (RCDP) educational approach.20 Existing AHA BLS faculty were recruited as
6
Page 6 of 26
instructors, a subset learned the new objectives and the RCDP technique for the high-
163
fidelity simulation IHCA stations. Prior to the study sessions, this group taught the
164
HospBLS course in an apprentice model with ongoing feedback until they achieved
165
mastery as faculty of this course. All six courses had a lead instructor who developed the
166
intervention content and a co-instructor, who together assured completion of key learning
167
objectives and appropriate time management. See Appendix A, B, C for an overview of
168
the HospBLS curriculum, list of TradBLS learning objectives and highlight of additional
169
learning objectives in the HospBLS course, and a HospBLS course timetable.
us
cr
ip t
162
an
170 Assessment Tools and Outcome Measures
172
Upon arrival to the Johns Hopkins Medicine Simulation Center, each student completed a
173
pre-course demographic survey. After completion of the course, students completed the
174
standard AHA BLS course skills testing, multiple choice question (MCQ) post-course
175
exam and course evaluation tool. Study assessments included:
177 178 179 180 181 182
d
Ac ce pt e
176
M
171
1) Additional MCQs to Assess IHCA knowledge: Five MCQs were created by course faculty, assessed for readability and face
validity by a group of senior medical students and assessed for construct validity
by a resuscitation scientist and a group of physicians with specialized training in critical care and emergency medicine, all of whom are involved in resuscitation research and education.
183 184
2) High-Fidelity Simulation Scenarios:
7
Page 7 of 26
185
Students participated as teams of two or three in two 5-minute summative
186
assessments. (Appendix D)
187
OOHCA scenario:
188
A woman (Resusci Anne
189
baseball park, and was found unresponsive and pulseless by a study confederate
190
who asked the learners for help.
191
IHCA scenario:
192
A man (SimMan
193
a hospital gown, head on a pillow, head of bed up, side rails up) became gray and
194
unresponsive, thus two confederate nurses call for help.
us
cr
ip t
Simulator) collapsed on the bathroom floor at a
an
3G) in a hospital bed, in a simulated hospital room (manikin in
M
195
The primary outcome measure was the chest compression fraction (CCF) based on
197
observations that students confronted with a simulated IHCA struggle with navigating the
198
environment, causing both delays and frequent pauses in chest compressions. Secondary
199
outcome measures included time elapsed from call for help and entry of participants into
200
room to: 1) initiation of chest compressions and 2) first defibrillation, as well as
201
knowledge and performance of IHCA-specific CPR quality process measures, i.e. use of
202
stepstool, backboard, “CPR lever” to automatically flatten hospital bed, maneuvers in
203
response to being unable to effectively ventilate with one-person bagging (i.e. either two-
204
person BMV and/or placement of oral airway), oxygen tubing connected to oxygen flow
205
meter, and proper flow rates for oxygen.
Ac ce pt e
d
196
206 207
Effect Size Calculation
8
Page 8 of 26
A convenience sample of 122 first-year medical students divided into teams of two
209
projected 30 teams per study arm. Pilot data from previous TradBLS courses had a
210
mean(±standard deviation) CCF of 0.50(±0.08). Assuming an alpha of 0.05, beta of 0.2,
211
our sample size gave us 80% power to detect a clinically significant difference in the
212
CCF as small as .06.
ip t
208
cr
213 Data Abstraction
215
Two video angles were captured for all scenarios to facilitate review. Two different sets
216
of reviewers abstracted data from the video recordings of the IHCA and OOHCA
217
summative assessments. The reviewers used custom-built software designed to facilitate
218
accurate and efficient data collection. Data captured were automatically exported to
219
comma-separated values (CSV) file, combined and transferred to Stata/IC 13 (StataCorp
220
LP, College Station, TX) for statistical analysis, eliminating risk of transcription errors.
