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STUDYPROTOCOL
Study protocol for the Anesthesiology Control
Tower—Feedback Alerts to Supplement Treatments
(ACTFAST-3) trial: a pilot randomized controlled trial in
intraoperative telemedicine [version 2; referees: 2 approved]
StephenGregory , TeresaM.Murray-Torres , BradleyA.Fritz ,
ArbiBenAbdallah , DanielL.Helsten , TroyS.Wildes , AnshumanSharma ,
MichaelS.Avidan , ACTFASTStudyGroup
DepartmentofAnesthesiology,WashingtonUniversitySchoolofMedicine,St.Louis,Missouri,63110,USA
Equalcontributors
Abstract
:Eachyear,over300millionpeopleundergosurgicalproceduresBackground
worldwide.Despiteeffortstoimproveoutcomes,postoperativemorbidityand
mortalityarecommon.Manypatientsexperiencecomplicationsasaresultof
eithermedicalerrororfailuretoadheretoestablishedclinicalpractice
guidelines.Thisprotocoldescribesaclinicaltrialcomparinga
telemedicine-baseddecisionsupportsystem,theAnesthesiologyControl
Tower(ACT),withenhancedstandardintraoperativecare.
:Thisstudyisapragmatic,comparativeeffectivenesstrialthatwillMethods
randomizeapproximately12,000adultsurgicalpatientsonanoperatingroom
(OR)leveltoacontrolortoaninterventiongroup.AllORclinicianswillhave
accesstodecisionsupportsoftwarewithintheORasapartofenhanced
standardintraoperativecare.TheACTwillmonitorpatientsinbothgroupsand
willprovideadditionalsupporttothecliniciansassignedtointerventionORs.
Primaryoutcomesincludebloodglucosemanagementandtemperature
management.Secondaryoutcomeswillincludesurrogate,clinical,and
economicoutcomes,suchasincidenceofintraoperativehypotension,
postoperativerespiratorycompromise,acutekidneyinjury,delirium,and
volatileanestheticutilization.
:TheACTFAST-3studyhasbeenapprovedbytheEthics and dissemination
HumanResourceProtectionOffice(HRPO)atWashingtonUniversityinSt.
Louisandisregisteredatclinicaltrials.gov( ).RecruitmentforthisNCT02830126
protocolbeganinApril2017andwillendinDecember2018.Disseminationof
thefindingsofthisstudywilloccurviapresentationsatacademicconferences,
journalpublications,andeducationalmaterials.
Keywords
telemedicine,decisionsupport,protocol,randomizedcontrolledtrial
1* 1* 1
1 1 1 1
1
1
*
Referee Status:
InvitedReferees
version 2
published
24Aug2018
version 1
published
22May2018
1 2
report report
,UniversityofMichigan,Leif Saager
USA
,UniversityofMichigan,Michael Burns
USA
1
,UniversityofMorten H. Bestle
Copenhagen,Denmark
,UniversityChristian Ari Dalby Sørensen
ofCopenhagen,Denmark
2
22May2018, :623(First published: 7
)https://doi.org/10.12688/f1000research.14897.1
24Aug2018, :623(Latest published: 7
)https://doi.org/10.12688/f1000research.14897.2
v2
Page 1 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
MichaelS.Avidan( )Corresponding author: avidanm@wustl.edu
:Conceptualization,FundingAcquisition,Investigation,Methodology,Writing–OriginalDraftPreparation,Writing–Author roles: Gregory S
Review&Editing; :Conceptualization,FundingAcquisition,Investigation,Methodology,Writing–OriginalDraftPreparation,Murray-Torres TM
Writing–Review&Editing; :Conceptualization,Methodology,Writing–Review&Editing; :Conceptualization,FormalFritz BA Ben Abdallah A
Analysis,Methodology,Writing–Review&Editing; :Conceptualization,FundingAcquisition,Investigation,Writing–Review&Editing;Helsten DL
:Conceptualization,FundingAcquisition,Investigation,Methodology,Writing–Review&Editing; :Conceptualization,Wildes TS Sharma A
FundingAcquisition,Methodology,Writing–Review&Editing; :Conceptualization,FundingAcquisition,Investigation,Methodology,Avidan MS
Resources,Writing–Review&Editing;
Nocompetinginterestsweredisclosed.Competing interests:
TheACTFAST-3project,includingthisprotocol,hasbeenfundedbyagrantfromtheAgencyforHealthcareResearchandGrant information:
Quality(R21HS24581-01).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
©2018GregoryS .Thisisanopenaccessarticledistributedunderthetermsofthe ,whichCopyright: et al CreativeCommonsAttributionLicence
permitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalworkisproperlycited.
GregoryS,Murray-TorresTM,FritzBA How to cite this article: et al. Study protocol for the Anesthesiology Control Tower—Feedback
Alerts to Supplement Treatments (ACTFAST-3) trial: a pilot randomized controlled trial in intraoperative telemedicine [version 2;
2018, :623( )referees: 2 approved] F1000Research 7https://doi.org/10.12688/f1000research.14897.2
22May2018, :623( )First published: 7 https://doi.org/10.12688/f1000research.14897.1
Page 2 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
Amendments from Version 1
This new version of the ACTFAST-3 protocol addresses the
critiques of the referees of the initial version of the manuscript.
Specifically, this version expands the introduction to highlight
perioperative risk assessment and the role that deviation from
evidence-based standards of care plays in adverse perioperative
outcomes. In addition, this manuscript provides additional
detail on the rationale for the primary outcomes in the study
and attempts to address potential sources of bias raised by the
referees. This new version also contains a Supplementary File 1
that provides definitions for the postoperative surrogate outcomes
in the study.
See referee reports
REVISED
Introduction
Each year, over 300 million surgical procedures are performed
worldwide1. Unfortunately, many patients will experience sig-
nificant morbidity or mortality in the postoperative period2.
Research conducted at our institution and others has dem-
onstrated an early postoperative mortality rate ranging from
1–5% and 90-day to 1-year mortality rates between 5–10%2–13.
Additionally, 5–40% of patients will experience some type
of postoperative surgical complication, including surgical site
infection, respiratory complications, myocardial infarction,
stroke and acute kidney injury, resulting in a three- to seven-fold
increase in postoperative mortality3,4,11,12,14.
