Implementation of Nudges to Promote Utilization of Low Tidal Volume Ventilation (INPUT) Study
Phase: NA
Conditions: ARDS, Critical Illness, Acute Respiratory Distress Syndrome, Acute Respiratory Failure
Sponsor: University of Pennsylvania

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Implementation of Nudges to Promote Utilization of low Tidal volume ventilation (INPUT) Study 
 
Sponsor 
NATIONAL HEART, LUNG, AND BLOOD 
INSTITUTE 
Protocol Number 
833400 
Principal Investigator 
Meeta Prasad Kerlin MD, MSCE 
Clinical Trials.gov Number 
NCT04663802 
Version Date: 
07/20/2023 
 
 

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Protocol Summary 
Title 
Implementation of Nudges to Promote Utilization of low Tidal volume 
ventilation (INPUT) Study  
Short Title 
INPUT Study 
Principal Investigator 
Meeta Prasad Kerlin MD, MSCE 
Co-Investigators 
Rinad Beidas PhD 
Scott Halpern MD, PhD 
Barry Fuchs MD 
Mark Mikkelsen MD, MSCE 
Dylan Small PhD 
Design 
Pragmatic, prospective stepped-wedge cluster randomized trial 
Objectives 
Our primary objective is to compare simple, low-cost, scalable strategies 
grounded in behavioral economic theory to (a) increase utilization of 
evidence-based lung-protective ventilation (LPV) to patient who undergo 
mechanical ventilation (MV), (b) gauge the process-oriented and clinical 
benefits of targeted vs. non-targeted approaches to changing behavior, (c) 
explore how clinician and environmental contextual factors affect LPV 
utilization, and (d) determine how patient factors such as type and severity 
of disease affect both LPV utilization and its associated outcomes. 
Interventions 
• Strategy A:  Default order set for MV 
With the default order set strategy, a physician will see a different 
order panel to order mechanical ventilation settings than the current 
usual state. In this intervention order panel, the ventilation mode will 
be pre-selected to be assist-control, volume-cycled; and the tidal 
volume with be pre-populated via an automatic calculation of 6 cc/kg 
of the patient’s ideal body weight (as determined by each patient’s 
height and gender, which are entered into the EHR during every 
hospital admission). The physician will have the option to opt out of 
any of the pre-specified settings with one click. 
 
• Strategy B:  Physician-targeted accountable justification of MV 
orders 
In this strategy, the order panel will remain nearly identical to the 
current state, with no pre-specified settings. However, if a physician 
enters an order for a tidal volume that is greater than 6.5 cc/kg ideal 
body weight, the physician will be required to enter a reason for 
choosing a setting inconsistent with LPV into a free text box. This box 
will instruct them to provide a reason for deviation from LPV settings 
and would inform them that their response will be maintained in the 

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medical record. The physician will not be able to proceed with 
entering the MV order until after a response is entered. 
 
• Strategy C:  RT- targeted accountable justification of initial MV 
settings 
In this strategy, if an RT enters a set tidal volume value greater than 
6.5 cc/kg into the flowsheet, he/she will be receive a pop-up window 
that requests that the RT enter an explicit rationale into a free-text 
box for deviating from LPV settings, similar to the physician-targeted 
accountable justification strategy. 
Study Duration  
27-month trial period, with a minimum 6-month follow-up without 
intervention monitoring 
Study Sites 
12 ICUs within 5 hospitals of the University of Pennsylvania Health System 
(UPHS) 
Sample Size 
 
Estimated 9,900 episodes of MV and 100 clinicians 
Patient Eligibility 
For the purpose of the trial, the analytic sample will be limited to the 
following:  
-Aged 18 and over; AND 
-Undergoing mechanical ventilation 
Patients eligible according to the criteria above will be EXCLUDED if: 
-The episode of MV lasts less than 12 hours, because we believe that the 
evidence-based practice may not apply to these patients nor alter their 
outcomes. 
-The patient is on minimal settings for the entirety of MV, defined as a 
spontaneous mode (e.g., pressure support ventilation) with pressure support 
<10 cmH2O, AND PEEP <8 cmH20, AND FiO2 <50%, because the clinical 
significance of spontaneous tidal volumes is unknown and low tidal volumes 
may not be beneficial or desirable. 
-Goals of care are documented as comfort measures only (as identified 
through their “code status” field in the EHR) during the first 72 hours during 
episode of MV, because mechanical ventilation is managed differently during 
care focused exclusively on comfort and low tidal volume ventilation may not 
be appropriate, nor would it likely influence clinical outcomes. 
-There is no height documented in the EHR at the time of initiation of MV, 
because we will be unable to estimate ideal body weight, a necessary 
parameter to calculate the primary outcome, and because they will not 
receive the interventions. 
-The height documented is less than 4 feet, because the formula for ideal 
body weight is not valid below this height. 
 