221
Reviewers were blinded to study group allocation of the participants. For each set of
222
videos, 20% were scored by both reviewers independently in order to calculate inter-rater
223
reliability.
an
M
d
Ac ce pt e
224
us
214
225
Data Analysis
226
Proportions were calculated for categorical variables and compared using the chi square
227
statistic. Means and standard deviations were calculated for continuous variables with t-
228
test comparison of means reported. If data were not normally distributed, then medians
229
and interquartile ranges were reported and groups were compared utilizing the Wilcoxon
230
Rank Sum test. A p-value < 0.05 was considered significant. For inter-rater reliability,
9
Page 9 of 26
correlation coefficients were calculated on the 20% overlap samples for all primary
232
outcome measures. The study methods adhered to the CONSORT 2010 and simulation-
233
based guidelines.21,22 (Appendix E, F)
234
Results:
235
One hundred twenty-two students were enrolled and divided into fifty-nine teams. All
236
students completed each assessment, either as an individual or part of a team. The two
237
groups were similar at baseline in terms of training and experience except more TradBLS
238
students were BLS instructors whereas more of the HospBLS students had assisted with
239
real-life CPR in the past. (Table 1) However, there were too few of these students for us
240
to control for these differences in our analysis. All students passed the AHA MCQ test
241
and skills assessment necessary to receive their BLS cards – the results of this evaluation
242
are not included as part of the results.
d
243
M
an
us
cr
ip t
231
Knowledge
245
The HospBLS group was significantly more likely to identify a set of a priori identified
246
maneuvers to improve quality of in-hospital CPR. The HospBLS group was also more
247
likely to identify ideal oxygen flow rates and maneuvers to attempt when unable to
248
effectively ventilate. (Table 2)
249
Ac ce pt e
244
250
Simulation Skills Performance
251
Overview of TradBLS Team Performance
252
All TradBLS students passed the AHA skills stations and met the overarching objectives,
253
i.e. started chest compressions and defibrillated the manikin in both the OOHCA and
10
Page 10 of 26
IHCA high-fidelity summative assessments. However, in the IHCA assessment 25% of
255
TradBLS teams took more than a minute to start compressions and few teams performed
256
any maneuvers to optimize quality of compressions for a patient in a hospital bed.
257
Regarding airway management, only one team connected oxygen tubing to the flow
258
meter and chose an appropriate flow rate. None of the TradBLS teams independently
259
noticed the manikin’s chest was not rising in response to bagging, and once pointed out to
260
them by a confederate, no teams performed any maneuvers beyond repositioning the
261
mask in an attempt to address the insufficient ventilation. (Tables 3-5)
263
Detailed Comparison of TradBLS and HospBLS Simulation Performance
264
Out-Of-Hospital Cardiac Arrest
265
All teams started compressions and successfully operated a public access AED. However,
266
HospBLS teams had larger CCF: [69% (65-74) vs 58% (53-62), p<0.001], were faster at
267
initiating compressions: [median: 9 seconds (IQR:7-12) vs. 22 (18-31), p<0.001], and had
268
shorter pre-shock pauses. (Table 5)
269
In-Hospital Cardiac Arrest
270
HospBLS teams had larger CCF and were quicker to initiate compressions. (Figures 1
271
and 2) In addition, HospBLS teams were more likely to perform IHCA-specific
272
maneuvers to optimize compressions: utilize CPR button to quickly flatten bed, lower
273
side rails, and utilize backboard and stepstool. All teams utilized the AED to defibrillate
274
within 180 seconds per AHA guidelines, [HospBLS: 122 sec (103-149) vs. TradBLS: 139
275
(116 vs. 172), p=0.09]. HospBLS teams were more likely to optimize airway
276
management: connect oxygen tubing and use appropriate flow rate [87% (26/30) vs. 3%
Ac ce pt e
d
M
an
262
us
cr
ip t
254
11
Page 11 of 26
(1/29), p<0.001]. Most remarkably, none of the TradBLS teams used any maneuvers
278
beyond repositioning the mask (oral airway and/or 2-person approach to assist with
279
bagging) when traditional BMV was unsuccessful, whereas every HospBLS team did so:
280
[100% (30/30) vs. 0% (0/29), p<0.001]. (Tables 3 and 4)
ip t
277
281 Inter-rater reliability
283
Pairwise inter-rater assessments of initiation of compression time (0.99), defibrillation
284
time (0.99) and compression fraction (0.90) were strongly correlated, p <0.05.
us
cr
282
an
285 Discussion:
287
Our data highlight that students who completed a TradBLS course based on the 2010
288
AHA guidelines met existing AHA learning objectives.19 However, other than
289
rudimentary BMV skills they did not appear to acquire any BLS skills that differentiate
290
the lay provider from the healthcare provider and were not prepared to manage issues
291
common to IHCA, such as resuscitating patients in a bed rather than on the floor. Both
292
the training and skill assessments of traditional courses were conducted in a fashion that
293
is incongruent with the manner in which CPR is actually performed during IHCAs.