Despite the overall decline in surgical morbidity and mortality
over time, the risk of perioperative adverse events remains
substantial2. Some of this risk is a manifestation of either
underlying patient pathology or the complexity of the surgical
procedure itself, with increasingly complex registries and risk
score calculators available to provide assessment of periopera-
tive risk9,12,15,16. However, evidence also suggests that medical
errors contribute considerably to negative patient outcomes17,18.
Although some errors may be considered active, such as the
administration of an incorrect medication, the failure to follow
established clinical practice guidelines and recommendations
likely has a more significant overall detrimental effect on
patient outcomes. Prior studies have documented that
deviation from evidence-based standards of care is common
in a variety of settings. This, deviation appears to worsen
patient outcomes, including increases in surgical site infection,
postoperative pneumonia, and mortality19–25.
Interventions to improve patient safety and outcomes remain
a major focus in anesthesiology. The complexity of anesthetic
practice can lead to frequent cognitive errors in the periop-
erative arena26,27, suggesting that the development of a real-time,
tailored feedback system to support intraoperative decision-
making may be valuable. The development of automated
feedback and alerting systems has been demonstrated to improve
adherence to a number of treatment guidelines28–45. However,
the impact of decision support systems appears to decay over
time46–49, and improvements in process variables may not translate
into improved patient outcomes50.
In the intensive care unit (ICU), the use of remote monitoring
to augment care, commonly referred to as “telemedicine,”
decreases ICU mortality and the length of ICU stay, and
improves adherence to clinical practice guidelines51–55. While
this type of clinical decision support has seen robust adoption
in the critical care setting, its utilization in the intraoperative
care of surgical patients is limited53. In light of the benefits that
have been demonstrated from using telemedicine in the ICU
setting, we believe that the implementation of such a system
in the operating room has the potential to elevate the general
safety and quality of perioperative care.
We have designed a multifaceted approach for the development
and institution of an Anesthesiology Control Tower (ACT)
to provide real-time intraoperative telemedicine decision
support. In the first component of our approach, we outlined
a strategy of iterative usability testing and platform modifica-
tion that allowed us to develop a high-fidelity, user-centered
system56. We intend to continue separate usability analyzes over
the course of the pilot trial in order to evaluate the key usability
elements of effectiveness, efficiency, and satisfaction57 in a more
real-world setting. Because the impact of a clinical interven-
tion is dependent on the success of the process through which
it is implemented58, we will also evaluate implementation out-
comes that are relevant to the use of the ACT in the periop-
erative setting59,60. In the second component of our approach, we
will employ large-scale data analytics, integrating perioperative
information in order to create forecasting algorithms for nega-
tive patient trajectories61. In the current manuscript, we describe
the third element of our investigation: a pilot randomized con-
trolled trial that aims to demonstrate the superiority of the ACT
in improving adherence to best care practices when compared
to enhanced usual care.
Methods and analysis
Overview of research design
The ACTFAST-3 study is a pragmatic comparative effectiveness
trial that is taking place at an academic university-affiliated
and adult tertiary care hospital in the United States that per-
forms over 19,000 surgeries a year. We plan to enroll approxi-
mately 12,000 patients over the study period, with approximately
6,000 patients in the control arm and 6,000 patients in the inter-
vention arm (Figure 1). Patients will be included with a waiver
of informed consent, as approved by the Human Research
Protection Office (protocol number 201603038), as the risk
associated with the ACT has been deemed to be minimal.
Randomization will occur at the level of individual operating
rooms on a daily basis.
The ACT will monitor all patients in both the control and
intervention operating rooms using information gathered from
the electronic medical record (EMR) and from a customized
version of a perioperative monitoring and alerting program called
AlertWatch® (Ann Arbor, MI). AlertWatch is an FDA-cleared
(KI3O4OI) system that displays integrated patient informa-
tion and alerts clinicians to physiologic derangements. It was
recently demonstrated that use of the AlertWatch software was
Page 3 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
Figure 1. Flow diagram of study population.
associated with improvements in several process measures,
although this did not translate into an effect on clinical
outcomes50. For the purposes of our intervention, the commer-
cially available AlertWatch platform was heavily modified through
usability testing56 to create a customized AlertWatch “Control
Tower” mode that is only available within the ACT (Figure 2
and Figure 3). The standard platform will remain available to
all OR clinicians during this study. The ACT will provide clini-
cians in the intervention ORs with real-time feedback based on
the available electronic resources, including AlertWatch Con-
trol Tower. Anesthesia providers in rooms assigned to the control
group will also be monitored but will not receive decision
support. Notably, the standard medical staffing models for
providing an anesthetic will not be affected with this inter-
vention, as the ACT is designed to augment decision-making,
rather than replace critical team members.
The primary outcome measures in the ACTFAST-3 pilot study
are compliance with best care practices for intraoperative core
temperature management and intraoperative blood glucose
management (Table 1). These outcomes were selected
because they are routinely and reliably tracked in the elec-
tronic medical record and optimal perioperative management of
temperature and blood glucose is known to influence clinical
outcome. We will also explore additional intraoperative process
measures in addition to surrogate outcomes (Table 2). The
incidence of intraoperative hypotension and the incidence of
postoperative renal dysfunction, atrial fibrillation, respiratory
failure and delirium will be assessed via review of the EMR.
Other postoperative complications, including intraoperative
awareness, surgical site infection, readmission, and death will be
assessed via analysis of the existing Center for Clinical Excellence
Registry, American College of Surgeons’ National Surgical
Quality Improvement Program (NSQIP) database, Society of
Thoracic Surgery (STS) database, and Systematic Assessment
and Targeted Improvement of Services Following Yearlong
Surgical Outcomes Surveys (SATISFY-SOS) database62. Outcomes
related to the usability of the ACT intervention, including
efficiency and efficacy of the software platform, will be obtained
from AlertWatch data logs. These logs will also be used to
obtain data related to the feasibility of implementing the pilot
ACT. User satisfaction will be assessed through surveys
administered to members of the anesthesia department.
