Clinical Trial Details
— Status: Not yet recruiting
Administrative data
| NCT number |
NCT06411327 |
| Other study ID # |
LevMax 232403355 |
| Secondary ID |
232403355 |
| Status |
Not yet recruiting |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
January 1, 2025 |
| Est. completion date |
June 30, 2028 |
Study information
| Verified date |
May 2024 |
| Source |
KidSIM Simulation Program |
| Contact |
Adam Cheng, MD |
| Phone |
4039552633 |
| Email |
Adam.Cheng[@]albertahealthservices.ca |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
Cognitive aids are decision support tools that present prompts to encourage recall of
information, thus freeing up mental resources to increase the likelihood of desired
behaviors. Cognitive aids have been trialed in different forms for use during resuscitation,
including pocket reference cards and digital apps. Simulation-based studies of cognitive aid
used during cardiac arrest events have shown improved adherence to guidelines, improved time
to completing critical tasks, and reduced rate of critical errors. Unfortunately, existing
pocket reference cards and mobile apps have significant flaws - they all require providers to
search through content to identify relevant information.
In the proposed study, we will evaluate the impact of an enhanced system, InterFACE-AR, which
provides role-specific decision support to the team leader and medication nurse through AR
devices, while concurrently optimizing team situational awareness by displaying a roadmap for
patient care on the LCD screen. Clinical data will be collected from the mobile app on a
tablet used by the charting nurse. The trial aims to assess the individual and combined
effectiveness of InterFACE-AR components (i.e. AR devices and LCD screen) on adherence to AHA
resuscitation guidelines during simulated cardiac arrest by conducting a randomized
controlled trial with a factorial design.
Description:
Introduction Cardiopulmonary resuscitation (CPR) is provided for thousands of patients
suffering from cardiopulmonary arrests (CPA) each year in North America. The provision of
guideline-compliant basic life support (BLS) and advanced life support (ALS) improves patient
outcomes following cardiac arrest. Unfortunately, healthcare providers struggle to
consistently perform guideline-compliant BLS4, 5 and ALSuring in-hospital cardiac arrest.
Deviations from American Heart Association (AHA) resuscitation guidelines are associated with
decreased survival from in-hospital cardiac arrest, signaling a pressing need to design,
evaluate, and implement novel strategies to improve the delivery of BLS and ALS care.
Delays in epinephrine administration, delays in defibrillation, medication dosing errors, and
errors in identification and treatment of the underlying condition, represent common
deviations from resuscitation guidelines associated with poor patient outcomes from cardiac
arrest. Prior studies point to high mental workload amongst resuscitation team members as a
major contributor to protocol deviations. The dynamic nature of resuscitation presents a
significant challenge for team leaders, who engage in complex cognitive process that result
in extremely high mental workload, leading to poor decision-making and errors. Reducing
mental workload of team members by providing decision support during resuscitation can
potentially improve quality of care during cardiac arrest. Our research team aims to address
these issues by designing a novel system that integrates augmented reality (AR) and
screen-based technology to provide decision support for resuscitation teams during
cardiopulmonary arrest.
Cognitive aids are decision support tools that present prompts to encourage recall of
information, thus freeing up mental resources to increase the likelihood of desired behavior.
Cognitive aids have been trialed in different forms for use during resuscitation, including
pocket reference cards and digital apps. Simulation-based studies of cognitive aid used
during cardiac arrest events have shown improved adherence to guidelines, improved time to
completing critical tasks, and reduced rate of critical errors. Unfortunately, existing
pocket reference cards and mobile apps have significant flaws - they all require providers to
search through content to identify relevant information. This presents a distraction and
increases mental workload - resulting in impaired communication and poor situational
awareness - both of which cause delays and errors in treatment.
Augmented reality (AR) and display screens have the potential of addressing these gaps.
Augmented reality can present individualized, role-specific guidance to potentially reduce
mental workload; while a display screen in the clinical environment can offer information to
the entire team to improve communication and enhance situational awareness.