294
Though all content from the 2010 AHA curricula are essential, our HospBLS learning
295
objectives addressed additional essential skills for those working in the hospital
296
environment. Our data highlight that managing IHCAs is not intuitive and thus requires
297
direct instruction. Our HospBLS learners developed a shared mental model (i.e.
298
compatible understanding amongst team members of roles, tasks, and the situation) of an
299
IHCA “high performing team”, i.e. how a larger team of 3 to 6 people (as is frequently
Ac ce pt e
d
M
286
12
Page 12 of 26
the situation in a hospital) will quickly assemble themselves into a well-oiled machine to
301
manage the first few minutes of an IHCA.23 These findings have three central
302
implications for future Healthcare Provider BLS training related to content as well as
303
delivery method.
ip t
300
304
First, in addition to foundational resuscitation skills targeted in traditional BLS programs,
306
a broader range of contextual skills are trainable, and may impact critical resuscitation
307
outcomes. These skills include recognizing and managing environmental factors unique
308
to the hospital setting (e.g. use of available hospital equipment, adapting chest
309
compression technique to the design of a hospital bed, etc…).24,25 Specifics of these
310
competencies may vary by hospital, as factors such as physical layout, equipment
311
models, and procedural considerations can impact CPR performance. However, a general
312
framework of the types of factors to address in training could be developed. This
313
framework, along with appropriate curriculum design guidance, would allow local
314
trainers to customize contextual aspects of BLS training while maintaining alignment
315
with a national curriculum. In terms of operationalizing this content beyond medical
316
students, our institution has one version of this contextual curriculum for medical
317
students who have not previously worked in the hospital setting, another for new nurses
318
on orientation, another for Security Officers, and another for ICU staff. The idea is that
319
the curriculum has three levels, i.e. 1) core AHA BLS content on psychomotor skills of
320
chest compressions, BMV and defibrillation, 2) core content which is contextually
321
relevant to performing high quality BLS within the hospital setting and 3) extra content
322
contextually relevant to that population’s environment and role within that environment.
Ac ce pt e
d
M
an
us
cr
305
13
Page 13 of 26
323
It is exciting to note the 2015 AHA guidelines section on education now includes
324
contextualization as a “core educational concept”.18
325 Second, practicing CPR under a broader range of conditions may be beneficial in its own
327
right. The variability of practice effect is a phenomenon wherein acquisition of skill and
328
transfer of training are improved when an individual or team practices those skills under a
329
wider array of conditions. This effect is well-documented for simple procedural26 and
330
problem solving skills,27 as well as more complex team performance issues.28 Traditional
331
BLS courses are highly standardized, which is desirable to ensure every learner
332
completing the course has reached the same targeted level of proficiency. However, when
333
the traditional BLS course is the only version available for both new and advanced
334
learners in re-certification, this limits the resilience of the learner in the face of variability
335
in practice, and effectively restricts learners’ ability to advance beyond fundamentals.
336
There appears to be value in an ‘advanced’ BLS course, one that addresses the same core
337
clinical skills as the ‘basic’ course, but in more varied and complex situations. Taken
338
together, these two issues of contextual competencies and practice variability provide
339
direction for the maturation of BLS curricula. For the lay provider, BLS is basic.
340
Learners meet minimum thresholds of performance and that is the end of development.
341
Our study’s findings suggest it is worth considering BLS from a continuous professional
342
development perspective, where the fundamentals of BLS are elaborated upon in
343
different contexts. Advanced learners may gain more value from practicing skills in
344
different types of situations, tailored to the needs of a variety of learner groups versus the
345
current “one-size-fits-all” approach.
Ac ce pt e
d
M
an
us
cr
ip t
326
14
Page 14 of 26
346 Third, it is essential to stress the time-critical and high-stakes nature of cardiac arrest
348
during training. Small delays can adversely impact patients. Therefore, it is not
349
appropriate to leave the contextual skills for ‘on the job training,’ per current practice.
350
Teams that operate with a shared mental model perform better.29,30 Team training31 and
351
team planning32 enable teams to reach high levels of shared mental models and
352
performance. One promising path forward for BLS involves identifying those aspects of
353
performance that can be optimized and (i.e. ‘one best way’ clearly defined) standardized
354
across all settings, as well as those that should be defined and standardized locally.