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Outcomes 
Primary outcome variable: Fidelity to low tidal volume ventilation, defined 
as percentage of time in the first 72 hours of mechanical ventilation that a 
patient is exposed to tidal volume >6.5 cc/kg ideal body weight 
Major secondary outcome variables:  
• MV metrics:  Durations of exposure to tidal volume >8 cc/kg and 
>10 cc/kg ideal body weight; initial tidal volume administered; 
duration of time exposed to plateau pressure (Pplat)>30 cmH20  
• Clinical outcomes: in-hospital mortality, hospital discharge 
disposition, duration of MV, ICU and hospital length-of-stay 
• Potential adverse effects of LPV: total cumulative doses of sedative 
medications during and after mechanical ventilation, total number 
of days with acute brain dysfunction during and after mechanical 
ventilation 
Analysis of Primary 
Outcome 
• The primary analysis will be performed at the level of the episode 
of mechanical ventilation. It will follow a modified intention-to-
treat approach, such that all patients meeting criteria and exposed 
to or eligible to be exposed to one of the order panel interventions 
(which will fire for a new mechanical ventilation order during the 
period of ICU admission) will be randomized and evaluated in the 
analysis 
• Primary analyses will utilize a mixed effects regression models with 
random effects for ICUs and fixed effects for time to account for the 
stepped-wedge cluster randomized design, and risk adjustment for 
several ICU and patient factors to account for potential imbalance 
due to the design. 
Study Oversight 
• Trial oversight will be conducted by the University of Pennsylvania 
(Penn) Institutional Review Board (IRB00000039). 
• A Data and Safety Monitoring Board (DSMB) will be convened to review 
the trial protocol and any safety concerns that may arise. 
• An expert critical care clinician (attending physician, fellow physician, 
or advanced practice provider) who has been trained by PI Kerlin, in 
conjunction with project manager Tran, will be directly responsible for 
identifying and reporting all serious adverse events to the DSMB and 
the IRB.   
• PI Kerlin will also report protocol deviations/violations and 
unanticipated events to the Penn IRB and DSMB.  
• Unanticipated adverse events that occur at any participating hospitals 
will be reported by ICU leadership to Co-I Fuchs. 
 
 
 
 

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Table of Contents 
1. Background and Rationale ................................................................................................................... 7 
1.1 Background and rationale for the INPUT study ........................................................................... 7 
2. Objectives ............................................................................................................................................ 7 
2.1 Primary objective ....................................................................................................................... 7 
3. Study Design ........................................................................................................................................ 7 
3.1  Overview ................................................................................................................................... 7 
3.2  Duration .................................................................................................................................... 8 
3.3  Study Setting ............................................................................................................................. 8 
3.4  Eligibility Criteria ....................................................................................................................... 8 
3.5 Randomization ........................................................................................................................... 9 
3.6 Blinding to study group assignment ............................................................................................ 9 
3.7  Interventions ........................................................................................................................... 10 
3.8  Data Collection ........................................................................................................................ 10 
3.9 Outcomes................................................................................................................................. 11 
4. Trial Implementation ......................................................................................................................... 12 
4.1  Participant recruitment and enrollment .................................................................................. 12 
4.2  Waiver of Informed Consent.................................................................................................... 12 
4.3  Waiver of HIPAA Authorization ................................................................................................ 13 
5. Data Management ............................................................................................................................. 14 
5.1  Data Confidentiality ................................................................................................................. 14 
5.2  Subject Confidentiality ............................................................................................................ 15 
5.3  Subject Privacy ........................................................................................................................ 15 
6. Human Subjects Protection ................................................................................................................ 15 
6.1  Risk / Benefit Assessment ........................................................................................................ 15 
6.2  Protective Measures ................................................................................................................ 16 
7. 
Sample Size and Analysis Plan ........................................................................................................ 17 
7.1  Sample Size ............................................................................................................................. 17 
7.2 Statistical Analysis .................................................................................................................... 18 
7.3.  Approach to Missing Data ....................................................................................................... 20 
7.4. 
Statistical Power Calculations............................................................................................ 21 
8. 
Data and Safety Monitoring ........................................................................................................... 21 
8.1. 
Adverse Events and Unanticipated Problems .................................................................... 21 
8.2.   
Data and Safety Monitoring Board .................................................................................... 21 
8.3. 
Interim Analyses ............................................................................................................... 22 