Study population, randomization, and blinding
The trial will include all adult patients undergoing surgery at
two campuses of an academic university-associated hospital,
Barnes-Jewish Hospital (South Campus and Parkview Tower)
Page 4 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
Figure 2. Interface of the AlertWatch® Control Tower system. (A) AlertWatch® Control Tower Census View. This view shows summary
information for operating rooms with ongoing procedures. Physiological alerts (e.g., low blood pressure) are shown as black or red squares,
depending on the severity of the derangement, with red indicating a more severe abnormality. Checkmarks appear inside an operating room
when an alert is triggered that has been classified as actionable and requires a response on the part of the clinicians in the Control Tower (see
Figure 3). Control rooms are indicated with a “Do Not Contact” symbol. (B) AlertWatch® Control Tower Patient Display View. This deidentified
intraoperative patient display demonstrates organ-specific information individualized to each patient. Colors outlining organs indicate normal
(green), marginal (yellow) or abnormal function (red). Orange would indicate an organ system at risk due to pre-existing conditions. The left
side of the display shows patient characteristics and the case information. Lab values, if available, are listed beneath the kidneys. Alerts
generated by the AlertWatch® system are listed on the right-hand side of the display. Specific alerts, determined by the study team to be
clinically significant and actionable, trigger a checkmark to appear at the bottom left of the screen. This informs the Anesthesiology Control
Tower (ACT) clinician that an alert is present that must be addressed. Clicking on this checkmark allows clinicians in the ACT to review and
address these alerts (Figure 3).
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F1000Research 2018, 7:623 Last updated: 29 JAN 2019
Figure 3. AlertWatch® Control Tower Case Review dialogue. Clinicians in the Anesthesiology Control Tower (ACT) use the Case Review
window to address actionable Control Tower alerts, indicated by checkmarks on the Census View and the Patient Display. Within this Case
Review window, clinicians document their assessment of the significant of each alert, what action they would recommend, and, in the case of
intervention operating rooms (ORs), the reaction of the clinician in the OR to the ACT support.
Table 1. Primary outcome measures and definitions.
Measure Outcome
Intraoperative temperature
management
Proportion of patients with final
recorded intraoperative core
temperature greater than 36°C
Intraoperative blood
glucose control
Proportion of cases with blood
glucose ≥180 mg/dl upon arrival
to the post-anesthesia recovery
area
(St. Louis, MI, USA), between 7:00 AM and 4:00 PM Monday
through Friday (Figure 1). This includes a total of 48 operating
room locations. The ACT will function on days when at least
two anesthesia providers are available, one of whom must
be an attending anesthesiologist. Patients undergoing surgical
procedures with greater than 50% of the case length occurring
outside of the ACT hours will be excluded from analysis. All
patients younger than 18 will also be excluded from the study.
Patients who undergo multiple surgeries in a single hospitaliza-
tion or who have a second surgical procedure within 30 days of
their initial surgery will be analyzed according to their initial
randomization assignment. Patients returning for a second sur-
gery more than 30 days after their initial surgical encounter will
be considered as separate patients in the analysis. We will also
obtain data from a group of historical control patients for
the 6 months prior to the initiation of the ACTFAST-3
study, as part of an analysis related to potential sources of bias
and contamination.
A randomization algorithm integrated into the AlertWatch sys-
tem will direct patient group allocation on a daily basis. Due to
the nature of the intervention in this study, clinicians work-
ing in the ACT and those randomized to receive support
cannot be blinded to the intervention. To minimize any risk of
bias with variation in ACT staff availability, we have ensured
that OR-level randomization will performed each day in a 1:1
ratio. Researchers responsible for extracting data during the
course of the study will be blinded to group allocation at the
time of extraction.
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Page 6 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
Primary intervention: ACT monitoring and decision support
A multidisciplinary team of clinicians in the ACT will
remotely monitor all active operating rooms at the campus
of interest. ACT clinicians will include attending anesthesi-
ologists, anesthesiology fellows, anesthesiology residents, and
certified and student registered nurse anesthetists. Information
will be obtained in near real-time from multiple complemen-
tary sources, including the AlertWatch Control Tower software
(Figure 2) and the EMR. The clinicians in the ACT will use this
information to communicate with OR clinicians to help main-
tain compliance with intraoperative best care practices and
to assist with the detection and management of physiological
derangements35,63–66. These clinicians will evaluate all alerts
generated by the AlertWatch Control Tower notification system
(Figure 3), including alerts from both the intervention and the
control operating rooms. For ORs allocated to the intervention
arm, the ACT will deliver decision support to the primary per-
sonnel caring for the patient via text message or telephone call.
The clinician receiving the alert will determine the applicabil-
ity of the alert to the clinical situation and will choose whether
to carry out any recommendations sent by the ACT. In patients
with a persistent critical event, the ACT will offer real-time
assistance with crisis resource management.
Operating rooms assigned to the control group will undergo
the same monitoring and assessment by the ACT, but
clinicians in these ORs will not receive any contact from the
ACT. However, if clinicians staffing the ACT feel ethically
obliged to contact a room assigned to the control group due
to perceived potential for imminent and significant patient
harm, they will be able to do so. Although we anticipate that
this will be a rare occurrence, it will still be documented and
reported as part of our study outcomes.
Data collection and outcome measures
Data collection for this study will utilize multiple sources to
extract outcome measures67. All alert data generated by the Alert-
Watch Control Tower platform will be automatically logged
to a secure database, including all responses by the providers in
the ACT to individual alerts (Figure 3). Data from the periop-
erative period will be imported from Metavision® (iMDsoft,
Wakefield, Massachusetts, USA), the anesthesiology infor-
mation management software system currently in use by the
Department of Anesthesiology. In addition to capturing com-
prehensive intraoperative clinical data, Metavision® also stores
preoperative information, such as patient characteristics, clinical
and surgical history, comorbidities, and data from the
Table 2. Secondary outcome measures and definitions.