355
Teams can then engage in repeated training to build shared mental models and efficiency.
356
Sullivan described the use of RCDP to perform 15-minute in situ simulation sessions to
357
drill ward nurses on the first few minutes of a ward IHCA.33 We suspect the key element
358
associated with the success of the HospBLS course is not necessarily the length of the
359
course, but explicit inclusion of skills specific to IHCA with opportunities to try again
360
(i.e. RCDP) until fundamental skills are mastered. Mastery learning techniques are
361
increasingly associated with improved educational outcomes, with specific reports in
362
relation to resuscitation topics.33-36
cr
us
an
M
d
Ac ce pt e
363
ip t
347
364
This study has several important limitations. First, while the HospBLS curriculum was
365
taught within the same time previously allocated for standard BLS for our students, this
366
three-hour course is longer than ultra-brief courses described in the literature.37 Lee
367
recently demonstrated while BLS skills can be learned in shorter courses, longer courses
368
were associated with improved performance.38 Second, the HospBLS course can be more
15
Page 15 of 26
resource-intensive than traditional BLS courses, secondary to the high-fidelity simulators,
370
simulated clinical environment and increased faculty to student ratios. However, we now
371
teach the course with traditional faculty-to-student ratios for AHA courses of 1:6 and
372
lower-fidelity simulators that still provide realistic practice opportunities. Requiring
373
students to navigate the highly realistic simulated hospital environment and equipment
374
may be the most important aspects of a contextual IHCA curriculum. Finally, we did not
375
obtain reliable data on depth and rate of compressions and thus cannot comment on the
376
impact of the adapted curriculum on that aspect of quality CPR, nor can we comment on
377
translation of skills into the actual patient environment.
an
us
cr
ip t
369
378 Conclusions:
380
Medical students participating in a traditional BLS course did not perform well in a
381
simulated IHCA. Our data support use of RCDP to teach BLS curricula that is
382
contextually relevant to both the in and out-of-hospital setting as components of the
383
standard AHA Healthcare Provider BLS course.
d
Ac ce pt e
384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399
M
379
16
Page 16 of 26
ip t cr
References:
us
1. Merchant RM, Yang L, Becker LB, et al; American Heart Association Get With The Guidelines-Resuscitation Investigators. Incidence of treated cardiac arrest in hospitalized patients in the United States. Crit Care Med. 2011 Nov;39(11):2401-6.
M
an
2. Girotra S, Nallamothu BK, Spertus JA, Li Y, Krumholz HM, Chan PS; American Heart Association Get with the Guidelines–Resuscitation Investigators. Trends in survival after in-hospital cardiac arrest. N Engl J Med. 2012 Nov 15;367(20):191220.
d
3. Girotra S, Spertus JA, Li Y, Berg RA, Nadkarni VM, Chan PS; American Heart Association Get With the Guidelines–Resuscitation Investigators. Survival trends in pediatric in-hospital cardiac arrests: an analysis from Get With the GuidelinesResuscitation. Circ Cardiovasc Qual Outcomes. 2013 Jan 1;6(1):42-9. 4. Merchant RM, Berg RA, Yang L, Becker LB, Groeneveld PW, Chan PS; American Heart Association's Get With the Guidelines-Resuscitation Investigators. Hospital variation in survival after in-hospital cardiac arrest. J Am Heart Assoc. 2014 Jan 31;3(1):e000400.
Ac ce pt e
400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443
5. Girotra S, Cram P, Spertus JA, et al; American Heart Association's Get With the Guidelines®‐Resuscitation Investigators. Hospital variation in survival trends for inhospital cardiac arrest. J Am Heart Assoc. 2014 Jun 10;3(3):e000871. 6. Ornato JP, Peberdy MA, Reid RD, Feeser VR, Dhindsa HS; NRCPR Investigators. Impact of resuscitation system errors on survival from in-hospital cardiac arrest. Resuscitation. 2012 Jan;83(1):63-9. 7. Hazinski MF, Shuster M, Donnino MW, et al. Highlights of the 2015 American Heart Association Guidelines Update for CPR and ECC. Available at: https://eccguidelines.heart.org/wp-content/uploads/2015/10/2015-AHA-GuidelinesHighlights-English.pdf. Accessed September 21, 2016.