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8.4. 
Institutional Review Board (IRB) ........................................................................................ 22 
8.5. 
Clinicaltrials.gov ................................................................................................................ 23 
9. 
References ..................................................................................................................................... 24 
 
 
 

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1. Background and Rationale 
1.1 Background and rationale for the INPUT study 
Of the million Americans who undergo invasive mechanical ventilation (MV) annually within intensive 
care units (ICUs),1-3 30-35% die in the hospital,1,4 and survivors commonly have long-term cognitive, 
emotional and physical impairments.5,6 Although potentially life-saving, MV can also injure the lungs.7 
Strategies of “lung-protective ventilation” (LPV) aim to minimize harm by delivering low tidal volumes 
(the amount of air per breath delivered by the ventilator) and limiting the artificial pressures in the 
lungs. LPV was first proven effective in patients with acute respiratory distress syndrome (ARDS), a 
severe form of respiratory failure associated with pneumonia, sepsis, and other common illnesses.8 A 
multicenter randomized trial published in 2000 demonstrated an absolute mortality reduction of 10%, 
shortened duration of MV, and reduced organ failure rates.9 These findings have since been replicated 
and incorporated into international guidelines.10 However, over fifteen years later, more than one-third 
of ARDS patients overall, and up to 81% in some ICUs, do not receive LPV.11,12  
 
Multiple studies across diverse ICUs have consistently identified two key barriers to LPV utilization: 
limited knowledge about LPV,13-17 and tendencies to prescribe LPV only when ARDS is definitively 
diagnosed,14,15 in part due to theoretical concerns about potential harms of LPV.15 However, definitive 
diagnosis of ARDS is challenging.18,19 And recent evidence suggests that (1) concern for harm among 
patients without ARDS is likely unwarranted,20,21 and (2) LPV may in fact reduce lung injury and mortality 
even among patients without ARDS.22 
 2. Objectives 
2.1 Primary objective 
The study’s overall objective is to compare simple, low-cost, scalable strategies grounded in behavioral 
economic theory to (a) increase utilization of evidence-based LPV for MV patients, (b) gauge the 
process-oriented and clinical benefits of targeted vs. non-targeted approaches to changing behavior, (c) 
explore how clinician and environmental contextual factors affect LPV utilization, and (d) determine how 
patient factors such as type and severity of disease affect both LPV utilization and its associated 
outcomes. 
3. Study Design 
 
3.1  Overview 
We will perform a stepped-wedge, cluster randomized trial of three EHR-based implementation 
strategies designed to increase utilization of LPV among MV patients. 
 
During the trial, study ICUs, which at baseline use an EHR-based algorithm to identify patients with ARDS 
and prompt physicians and respiratory therapists (RTs) to employ LPV, will sequentially add two of three 
EHR-based implementation strategies to further promote LPV utilization among all MV patients. ICUs 
will be randomly assigned to first receive one of two physician-directed strategies:  either a default 
order set (Strategy A) or physician-targeted accountable justification strategy (Strategy B). ICUs will be 
randomly assigned to one of six wedges, thereby determining the date on which they adopt their 
assigned EHR-based strategy (Figure 3). The first wedge will begin in the fourth month of the trial phase, 
so that all hospitals will contribute a minimum of 3 months of data prior to having adopted the 