Intraoperative process measures Outcomes
Intraoperative blood pressure
management
Mean duration of time spent with Mean Arterial Pressure <60 mmHg
Temperature monitoring Proportion of procedures lasting greater than 1 hour with documented
temperature
Antibiotic dosing Proportion of procedures with appropriate administration of repeat doses of
antibiotics
Intraoperative blood glucose
management
Proportion of cases with at least one dose of insulin administered for blood
glucose greater than 180 mg/dl
Intraoperative measurement of blood glucose in patients with type 1
diabetes undergoing cases ≥1 hour in length and patients with type 2
diabetes undergoing cases ≥2 hours in length
Train of four documentation Proportion of cases with a train of four documented prior to extubation if a
nondepolarizing neuromuscular blocking agent was administered
Ventilator management Proportion of cases with median tidal volume less than 10 ml/kg ideal body
mass
Volatile anesthetic utilization Mean and standard deviation of fresh gas flow rates for cases with volatile
anesthetic use >80% of case duration
Postoperative surrogate measures Outcomes
Postoperative acute kidney injury Incidence of individual outcomes (Supplementary File 1)
Postoperative atrial fibrillation
Postoperative respiratory failure
Postoperative delirium
Intraoperative awareness
Surgical site infection
30-day readmission
30-day mortality
Page 7 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
immediate post-operative period. Of note, during the anticipated
duration of this trial, our hospital system will be transitioning
to Epic Systems software (Verona, WI, USA) for both the hos-
pital electronic health record and the anesthesiology infor-
mation management software. Postoperative data for patient
outcomes will be obtained from the inpatient EMR record
system, and from clinical registries (SATISFY-SOS, NSQIP, STS).
Primary outcome measures
The primary outcome measures in the ACTFAST-3 study are
compliance with recommendations for intraoperative core
temperature management and intraoperative blood glucose
management (Table 1). Data on primary outcomes measures will
be recorded to an SQL server.
Secondary outcome measures
Secondary intraoperative outcomes will include several process,
surrogate, clinical measures (Table 2). Intraoperative process
outcomes will include blood pressure management, compli-
ance with recommendations for repeat dosing of antibiotics and
for temperature monitoring, management of hyperglycemia,
documentation of train of four monitoring following neuromus-
cular blockade, and adherence to strategies for intraoperative
low tidal volume ventilation. Additionally, the impact of the
ACT on volatile anesthetic usage will be assessed. We will also
evaluate surrogate and clinical outcomes, specifically, the inci-
dence of postoperative acute kidney injury, postoperative atrial
fibrillation, postoperative respiratory failure, postoperative delir-
ium, intraoperative awareness, surgical site infection, 30-day
hospital readmission, and 30-day mortality. Data will be obtained
from review of electronic health records and cross-referencing
of patients in the ACTFAST study with other surgical
databases, as described above. We will also track the incidence of
provider-reported intraoperative adverse events via a review of
the departmental quality improvement database. Feasibility of
implementing the ACT will be determined in part by examining
the number of potentially staffed days versus the actual number
of staffed days. Usability outcomes will include metrics such as
the median number of alerts addressed by provider and across
time.
Data analysis
Comparisons between groups will be with parametric and non-
parametric statistical tests, as appropriate. Fisher’s exact or χ2 test
will be used to evaluate primary outcome measures with regards
to the following proportions: (i) the proportion of patients with
a last-documented intraoperative core temperature greater than
36 degrees Celsius; and (ii) the proportion of patients arriving to
the post-anesthesia care unit or ICU with a blood glucose greater
than 180 mg/dl. Contingency statistical tests will be used to com-
pare occurrence of hypothermia and hyperglycemia between
groups. Secondary outcomes will be compared between groups
using χ2 or Fisher’s exact test for categorical outcomes, and two-
sided t tests with unequal variances for comparison of means. By
convention, statistical significance will be based on a two-sided
p value <0.05. All statistical testing will performed using SAS®
version 9.4 (SAS Institute Inc., Cary, North Carolina, USA).
The small subset of rare patients in the control group whose pro-
vider may be contacted by the ACT clinicians out of concern
for a significant patient safety event will be included in the
control group in an intention-to-treat analysis. A sensitivity
analysis will also be performed with inclusion of these patients
in the intervention group. The frequency and rationale for
contacting these rooms will be reported as part of our trial results.
Once the ACT intervention is executed, we anticipate several
sources of contamination effect in the control group. There is
a high likelihood of a robust Hawthorne effect due to OR clini-
cian awareness of the ACT monitoring68,69. Also, all clinicians
in the OR will eventually be included in the intervention group,
due to the unit of randomization, and will likely become aware
of the best management practices of interest in this trial. There-
fore, even on days when they do not receive ACT support,
clinicians may change their behavior, leading to overlapping
improvements in both groups over the course of the study. Addi-
tionally, utilization of the AlertWatch software by clinicians in
the ORs may increase over time. Learning effects might mani-
fest most strongly among clinicians who staff the ACT and are
therefore sensitized to the interventions and outcomes in this
study. In order to evaluate the extent of the contamination and
Hawthorne effects, we will collect baseline data for the group
of historical controls. For categorical variables, contamina-
tion will be analyzed using logistic regression with a three-level
categorical variable representing group assignment (histori-
cal cohort, control group, or intervention group); continuous
variables will be analyzed using ANCOVA or non-parametric
ANCOVA70. Additionally, we will track which operating
rooms utilize the AlertWatch system intraoperatively, and will
plan to perform a subgroup analysis to assess the effect of the
ACT in this subset of patients. We will also perform an
analysis to ensure the integrity of the study data following our
institutional transition to the Epic electronic medical record.
Within the AlertWatch system, all alerts that are generated are
automatically logged to a secure database, as are all responses
of the ACT clinicians to these alerts (Figure 3). We will
analyze these logs to determine how clinicians in the ACT moni-
tor patients, address alerts, and interact with OR clinicians, and
how OR clinicians respond to the ACT support. This data will
allow us to explore aspects of the real-world usability of the
ACT intervention related to efficiency and effectiveness, and
will complement information gathered from qualitative usability
surveys administered to department members.