17
Page 17 of 26
8. Herlitz J, Aune S, Bång A, et al. Very high survival among patients defibrillated at an early stage after in-hospital ventricular fibrillation on wards with and without monitoring facilities. Resuscitation. 2005 Aug;66(2):159-66.
ip t
9. Chan PS, Krumholz HM, Nichol G, Nallamothu BK; American Heart Association National Registry of Cardiopulmonary Resuscitation Investigators. Delayed time to defibrillation after in-hospital cardiac arrest. N Engl J Med. 2008 Jan 3;358(1):9-17.
cr
10. Chan PS, Nichol G, Krumholz HM, Spertus JA, Nallamothu BK; American Heart Association National Registry of Cardiopulmonary Resuscitation (NRCPR) Investigators. Hospital variation in time to defibrillation after in-hospital cardiac arrest. Arch Intern Med. 2009 Jul 27;169(14):1265-73.
us
11. Herlitz J, Bang A, Alsen B, Aune S. Characteristics and outcome among patients suffering from in hospital cardiac arrest in relation to the interval between collapse and start of CPR. Resuscitation.2002;53:21– 27.
M
an
12. Edelson DP, Abella BS, Kramer-Johansen J, et al. Effects of compression depth and pre-shock pauses predict defibrillation failure during cardiac arrest. Resuscitation. 2006 Nov;71(2):137-45.
d
13. Sell RE, Sarno R, Lawrence B, et al. Minimizing pre- and post-defibrillation pauses increases the likelihood of return of spontaneous circulation (ROSC). Resuscitation. 2010 Jul;81(7):822-5. 14. Cheskes S, Schmicker RH, Verbeek PR, et al; Resuscitation Outcomes Consortium (ROC) investigators.The impact of peri-shock pause on survival from out-of-hospital shockable cardiac arrest during the Resuscitation Outcomes Consortium PRIMED trial. Resuscitation. 2014 Mar;85(3):336-42.
Ac ce pt e
444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489
15. Christenson J, Andrusiek D, Everson-Stewart S, et al; Resuscitation Outcomes Consortium Investigators. Chest compression fraction determines survival in patients with out-of-hospital ventricular fibrillation. Circulation. 2009 Sep 29;120(13):1241-7. 16. Idris AH, Guffey D, Pepe PE, et al; Resuscitation Outcomes Consortium Investigators. Chest compression rates and survival following out-of-hospital cardiac arrest. Critical Care Med. 2015 Apr;43(4):840-8. 17. Talikowska M, Tohira H, Finn J. Cardiopulmonary resuscitation quality and patient survival outcome in cardiac arrest: A systematic review and meta-analysis. Resuscitation. 2015 Nov;96:66-77. 18. Bhanji F, Donoghue AJ, Wolff MS, Flores GE, Halamek LP, Berman JM, Sinz EH, Cheng A. Part 14: Education: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation. 2015 Nov;132(18 Suppl 2):S561-73.
18
Page 18 of 26
19. Berg RA, Hemphill R, Abella BS, Aufderheide TP, Cave DM, Hazinski MF, Lerner EB, Rea TD, Sayre MR, Swor RA. Part 5: adult basic life support: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation. 2010 Nov;122(18 Suppl 3):S685-705.
ip t
20. Hunt EA, Duval-Arnould JM, Nelson-McMillan KL, et al. Pediatric resident resuscitation skills improve after "rapid cycle deliberate practice" training. Resuscitation. 2014 Jul;85(7):945-51.
cr
21. www.consort-statement.org, accessed 10/14/2016.
us
22. Cheng A, Kessler D, Mackinnon R, et al. Reporting Guidelines for Health Care Simulation Research: Extensions to the CONSORT and STROBE Statements. Simul Healthc. 2016 Aug;11(4):238-48.
an
23. Hunt EA, Walker AR, Shaffner DH, Miller MR, Pronovost PJ. Simulation of inhospital pediatric medical emergencies and cardiopulmonary arrests: highlighting the importance of the first 5 minutes. Pediatrics. 2008 Jan;121(1):e34-43.
M
24. Lee DH, Kim CW, Kim SE, Lee SJ. Use of step stool during resuscitation improved the quality of chest compression in simulated resuscitation. Emerg Med Australas. 2012 Aug;24(4):369-73.
d
25. Oh J, Chee Y, Lim T, Cho Y, Kim IY. Chest compression with kneeling posture in hospital cardiopulmonary resuscitation: A randomised crossover simulation study. Emerg Med Australas. 2014 Dec;26(6):585-90.