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implementation strategy. Six months after adoption, all 
ICUs will add on an RT-targeted accountable 
justification strategy (Strategy C). By the end of the 27-
month study period, all hospitals will have been utilizing 
two strategies in combination for at least 3 months. This 
design enables comparisons of outcomes before and 
after implementation within ICUs, as well as at a given 
point in time among ICUs which will have been 
randomly assigned to different strategies.23 
 
For the objectives of this study, the stepped-wedge 
cluster randomized design is preferred to designs that 
randomize individual patients and to parallel or cross-
over cluster designs. Patient level randomization is 
problematic because the intervention entails a systems 
level modification of clinician behavior, rather than a 
test of a simple drug or procedure. Individual patient 
randomization would require that clinicians adhere to 
three very different approaches, reducing adherence 
and likely resulting in contamination across arms. 
Randomizing patients within entire intensive care units 
to receive the intervention decreases the risks. 
 3.2  Duration 
The study will have a control period, an intervention period, and an observational period. All ICUs will 
contribute a minimum of 3 months of baseline data prior to intervention and utilize two strategies in 
combination for a minimum of 3 months. ICUs will be assigned to intervention phase based on the 
randomization strategy described in detail below. After the intervention period, all study ICUs will 
contribute at least 6 months of post-intervention data. The total study intervention period will be 27 
months and entire study duration will be a minimum of 33 months. 
 
3.3  Study Setting 
We will test the intervention during the course of providing usual care among a large and diverse 
population of patients admitted to 12 ICUs across 5 hospitals within UPHS. 
 
3.4  Eligibility Criteria 
The implementation strategies will be rolled out as a new standard of care for all mechanically 
ventilated patients admitted to 12 intensive care units. For the purpose of the trial, patients will be 
considered initially eligible if they are:  
-Aged 18 and over; AND 
-Undergoing mechanical ventilation 
 
Any patients meeting the eligibility criteria above will be excluded from the analysis for the following 
reasons: 
-The episode of MV lasts less than 12 hours, because we believe that the evidence supporting low tidal 
volume ventilation does not apply to patients who undergo very short periods of MV, nor does it alter 
their outcomes. 

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-The patient is on minimal settings for the entirety of the first 72 hours of MV, defined as a spontaneous 
mode (e.g., pressure support ventilation) with pressure support <10 cmH2O, AND PEEP <8 cmH20, AND 
FiO2 <50%, because the clinical significance of spontaneous tidal volumes is unknown and low tidal 
volumes may not be beneficial or desirable. 
-Goals of care are documented as comfort measures only during the first 72 hours during the episode of 
MV, because mechanical ventilation is managed differently during care focused exclusively on comfort 
and low tidal volume ventilation may not be appropriate, nor would it be expected to influence clinical 
outcomes. 
-There is no height documented in the EHR at the time of initiation of MV, because we will be unable to 
estimate ideal body weight, a necessary parameter to calculate the primary outcome, and because they 
will not receive the interventions. 
-The height documented is less than 4 feet, because the formula for ideal body weight is not valid below 
this height. 
 
Clinicians will be eligible for inclusion in semi-structured interviews if they participate in any shift to 
provide bedside care and interact with one of the three interventions during intervention phase of any 
study ICU. 
 
3.5 Randomization 
All ICUs will receive one of two physician-directed interventions, followed by the RT-directed 
intervention, as described above.  The study design includes randomization at the ICU level.  
 
12 ICUs across five UPHS hospitals will be randomized into six 2-ICU clusters by computerized random-
number generation using R random number generator function. To form clusters with balanced patient 
volume and primary outcome baseline value, ICUs will be matched in pairs based on: 1) ICU patient 
volume (ICUs will be categorized as large or small based on whether their annual patient volume is 
above or below the median) and 2) the baseline value of the primary outcome (ICUs will be categorized 
as high or low rates of adherence to LPV based on whether their median rate is above or below the 
median). The six ICU clusters will then be randomly assigned to receive either Strategy A or B and then 
randomly assigned to represent wedges 1 through 6, with each wedge transitioning to the intervention 
phase in sequential fashion. 
 