Sample size and power analysis
In this study, we plan to enroll a convenience sample of
12,000 patients over the course of the study period, based
on the staffing available for the ACT and the usual daily
surgical volume of approximately 125 cases. Power analysis
was based on the two primary outcomes defined for this study,
with the following assumptions:
i) Regarding the core-temperature outcome, we conserva-
tively assumed that only 80% of Barnes-Jewish Hospital
patients have their core temperature recorded during sur-
gery. Among patients with their temperature documented,
the target for this outcome was that the ACT intervention
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F1000Research 2018, 7:623 Last updated: 29 JAN 2019
will increase the proportion of patients whose final recorded
intraoperative temperature is above 36°C from 60% to
95%. For this calculation we assumed a standard deviation
of core temperature of 0.9 degrees Celsius for both groups,
based on an unpublished EMR audit.
ii) Regarding the primary outcome of glucose control, we
assumed that the prevalence of diabetes mellitus among
Barnes-Jewish Hospital surgical patients is about 20%,
based on our EMR data over the past 5 years. Based on
the same data, we also assumed that currently 60% of our
diabetic patients reach a blood glucose >180 mg/dl at any
point during surgery. Our goal was that the ACT interven-
tion will reduce the proportion of patients arriving to the
Post Anesthesia Care Unit (PACU) with a blood glucose
value greater than 180 mg/dl from 60% to 40%.
A statistical power calculation based on the above assumptions
was performed for each of the two primary study outcomes to
determine whether the sample size (N=12,000) allocated for
this study is adequate. The effective sample size for the study
was defined as the largest sample needed to achieve any of the
two stated outcomes. We mainly powered all targeted outcomes
to detect a difference in proportions (adjusted for contamina-
tion between the two study groups) in a completely balanced
clustered-randomized design study (24 operating rooms in each
group) using two-sided Z-test statistics. We also assumed a mini-
mum to 90% power, a significance level of 0.05, an intracluster
correlation coefficient (ICC) varying between 0.01 and 0.05 by a
small increment of 0.005, and a coefficient of variation of cluster
sizes of 0.50. Table 3 shows the required sample per operating
room as well as the overall sample needed to achieve the
study targeted outcomes. The largest sample was required for
the proportion of patients whose last recorded intraoperative
core temperature is equal to or greater than 36°C (N=11,472).
This value was sufficient for the other primary outcome.
Substudy in educational curriculum
While the primary goal of the ACTFAST-3 study is to evalu-
ate the impact of the ACT on patient care and outcomes, the
structure and environment of the ACT has allowed for the crea-
tion of a novel curriculum in perioperative medicine. The
current educational paradigm for anesthesiology residents pri-
marily focuses on the management of individual patients in
the perioperative setting. However, the substantial increase in
requirements for surgical procedures, a projected shortage of
anesthesiologists, and financial constraints in healthcare suggest
that it will eventually be infeasible for anesthesiologists to provide
the level of supervision that is currently standard in the United States
(e.g. one anesthesiologist for every one to four ORs)71. There is
currently little emphasis in anesthesiology education on process
management and multitasking and caring for multiple patients
in a complex care environment. With the support of the resi-
dency program director and departmental chair, we have revised
the residency curriculum at our institute to allow each anesthe-
sia resident to spend 2 weeks in the ACT during their final
year of residency. We plan to implement an educational cur-
riculum in perioperative telemedicine, focusing on the utiliza-
tion of healthcare system resources to optimize intraoperative
management, improve quality, and provide oversight of multiple
patients undergoing complex surgical procedures.
Adverse events and safety monitoring
We do not anticipate the occurrence of significant adverse
events during this study. However, the primary investigator and
the study team will review any adverse events identified by the
departmental quality improvement program as potentially attrib-
utable to the ACT. The occurrence of any significant adverse
events will be reported to the HRPO, and the study team and
HRPO would decide together whether to halt the trial. No formal
data-monitoring committee will used. There will be no audit of
trial conduct during the investigation, although data recorded
via the AlertWatch system will be reviewed and analyzed to
determine appropriate group allocation and inclusion in the
final analysis. No interim data analysis is planned for this
pilot trial unless unanticipated safety issues are identified.
There are no provisions for post-trial care or compensation
to patients enrolled as part of this trial, as the intervention in
the ACTFAST-3 trial involves only the addition of real-time
decision-support tools and does not change existing anesthesia
care models.
Data management
The risk of breach of confidentiality will be minimized. The
data necessary for the completion of the trial will be pro-
tected by passwords and is contained in applications that are
compliant for protected healthcare information (PHI). Alert-
Watch meets this same standard of protection. Individual clinical
Table 3. Sample size assumptions and calculations for primary outcomes.
Outcome†
Current
practice
Cluster per group(size) Target level*Intracluster
correlation
coefficient
Total
Sample
RequiredIntervention Control Intervention Control
Core temperature:
proportion
reaching 36°C
50% 24(239) 24
(239)
95% 90% 0.0375 11,472
Post- operative
Blood Glucose
≥ 180 mg/dL
60% 24(59) 24
(59)
40% 50% 0.03 2,832
†See Table 1 for full explanation of outcomes.
*High contamination effects were set to reach 67% as 2 out of 3 physicians will participate in the ACT.
Page 9 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
alerts and the ACT evaluation of these alert will be documented
using an electronic data capture tool in the AlertWatch system.
Outcomes data will be stored on one of two Washington Univer-
sity Department of Anesthesiology servers (a SQL server or a
Windows file server). Only trained employees of the Department of
Anesthesiology or Barnes Jewish Healthcare are granted access to
resources on this network. Access to the contents of this study will
be further restricted to approved personnel only, using server-level
permission access (for the SQL server), or Windows folder per-
mission settings (for the file server). It is a strict policy that PHI
cannot be saved or reviewed outside of this protected environ-
ment. Whenever possible, extracts for this project will avoid
the use of this information. Data extracts can be reconnected
to PHI using a special, non-PHI primary key, which this group
has successfully used with previous studies.
Strengths and limitations
The ACTFAST pilot study has important strengths. It is a ran-
domized clinical trial conducted in a high volume, real world
clinical setting and can be conducted efficiently, as many com-
ponents of the proposed study are incorporated into existing
infrastructures and processes at Washington University. This
includes access to existing information technology resources and
to established and ongoing registries (SATISFY-SOS, NSQIP
and STS). The data required for analysis of the primary out-
come measures are routinely recorded on every patient undergo-
ing surgery at our institution, and the databases used for analysis
of secondary surrogate and clinical outcomes also all have high
levels of data fidelity.