Ac ce pt e
490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535
26. Holladay CL, Quinones MA. Practice variability and transfer of training: the role of self-efficacy generality. Journal of Applied Psychology. 2003 Dec;88(6):1094. 27. de Croock MB, van Merriënboer JJ, Paas FG. High versus low contextual interference in simulation-based training of troubleshooting skills: Effects on transfer performance and invested mental effort. Computers in Human Behavior. 1998 May 25;14(2):249-67. 28. Gorman JC, Cooke NJ, Amazeen PG. Training adaptive teams. Human Factors: The Journal of the Human Factors and Ergonomics Society. 2010 Jul 23. 29. Mathieu JE, Heffner TS, Goodwin GF, Salas E, Cannon-Bowers JA. The influence of shared mental models on team process and performance. Journal of Applied Psychology. 2000 Apr;85(2):273. 30. DeChurch LA, Mesmer-Magnus JR. The cognitive underpinnings of effective teamwork: a meta-analysis. Journal of Applied Psychology. 2010 Jan;95(1):32.
19
Page 19 of 26
31. Salas E, Diaz Granados D, Klein C, et al. Does team training improve team performance? A meta-analysis. Human Factors: The Journal of the Human Factors and Ergonomics Society. 2008 Dec 1;50(6):903-33.
ip t
32. Stout RJ, Cannon-Bowers JA, Salas E, Milanovich DM. Planning, shared mental models, and coordinated performance: An empirical link is established. Human Factors: The Journal of the Human Factors and Ergonomics Society. 1999 Mar 1;41(1):61-71.
us
cr
33. Sullivan NJ, Duval-Arnould J, Twilley M, Smith SP, Aksamit D, Boone-Guercio P, Jeffries PR, Hunt EA. Simulation exercise to improve retention of cardiopulmonary resuscitation priorities for in-hospital cardiac arrests: A randomized controlled trial. Resuscitation. 2015 Jan;86:6-13. 34. McGaghie WC. Mastery learning: it is time for medical education to join the 21st century. Academic Medicine. 2015 Nov;90(11):1438-41.
M
an
35. Eppich WJ, Hunt EA, Duval-Arnould JM, Siddall VJ, Cheng A. Structuring feedback and debriefing to achieve mastery learning goals. Academic Medicine. 2015 Nov;90(11):1501-8.
d
36. Barsuk JH, Cohen ER, Wayne DB, Siddall VJ, McGaghie WC. Developing a Simulation-Based Mastery Learning Curriculum: Lessons From 11 Years of Advanced Cardiac Life Support. Simulation in Healthcare. 2016 Feb;11(1):52-9. 37. Panchal AR, Meziab O, Stolz U, et al. The impact of ultrabrief chest compressiononly CPR video training on responsiveness, compression rate, and hands-off time interval among bystanders in a shopping mall. Resuscitation. 2014 Sep;85(9):128790.
Ac ce pt e
536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569
38. Lee JH, Cho Y, Kang KH, Cho GC, Song KJ, Lee CH. The Effect of the Duration of Basic Life Support Training on the Learners' Cardiopulmonary and Automated External Defibrillator Skills. Biomed Res Int. 2016;2016:2420568. Epub 2016 Jul 27.