3.6 Blinding to study group assignment 
The study PI and data analyst will remain blinded to all study group assignments throughout the trial 
and during the analyses.  The data manager and project manager will be unblinded to study group 
assignments, in order to facilitate data processing and adverse event monitoring and communication 
with the Data Safety and Monitoring Board. An expert critical care clinician (attending physician, fellow 
physician, or advanced practice provider) other than the PI will be un-blinded to study group assignment 
only as needed in order to perform detailed reviews of any occurrences of potential serious adverse 
events (as further detailed below).   They will communicate any relevant adverse events to the project 
manager, who will in turn communicate directly with the DSMB.  At the end of the trial, the data 
manager will assign variables to indicate the study group assignment and time that will allow the data 
analyst to maintain blinding. 
 
Some of the co-investigators are attending physicians in some of the study ICUs and will potentially be 
on-service during the trial period. As attending physicians, they typically have no interaction with placing 

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or reviewing orders in the EHR; therefore, it is unlikely that they will unwittingly be unblinded through 
their clinical responsibilities. 
 
 
3.7  Interventions 
ICUs, which have individual practices for identifying eligible patients and administering LPV, will 
sequentially implement two of three EHR-based strategies to further promote LPV utilization among all 
MV patients. Strategies will be rolled out via a stepped-wedge design. Study ICUs will be randomly 
assigned to first receive either a default order set (Strategy A) or physician-targeted accountable 
justification strategy (Strategy B). Six months after Strategies A and B are implemented, ICUs will add 
on an RT-targeted accountable justification strategy (Strategy C). 
 
Strategy A:  Default order set for MV 
With the default order set strategy, a physician will see a different order panel to order mechanical 
ventilation settings than the current usual state. In this intervention order panel, the ventilation mode 
will be pre-selected to be assist-control, volume-cycled; and the tidal volume with be pre-populated 
via an automatic calculation of 6 cc/kg of the patient’s ideal body weight (as determined by each 
patient’s height and sex, which are entered into the EHR during every hospital admission). The 
physician will have the option to opt out of any of the pre-specified settings with one click. 
 
Strategy B:  Physician-targeted accountable justification of MV orders 
In this strategy, the order panel will remain nearly identical to the current state, with no pre-specified 
settings. However, if a physician enters an order for a set tidal volume that is greater than 6.5 cc/kg 
ideal body weight, the physician will be required to enter a reason for choosing a setting inconsistent 
with LPV into a free text box. This box would instruct them to provide a reason for deviation from LPV 
settings and will inform them that their response will be maintained in the medical record. The 
physician will not be able to proceed with entering the MV order until after a response is entered. 
 
Strategy C:  RT- targeted accountable justification of initial MV settings 
In this strategy, if an RT enters a set tidal volume value greater than 6.5 cc/kg into the flowsheet, 
he/she will receive a prompt to enter an explicit reason for deviating from LPV settings, similar to the 
physician-targeted accountable justification strategy. 
 
After completion of the trial intervention period (27 months in total) we will continue to collect patient 
data from study ICUs regarding adherence to lung-protective ventilation, use of the implementation 
strategies, and outcomes, in order to measure sustainment for at least 6 months after the intervention 
period ends. During this period, the study team will have no interactions with the clinical teams or 
leadership of the ICU, and no research-related changes will be made to the EHR. 
3.8  Data Collection 
All research patient data for this pragmatic clinical trial will be captured electronically via the UPHS EHR. 
Thus, consistent with the goals of a pragmatic trial, there are no research personnel located onsite at 
each study hospital. Instead, outcomes data will be restricted to data elements that are routinely 
collected in the course of providing routine clinical care and extracted from the UPHS EHR. 
This study also seeks to understand how the implementation strategies function in the context of 
different clinician and environmental factors, including additional barriers and facilitators of LPV 

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utilization. During the two months after the implementation strategy rolls out in each ICU, we will 
perform semi-structured interviews of all physicians and RTs who staff study ICUs. All interviews will be 
completed by a single research coordinator, who will be trained in the conduct of semi-structured 
interviews. The interviews follow a guide and begin with neutral, open-ended questions, followed by 
questions that arise from clinicians’ responses, with the interviewer pursuing themes, probing for 
further details, and seeking clarification and elaboration when appropriate. All interviews will be audio-
recorded with the participants’ consent and professionally transcribed. No identifiable information will 
intentionally be collected but may be recorded during the interview. Any identifiable information in 
interviews will be removed in transcription. 
 