Randomization of anesthesiology care teams can be easily
implemented, and the process for providing feedback alerts
does not require any advanced preparation on the part of clini-
cians working in the OR. These clinicians will participate in
the ACTFAST trial in the course of their routine clinical work,
and the impact on overall workflow and workload will be mini-
mized through the testing in our first phase of the study56. We
anticipate that it will be feasible to staff the ACT during the pilot
RCT. The feasibility is enhanced by participation of a highly
committed cadre of attending anesthesiologists and all of
the residents in the anesthesiology department, as well as an
experienced team of investigators that has established a track
record of collaboration and completion of major clinical trials.
The following limitations should be considered. The Alert-
Watch software is currently available on all computers in
the OR, and in-room provider utilization of AlertWatch may
increase over the course of the study. In response, we plan to
conduct a subgroup analysis with user log-in data to ascertain
the impact of in-room software utilization, defined as docu-
mentation of intraoperative provider log-in to the AlertWatch
system. Also, the ACTFAST study will be vulnerable both to
Hawthorne and contamination effects. While we do not think
that these effects can be eliminated, we have considered
how best to account for them in the analyses. An important
constraint and possible source of bias will be that it will not be
possible to ensure blinding of OR clinicians as any communica-
tion from the ACT will inform them that their operating room
is in the intervention group on that day72. However, clinicians
outside of the OR, and the researchers responsible for extracting
data, will be blinded to group assignment.
Another potential source of bias involves the existing surgi-
cal databases that will be used during analysis (i.e. STS, NSQIP,
SATISFY-SOS). These registries themselves may be biased
according to which patients choose to participate, with indi-
vidual patients’ outcomes impacting their willingness or ability
to provide reliable information, and which patients are contacta-
ble. We have been attempting to mitigate this source of bias by
employing three modalities (e-mail, telephone and mail) to reach
patients postoperatively in one such study62. Overall, the regis-
tries have impressive response rates, and there does not appear
to be systematic bias in any of these registries based on baseline
patient characteristics. Therefore, we expect our data sources
to be robust, with minimal deficiencies.
Ethics and dissemination
This study was approved by the HRPO at Washington Univer-
sity (St. Louis, MI, USA, protocol number 201603038). This
protocol is written in compliance with the Standard Protocol
Items: Recommendations for Interventional Trials (SPIRIT)
checklist with consideration of the Consolidated Standards of
Reporting Trials (CONSORT) guidelines73,74.
If the results of the pilot ACTFAST-3 trial show benefit, the
pilot study will likely be replicated as a larger, multicenter study
for further validation that this intervention remains beneficial
and that it is feasible to institute at other centers. We also antici-
pate the expansion of the ACT into the surrounding healthcare
facilities within our hospital system. Larger trials could focus
on expanded clinical and patient-reported outcomes (e.g. death,
renal failure, delirium, duration of mechanical ventilation, inten-
sive care length of stay, post-discharge disposition, postoperative
falls, return to work, disability-free survival). The ACT infra-
structure could also be used to explore current controversies
in perioperative care by testing candidate experimental
interventions (e.g., fluid management strategies, blood trans-
fusion triggers). We envision that national implementation
of the ACT concept would occur, which would be
comparable to the path that similar programs for intensive care
units have followed.
Any significant changes to the protocol or the analysis plan
during the trial will be communicated directly to the Washing-
ton University HRPO, as well as via update of the ACTFAST-3
registration at clinicaltrials.gov (ClinicalTrials.gov Identifier:
NCT02830126). We also plan to publish any modifications
made to this protocol during dissemination of the results of the
trial. Authorship for the final trial data will be determined in
accordance with International Committee of Medical Journal
Editors (ICMJE) guidelines.
Data sharing
Data from the ACTFAST-3 trial will be made available for analy-
sis in compliance with the recommendations of the ICMJE75. For
this study, individual participant data that underlie the results of
Page 10 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
the trial will be made available after appropriate deidentifica-
tion, along with the study protocol and statistical analysis plan.
We plan to make this information accessible to researchers who
provide a methodologically appropriate proposal for the purpose
of achieving the aims of that proposal. Data will be available
beginning 9 months and ending 36 months following trial publi-
cation at a third-party website. Data requestors will need to sign
a data access agreement to gain access to trial data. Proposals
should be directed to avidanm@wustl.edu.
Conclusions
Despite aggressive efforts aimed to improve the quality of peri-
operative care, the risk of morbidity and mortality following a
major surgical procedure remains substantial. In this protocol,
we describe a pilot pragmatic, randomized, controlled trial in
intraoperative telemedicine that examines the ability of a novel
system of real-time feedback to improve adherence to periopera-
tive best care practices. We hypothesize that the implementation
of the ACT will be feasible and that it will increase clinician
compliance with clinical practice standards. The development of
the ACT, as described in this protocol, will also lay the ground-
work for a subsequent large randomized controlled trial exam-
ining the utility of the ACT in improving patient outcomes
following surgical procedures.
The findings from the trial will be disseminated in the form
of posters and oral presentations at scientific conferences, as
well as publications in peer-reviewed journals. Updates and
results of the study will be available at https://clinicaltrials.gov/
ct2/show/NCT02830126.
Data availability
No data is associated with this study.
Competing interests
No competing interests were disclosed.
Grant information
The ACTFAST-3 project, including this protocol, has been funded
by a grant from the Agency for Healthcare Research and Quality
(R21 HS24581-01).
The funders had no role in study design, data collection and
analysis, decision to publish, or preparation of the manuscript.
Acknowledgements
Members of the ACTFAST study group are as follows: Stephen
Gregory, Teresa M. Murray-Torres, Bradley A. Fritz, Arbi Ben
Abdallah, Daniel L. Helsten, Troy S. Wildes, Anshuman Sharma,
Yixin Chen*, Mary Politi*, Alex Kronzer*, Bernadette Henrichs*,
Brian A. Torres*, Sherry McKinnon*, Thaddeus Budelier*,
Walter Boyle*, Bruce Hall*, Benjamin Kozower*, Sachin
Kheterpal*, Michael S. Avidan
*Contributor
References
Supplementary material
Supplementary File 1: Definitions of postoperative surrogate measures for the ACTFAST-3 clinical trial.