20
Page 20 of 26
Table 1
Table 1. Demographics of Individual Participants HospBLS
(Control)
(Intervention)
(n=60)
(n=62)
% (n)
% (n)
48%(29)
Previous ECC certification BLS
52%(31)
48%(30)
us
Male
cr
Baseline Characteristics
ip t
TradBLS
53%(33)
2% (1)
ACLS
2% (1)
3% (2)
97%(58)
95%(59)
8% (5)
0% (0)
3% (2)
15% (9)
0% (0)
2% (1)
EMT
0% (0)
5% (3)
Respiratory Therapist
2% (1)
0% (0)
Life Guard
0% (0)
5% (3)
Other
2% (1)
3% (2)
an
PALS
M
Neither PALS or ACLS
Real-life CPR role
Ac ce p
Nurse
te
Assisted with real-life CPR
d
BLS Instructor
0% (0)
Page 21 of 26
Table 2
Table 2. Knowledge Assessment of Individual Participants
(Control)
(Intervention)
(n=60)
(n=62)
% (n)
%(n)
P Value
ip t
Compressions
HospBLS
cr
Assessment Topic
TradBLS
Correct identification of methods to
us
improve quality of chest compressions*
27%(16)
87%(54)
<0.001
Identified at least 5 methods
58%(35)
100%(62)
<0.001
18%(11)
77%(48)
<0.001
17%(10)
90%(56)
<0.001
92%(55)
98%(61)
0.09
Respirations
M
Correct identification of 2-person BMV to
improve ventilation when chest rise is not
d
visible^
Ac ce p
Defibrillation
te
Correct identification of 15L/min O2 flow during use with BMV
an
Identified all 6 methods
Correct identification of AED as single first piece of equipment to request
*In MCQ assessment, the following six choices were considered methods that can be used to improve quality of chest compressions: 1) Lowering the head of the bed, 2) Lowering the bed, 3) Compressor standing on a step stool, 4) Positioning compressor’s shoulders above the patient, 5) Locking compressor’s elbows, 6) Putting patient on a hard surface, i.e. back board ^ BMV = Bag-Mask-Ventilation
Page 22 of 26
Table 3
Table 3. Team Performance in Simulated Cardiopulmonary Arrests Simulation Scenario
TradBLS
HospBLS
Outcome Measures
(Control)
(Intervention)
(n=29)*
(n=30)*
22 (18-31)
9 (7-12)
<0.001
0% (0)
67%(20)
<0.001
0.58 (0.53-0.62)
0.69 (0.65-0.74)
<0.001
7% (2)
63%(19)
<0.001
15 (14-21)
0.05
36 (27-63)
10 (6-11)
<0.001
0% (0)
63%(19)
<0.001
0.5 (0.43-0.54)
0.73 (0.68-0.75)
<0.001
3% (1)
43%(13)
<0.001
0% (0)
23% (7)
0.006
Lowered bedrails, %(n)
34%(10)
93%(28)
<0.001
Utilized backboard, %(n)
17% (5)
70%(21)
<0.001
Utilized stepstool, %(n)
28% (8)
93%(28)
<0.001
3% (1)
87%(26)
<0.001
Chest Compression Fraction+, median (IQR)
an
Verbalized Cycle Number, %(n)
Out-of-Hospital: Defibrillation
In-Hospital: Chest Compressions
te
Compressions by 10s, %(n)
d
Time to starting, median (IQR), s
Chest Compression Fraction+,
Ac ce p
median (IQR)
22 (15-27)
M
Pre-shock Pause, median (IQR), s
Verbalized Cycle Number, %(n)
Utilized CPR button to flatten bed, %(n)
cr
Compressions by 10s, %(n)
us
Time to starting, median (IQR), s
ip t
Out-of-Hospital: Chest Compressions
P Value
In-Hospital: Airway Optimization Attached O2 with appropriate flow, %(n)
Page 23 of 26
Used oral airway and/or 2-person
0% (0)
100%(30)
<0.001
139 (117-172)
122 (103-149)
0.09
79%(23)
87%(26)
0.45
18 (12-25)
13 (6-11)
0.07
bagging, %(n)
Time to defib, median (IQR), s Defibrillation by 180s, %(n) Pre-shock Pause, median (IQR), s
ip t
In-Hospital: Defibrillation
cr
*Unit of analysis is at the 2-person team level; Wilcoxon rank sum for median, Chi square for proportions
us
+Chest Compression Fraction is defined as the amount of time during which the simulated patient was
Ac ce p
te
d
M
an
pulseless and receiving chest compressions.
Page 24 of 26
Figure 1
pt ce
Ac
63
36
27
11 6
9.5 Page 25 of 26
0
Compression Start Time (seconds) 60 80 40 20
100
ed
IHCA Time to Initiation of Chest Compressions TradBLS vs. HospBLS (median, IQR) p<0.001
TradBLS
HospBLS
54%
ce
pt
ed
IHCA Chest Compression Fraction TradBLS vs. HospBLS (median, IQR) p<0.001
Ac
0 10 20 30 40 50 60 70 80 90 100
Chest Compression Fraction (%)
Figure 2
75% 68%
73%
50%
43%
Page 26 of 26
TradBLS
HospBLS