Augmented reality using a head-mounted device allows for participant interaction with the
real environment while displaying three-dimensional interactive images in a user's field of
view without disturbing normal vision. AR-based cognitive aids enable fast decision making by
providing clinically relevant prompts and supporting anticipatory behaviors by listing
upcoming tasks. Studies completed by our research team have shown that an AR device providing
clinical guidance for the team leader improves compliance with pediatric and neonatal
resuscitation guidelines, but fell short on improving time to epinephrine or defibrillation.
In these studies, the AR systems were entirely reliant upon data collected from the team
leader through the AR device to determine the clinical guidance. This amplified team leader
workload which contributed to delays in task completionIn designing a new system, our
overarching goal is to reduce mental workload by providing role-specific and timely
information to key team resuscitation team members. To achieve this goal, we developed a
mobile app (i.e. Guiding Pad app), used by the charting nurse, which provides guidance on
pending tasks as the charting nurse enters completed tasks. The Guiding Pad app interfaces
with a large liquid crystal display (LCD) screen in the resuscitation room, providing a
collaborative platform used to support healthcare providers during management of cardiac
arrest - called InterFACE (Interconnected and Focused Mobile Applications in the Patient Care
Environment). Integration of the LCD screen allows for display of the cardiac arrest
algorithm and a running list of tasks completed, which we anticipate will promote
communication and shared situational awareness. When connected to AR devices, the Guiding Pad
app allows for role-specific decision support to be shared with the provider wearing the AR
device.
In the proposed study, we will evaluate the impact of an enhanced system, InterFACE-AR, which
provides role-specific decision support to the team leader and medication nurse through AR
devices, while concurrently optimizing team situational awareness by displaying a roadmap for
patient care on the LCD screen (Figure 1). Clinical data will be collected from the mobile
app on a tablet used by the charting nurse. The trial aims to assess the individual and
combined effectiveness of InterFACE-AR components (i.e. AR devices and LCD screen) on
adherence to AHA resuscitation guidelines during simulated cardiac arrest by conducting a
randomized controlled trial with a factorial design.
The primary aim is to determine, amongst pediatric healthcare teams, if the use of AR devices
alone (for the team leader and medication nurse), the LCD screen alone, or AR devices and LCD
screen combined (i.e. InterFACE-AR), compared to groups using the AHA pocket reference card
(control), improves adherence to AHA resuscitation guidelines. Our secondary aims are to
determine the impact of the AR devices, LCD screen and the full InterFACE-AR system on
provider workload, cognitive load, leadership and teamwork behaviors, types and patterns of
language used during resuscitation, clinical performance (e.g. number and types of pauses in
CPR), and to describe user experiences with the components of InterFACE-AR.
METHODS We will conduct a prospective, simulation-based randomized controlled trial with a
factorial study design. Simulation-based research confers the advantage of answering research
questions without risk of harm to patients. Ethics approval will be obtained at all sites.
Participants will be recruited to the study in teams of five, comprised of a team leader,
charting nurse, medication nurse, and two bedside clinicians who will perform CPR. Two
research actors, playing the scripted roles of airway provider and CPR Coach, will join each
group to comprise resuscitation team of seven healthcare providers. Actors will be trained
with methodology successfully used in prior multicenter trials. Participant teams will manage
one cardiopulmonary arrest simulation scenario, using the specific trial intervention
assigned during randomization.
Our factorial study design will assess the individual and synergistic impact of two
interventions designed to provide decision support: (a) Augmented reality devices for the
team leader and medication nurse; and (b) LCD Screen.
Intervention A: Augmented Reality Devices - data collected from the Guiding-Pad app will be
fed to two AR devices (i.e. team leader and medication nurse), which will provide
role-specific decision support for these two providers.
Intervention B: LCD Screen - data collected from the Guiding-Pad app will be fed to the LCD
screen, which will be mounted on a wall, in clear view for the entire resuscitation team to
see.