Click here to access the data.
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F1000Research 2018, 7:623 Last updated: 29 JAN 2019
Open Peer Review
Current Referee Status:
Version 1
29 June 2018Referee Report
https://doi.org/10.5256/f1000research.16217.r35259
, Morten H. Bestle Christian Ari Dalby Sørensen
DepartmentofAnaesthesiologyandIntensiveCare,NordsjællandsHospital-Hillerød,Universityof
Copenhagen,Hillerød,Denmark
Thankyoufortheopportunitytoreviewthispaper.
Inmanuscripttheauthorsdescribeapilotrandomizedcontrolledtrialthataimstodemonstratethe
implementationandutilityoftheanesthesiologycontroltower(ACT)inimprovingadherencetobestcare
practiceswhencomparedtoenhancedusualcare.Theauthorsproposetorandomize12,000patients
overthestudyperiod,withapproximately6,000patientsinthecontrolarmand6,000patientsinthe
interventionarm.Cliniciansgroupedintheinterventionarmwillbeprovidedwithreal-timefeedback
basedontheavailableelectronicresources.Primaryandsecondaryoutcomeswillbecomparedtothe
controlgroup.
Page3paragraph2:Theauthorsstatethatsomeoftherisksofperioperativeadverseeventsmaybea
manifestationofeitherunderlyingpatientpathologyorthecomplexityofthesurgicalprocedureitself.The
authorscouldconsiderelaboratingthatstatementinmoredetails.Howbigistheproportionofunderlying
patientpathologyandcomplexsurgicalprocedures?
Page3paragraph2:Theauthorsstatethatpriorstudieshavedocumentedthatdeviationfrom
evidence-basedstandardsofcareiscommon,andthatdeviationresultsinpoorerpatientoutcomes.
Whichoutcomeshasbeenthefocusofpriorstudies?
Page3paragraph8:Whyhaveyouchosentheseoutcomestobetheprimaryoutcomes?
Page4paragraph2:Theauthorsmentionsthatonlypatientsundergoingsurgerybetween7:00AMand
4:00PMMondaythroughFridaywillbeincluded.Haveyouconsideredtherecouldbeadifference
betweenelectiveandacutesurgery.Arecliniciansmorepronetofollowclinicalguidelinesatdaytime
comparedtonighttime?
Is the rationale for, and objectives of, the study clearly described?
Yes
Is the study design appropriate for the research question?
Yes
Are sufficient details of the methods provided to allow replication by others?
Page 14 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
Are sufficient details of the methods provided to allow replication by others?
Yes
Are the datasets clearly presented in a useable and accessible format?
Yes
Nocompetinginterestsweredisclosed.Competing Interests:
Referee Expertise:Clinicalresearchinintensivecaremedicine
We have read this submission. We believe that we have an appropriate level of expertise to
confirm that it is of an acceptable scientific standard.
AuthorResponse16Jul2018
,WashingtonUniversityinSaintLouis,USATeresa Murray-Torres
Thankyoufortakingthetimetoreviewourmanuscriptandprovidefeedback.Wehavesubmitteda
revisedversionofourprotocoladdressingthereviewer'scomments.Ourchangesinresponseto
therefereeareasfollows:
Page3paragraph2:Theauthorsstatethatsomeoftherisksofperioperativeadverseeventsmay
beamanifestationofeitherunderlyingpatientpathologyorthecomplexityofthesurgical
procedureitself.Theauthorscouldconsiderelaboratingthatstatementinmoredetails.Howbigis
theproportionofunderlyingpatientpathologyandcomplexsurgicalprocedures?
We have expanded this sentence to highlight the development of complex surgical risk calculators
to evaluate perioperative risk using both patient pathology and the surgical procedure.
Page3paragraph2:Theauthorsstatethatpriorstudieshavedocumentedthatdeviationfrom
evidence-basedstandardsofcareiscommon,andthatdeviationresultsinpoorerpatient
outcomes.Whichoutcomeshasbeenthefocusofpriorstudies?
We have updated this section to highlight that deviation from evidence-based standards of care is
ubiquitous across a variety of health care settings and may be associated with an increase in a
number of adverse patient outcomes, including surgical site infection, pneumonia, and mortality.
Page3paragraph8:Whyhaveyouchosentheseoutcomestobetheprimaryoutcomes?
These outcomes were selected because they are routinely and reliably tracked in the electronic
medical record and optimal perioperative management of temperature and blood glucose is known
to influence clinical outcome. We have added this information to the manuscript.
Page4paragraph2:Theauthorsmentionsthatonlypatientsundergoingsurgerybetween7:00AM
and4:00PMMondaythroughFridaywillbeincluded.Haveyouconsideredtherecouldbea
differencebetweenelectiveandacutesurgery.Arecliniciansmorepronetofollowclinical
guidelinesatdaytimecomparedtonighttime?
We do recognize that this is a limitation of our current study, but we have attempted to account for
any variation in guideline compliance during off-hours by equally applying time exclusion criteria to
both our control and intervention ORs. Additionally, we have designated that patients having a
Page 15 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
both our control and intervention ORs. Additionally, we have designated that patients having a
surgical procedure with >50% of the operative time occurring outside of ACT hours will be
excluded from analysis. Evaluating variations in compliance with perioperative guidelines outside
of normal working hours is an interesting proposal, and may be considered as part of a future
expansion of the ACT concept.
N/A.Competing Interests:
05 June 2018Referee Report
https://doi.org/10.5256/f1000research.16217.r34272
, Leif Saager Michael Burns
UniversityofMichigan,AnnArbor,MI,USA
Thankyouverymuchfortheopportunitytoreviewthisinnovativeandtimelysubmission.
Themanuscriptiseloquentlywrittenandthestudyprotocolcomprehensivelydescribed;ourcomments
arethereforefewandminor.