3.9 Outcomes 
3.9.1  Primary outcome variable(s) 
The primary outcome variables will be (1) fidelity to LPV, measured by the percentage of time in the first 
72 hours of mechanical ventilation that a patient is exposed to tidal volume >6.5 cc/kg ideal body weight 
and (2) sustainability, measured as the percentage of time in the first 72 hours of mechanical ventilation 
that a patient is exposed to tidal volume >6.5 cc/kg ideal body weight among MV patients each month 
during the sustainment period, at least 6 months after the intervention period ends. 
 
3.9.2  Secondary outcome variable(s) 
We will include additional measures of LPV as secondary implementation outcome measures:  
- 
Durations of exposure to tidal volume >8 cc/kg ideal body weight  
- 
Duration of exposure to tidal volume >10 cc/kg ideal body weight 
- 
Initial tidal volume administered 
- 
Initial plateau pressure (Pplat) 
We will also evaluate the following clinical outcomes:   
- 
In-hospital mortality 
- 
Hospital discharge disposition 
- 
Duration of MV 
- 
ICU length-of-stay 
- 
Hospital length of stay 
We will evaluate the potential adverse effect of excessive sedation with LPV using the following 
additional secondary outcome measures:   
- 
Early deep sedation, defined as the proportion of time during the first 72 hours of mechanical 
ventilation that patients were alive, in the ICU, and with a RASS -3 to -5 
- 
Average sedation intensity within the first 72 hours, defined as the average RASS value, 
weighted by duration of time at that value 
- 
Deep sedation for the entirety of the first 72 hours of mechanical ventilation (binary) 

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4. Trial Implementation 
 
4.1  Participant recruitment and enrollment 
All patients admitted to the study ICUs who meet eligibility criteria specified above during the 27-month 
interventional phase will be enrolled in the study and included in the interventions. Subsequently, all 
patients meeting the same criteria during the 6-month observational period will be included in the 
second, observational phase of the study. All patients will be identified through the electronic health 
record. 
 
We will identify clinicians eligible for participating in interviews during the intervention roll-out periods 
by building EHR based reports that will generate lists of clinicians who interact with study interventions 
within all study ICUs. We will recruit clinician participants by sending an email describing the study, 
explaining that their involvement will require a 15- to 30-minute interview either by telephone or on site 
at the ICU. Conservatively, we anticipate that we will be able to complete 6 - 8 clinician interviews per 
wedge over the study intervention period. We will purposively sample and recruit clinician participants 
to ensure representation of the diverse professional backgrounds and views of the entire population of 
clinicians in those ICUs. 
 
4.2  Waiver of Informed Consent 
The INPUT study will be conducted under a waiver of the requirement for informed consent based on 
the following criteria set forth by the Federal Policy for the Protection of Human Subjects (the “Common 
Rule”): 
1.   The research involves no more than minimal risk to subjects. 
2.   The waiver will not adversely affect the rights and welfare of the subjects. 
3.   To the extent possible, the subjects will be provided with pertinent information after 
participating in the trial. 
4.   The research cannot be practicably conducted without a waiver of the requirement for 
informed consent. 
 
The research involves no more than minimal risk to subjects. 
The risk to subjects of participating in the trial is no more than minimal because the intervention 
consists of EHR-based nudges to promote LPV, which is within the standard of care for MV patients. The 
only manipulation is that LPV ordering may be made simpler and more routine, rather than left to the 
complete discretion of physicians. 
 
The risk to subjects of participating in the post-trial observational period is also no more than minimal 
because they will not be subject to any interventions during this phase of the study, and the data that 
will be collected for analysis will include only data routinely collected for clinical care. The primary risk 
will be breach of confidentiality of protected health information, and strong safeguards will be put in 
place to mitigate this risk, as described throughout this protocol. 
 
The risk to subjects participating in clinician interviews is also no more than minimal. The primary risk is 
the risk of breach of confidentiality about any comments made regarding the quality of care provided in 
the ICU or the clinicians ICU environment; however, there are strong data safeguards in place to prevent 
confidentiality breaches. 
 