Intervention C: InterFACE-AR System - data collected from the Guiding-Pad app will be fed to
the two AR devices (i.e. team leader and medication nurse) to provide role-specific decision
support, and to the LCD screen, in clear view for the entire resuscitation team to see.
Control Group: AHA Pocket Reference Card - all participants will have access to the AHA
pocket reference card, which is the mostly commonly used cognitive aid during resuscitation.
Following randomization, all participants will view a standardized orientation video
describing the clinical environment, equipment, manikin functionality, and participant roles.
Video content will be customized to include an orientation to the intervention assigned to
each group, followed by a 15-minute table-top practice simulation where participants have
opportunity to use the assigned intervention in their provider roles by running through a
cardiac arrest scenario while seated at a table. For example, participants in the
InterFACE-AR group will do a table-top simulation with the medication nurse and team leader
using the AR device, charting nurse using the Guiding Pad app, and the LCD screen visible to
the entire team. Participants assigned to the control group will participate in a table-top
simulation using the AHA pocket reference card.
An 18-minute cardiopulmonary arrest simulation scenario (ventricular tachycardia to
ventricular fibrillation to pulseless electrical activity) will be run for all participants,
with CPR quality data collected by the Zoll R Series feedback defibrillator. All recruitment
sites will utilize the identical pediatric manikin (SimJuniorTM, Laerdal Corporation),
specifically designed and calibrated for CPR training. All simulation scenarios will be
tightly standardized by using a scenario template with highly scripted actor roles and
patient progression. Following completion of the scenario, participants will complete the
NASA-TLX survey, User Experience Questionnaire, System Usability Survey, Technology
Acceptance Model survey, and STAI survey. Scenarios will be videotaped from a birds-eye view
angle at the foot of the bed and by high-definition action cameras worn hand-free by the
leader and medication nurse. After the session, all participants will receive an educational
debriefing to address performance issues using a blended-method approach to debriefing.
Randomization will occur at the level of the team, stratified by study site and sex of the
team leader (to ensure equal distribution of sex in both arms), and conducted in blocks of 4
to ensure an even distribution of teams across study arms. Randomization packages will be
prepared at a central study site using a web-based random number generator (e.g.
www.sealedenvelope.com). Sequentially numbered recruitment packages provided for each site
will contain sealed opaque envelopes (i.e. one envelope per team) with study arm assignments
and unique identifier codes for participants.
Sample size estimation is based on the primary outcome measure. The sample size estimation
assumes that the main effects of the 2 different interventions on the time to first dose of
epinephrine would comprise the 2 primary comparisons. Allowing for Bonferroni adjustments, p
< 0.025 was considered statistically significant. Time to the first dose of epinephrine was
previously reported to be approximately 165 sec with a standard deviation of 60 sec. We aim
to improve the time to first dose of epinephrine to 120 sec, which is associated with
improved clinical outcomes from pediatric cardiac arrest10. Assuming similar variability
amongst teams receiving either intervention, to detect a difference of 45 sec in time to
administer first dose of epinephrine, with a power of 0.8 and a significance level of 0.025
for each of the comparison, the required sample size will be 68 teams (17 teams per study
arm). Based on our prior experiences with simulation-based research, we estimated 15% of
missing data due to technical issues. Accounting for missing data, we aim to recruit a total
of 80 teams (20 teams per study arm).
STATISTICAL ANALYSIS Demographic characteristics of participants including sex, gender,
profession, and experience will be reported using descriptive statistics across all study
arms. The analyses will be conducted in the unit of teams. We will use multivariable linear
regression analysis to assess the effect of both interventions on the primary and secondary
outcomes and include the interaction term in the model. As the effects of the two
interventions may be non-additive, we will also report the effect of each intervention at
each level of the other intervention. All estimates of intervention effects will be reported
as mean differences with 95% confidence intervals.