Inthisarticletheauthorspresentastudyprotocolforarandomizedcontroltrialinthefieldof
intraoperativeclinicaldecisionsupport.Theauthorsproposetorandomize12,000patientstoeither
intraoperativeclinicaldecisionsupportorenhancedintraoperativeclinicaldecisionsupportbyutilizinga
novelAnesthesiaControlTower(ACT)concept.Throughoutthearticletheauthorsthoroughlypresent
theirpragmaticstudywithadequatedetailsandathoughtfulpatient-centricapproach.Theiridentification
ofthecomplexityoftheanestheticpracticeandcognitiverequirementsiswellfounded,andtheir
referencetotheICUremotemonitoringsystemsisestablished.
Onpage3,paragraph1,theauthorsstatethat“10-40%ofpatientswillexperiencesomesortof
postoperativesurgicalcomplication”.Thecitationsmostlyrefertoelderlyand/orhigh-risksurgical
patients.Perhapstheauthorscouldconsideraddingareferenceforageneralsurgicalpopulation.
Onpage4,theauthorsstatetheACTwillfunctiononlyondayswithatleast2anesthesiaproviders
available.CouldthisintroducebiasintothestudyasonORdayswithhighvolume,orcomplexcases
requiringlowerstaffingratios,theavailabilityofstafffortheACTwouldbelesslikely?
Onpage7,paragraph2,theauthorsstateananticipatedtransitioninelectronichealthrecords.Inour
experience,implementationofanewrecordkeepingsystemcanincreasecognitiveload,documentation
errors,andlagsindataacquisition.Ourconcernwouldbeapossiblecompromiseofstudydata.Dothe
authorshaveacontingency/transitionplanavailable?
Onpage8,theauthorsbasethesamplesizecalculationoncoretemperaturemeasurements.Therestof
themanuscriptislessspecificastothesiteoftemperaturemeasurement.Willonlycoretemperaturesbe
utilizedinthisstudy?
Onpage9,paragraph2,theauthorsproposeaninnovativeeducationalcurriculum.Wouldtheauthors
considerprovidingmoredetailontheimplementationandevaluationofthiscomponent?
InTable2,theauthorsdescribesecondaryoutcomes.Woulditbepossibletoaddanappendixtoprovide
Page 16 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
InTable2,theauthorsdescribesecondaryoutcomes.Woulditbepossibletoaddanappendixtoprovide
definitionsfortheseparametersorreferenceNSQIP/STSdocumentsasthesourceofthesedefinitions?
Is the rationale for, and objectives of, the study clearly described?
Yes
Is the study design appropriate for the research question?
Yes
Are sufficient details of the methods provided to allow replication by others?
Yes
Are the datasets clearly presented in a useable and accessible format?
Yes
Nocompetinginterestsweredisclosed.Competing Interests:
We have read this submission. We believe that we have an appropriate level of expertise to
confirm that it is of an acceptable scientific standard.
AuthorResponse16Jul2018
,WashingtonUniversityinSaintLouis,USATeresa Murray-Torres
Thankyoufortakingthetimetoreviewourmanuscriptandprovidefeedback.Wehavesubmitteda
revisedversionofourprotocoladdressingthereviewer'scomments.Ourchangesinresponseto
therefereeareasfollows:
Onpage3,paragraph1,theauthorsstatethat“10-40%ofpatientswillexperiencesomesortof
postoperativesurgicalcomplication”.Thecitationsmostlyrefertoelderlyand/orhigh-risksurgical
patients.Perhapstheauthorscouldconsideraddingareferenceforageneralsurgicalpopulation.
We have updated this statistic to “5-40%,” including a reference examining NSQIP complication
rates in patients undergoing orthopedic surgical procedures, primarily elective total joint
procedures.
Onpage4,theauthorsstatetheACTwillfunctiononlyondayswithatleast2anesthesiaproviders
available.CouldthisintroducebiasintothestudyasonORdayswithhighvolume,orcomplex
casesrequiringlowerstaffingratios,theavailabilityofstafffortheACTwouldbelesslikely?
We have attempted to minimize the risk of bias secondary to ACT staff availability by performing
OR randomization each day with a 1:1 allocation. We anticipate that this will allow for any staffing
variations to equally affect both the intervention and control groups to minimize bias. We have
updated the manuscript to specifically address this point.
Onpage7,paragraph2,theauthorsstateananticipatedtransitioninelectronichealthrecords.In
ourexperience,implementationofanewrecordkeepingsystemcanincreasecognitiveload,
documentationerrors,andlagsindataacquisition.Ourconcernwouldbeapossiblecompromise
ofstudydata.Dotheauthorshaveacontingency/transitionplanavailable?
Fortunately, the data required to evaluate the primary and secondary outcomes in this study is
Page 17 of 18
F1000Research 2018, 7:623 Last updated: 29 JAN 2019
Fortunately, the data required to evaluate the primary and secondary outcomes in this study is
electronically populated from patient monitoring data (temperature) or autopopulated into the
electronic medical record following measurement (glucose). Although we do not anticipate any
significant difficulties with ensuring the integrity of the study data, we do plan to perform an
analysis to confirm that there has been no significant compromise of study data.
Onpage8,theauthorsbasethesamplesizecalculationoncoretemperaturemeasurements.The
restofthemanuscriptislessspecificastothesiteoftemperaturemeasurement.Willonlycore
temperaturesbeutilizedinthisstudy?
Yes, we plan to only utilize core temperature in our analysis of temperature as a primary outcome.
This has been updated in the manuscript.
Onpage9,paragraph2,theauthorsproposeaninnovativeeducationalcurriculum.Wouldthe
authorsconsiderprovidingmoredetailontheimplementationandevaluationofthiscomponent?
At present time, we are still actively developing the educational curriculum for residents rotating
through the ACT. The specific endpoints for the protocol assessing this substudy are not yet
defined.
InTable2,theauthorsdescribesecondaryoutcomes.Woulditbepossibletoaddanappendixto
providedefinitionsfortheseparametersorreferenceNSQIP/STSdocumentsasthesourceof
thesedefinitions?
We have added an appendix to define the postoperative surrogate outcomes for the study.
Nocompetinginterestsweredisclosed.Competing Interests:
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Page 18 of 18
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