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The waiver will not adversely affect the rights and welfare of the subjects. 
The waiver will not adversely affect the rights and welfare of patients because LPV is within the standard 
of care for MV patients. We do, however, recognize the possibility that some may perceive the 
intervention to limit the autonomy of physicians to order MV settings; however, this is not the case. 
Although the EHR-based nudges are designed to prompt clinicians to consider LPV setting for their 
patients, clinicians still retain decisional autonomy and can use their clinical judgment to order MV 
settings as they see fit for patient care.  
 
The waiver will not adversely affect the rights and welfare of the clinicians because they will be offered 
the options to decline participation in the interview, to terminate the interview at any time, and to 
withdraw their recording or transcript at any time. 
 
To the extent possible, the subjects will be provided with pertinent information after participating in the 
trial. 
Patients enrolled in the study will not be informed of the study as randomization occurs at the ICU unit 
level, not patient. We have strongly considered viable approaches to satisfy this criterion that is both 
practical and protective of patients’ rights. Under usual care, patients would not be consulted in real-
time by their critical care physicians regarding chosen MV settings, or informing them on chosen 
decision after the fact.  Thus informing them of this technical information afterward could cause 
unnecessary patient or family member distress. This same approach was used in PI Kerlin’s pragmatic 
trial of nighttime intensivist staffing in ICUs, which yielded a study published in the New England Journal 
of Medicine in 2013. 
 
Materials will be developed for dissemination to ICU staff through the preferred communication 
channels at each study hospital (e.g. electronic presentations, email, etc.) highlighting the new EHR 
processes. The stepped-wedge design provides ample time for the investigative team to prepare each 
hospital individually for implementation of the intervention(s) within their ICU(s). Clinicians will be 
informed of all study information and subject rights prior to proceeding with the semi-structured 
interview. 
 
The research cannot be practicably conducted without a waiver of the requirement for informed 
consent.  
This study seeks to evaluate the effectiveness of the intervention for the overall population of MV 
patients rather than to evaluate efficacy of the interventions for a selected, non-representative subset. 
The study design calls for randomization by ICU, not by individual patients. It is not technically possible 
to apply the interventions to some patients in an ICU but not others because they are order sets that 
must represent the single available order set for MV order entry within the EHR for a given ICU. 
Furthermore, because many patients will be mechanically ventilated at the time of ICU admission, 
orders for MV settings will have to be entered within 15 minutes of arrival, per health system policy. 
Thus, even if there was a role for informed consent, it could not practicably be obtained in this time 
period. These are the most prominent reasons that it is impracticable to answer the research question 
without a waiver of informed consent. A secondary, but also relevant consideration is the impracticality 
of hiring and retaining sufficient staff to obtain individual informed consent at all hours of the day over 
27 months at 12 different ICUs. This is wholly inconsistent with the goals of pragmatic clinical trials. 
 
4.3  Waiver of HIPAA Authorization  

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The INPUT study will be conducted with a waiver of HIPAA authorization in accordance with the 
provisions for using protected health information (PHI) set forth in 45 CFR 46, § 164.512 (i) as follows: 
1. The researchers require access to protected health information (PHI) in order to conduct the 
research. 
2. The research cannot be practicably conducted without the waiver.  
3.   The use or disclosure of PHI poses no more than minimal risk to participants. 
 
The researchers require access to protected health information (PHI) in order to conduct the research. 
The investigative team will analyze a data set derived directly from administrative and electronic health 
data collected in the course of providing routine clinical care. The research could not be practically done 
without access to PHI as multiple datasets and data from multiple time points need to be linked in order 
to identify eligible patients from study ICUs and evaluate the variety of outcomes to answer our study 
questions. The study is using the minimum necessary elements of PHI to enroll eligible ICU patients and 
accomplish research objectives.  
 
The research cannot be practicably conducted without the waiver. 
This large, pragmatic clinical trial will be conducted within the usual clinical care setting and utilizes 
existing EHRs rather than research personnel. The research is not practicable without a waiver of HIPAA 
authorization.  The will be conducted within the usual clinical care setting for seriously ill hospitalized 
patients requiring MV, and their clinicians, and will test an intervention implemented by existing 
electronic medical records, rather than research personnel. Given these constraints, the research team 
did not identify a suitable mechanism for notifying the clinicians without introducing important selection 
biases and contamination as discussed above, or patients and families that is both practical and 
protective of additional PHI. However, viable approaches to provide subjects with a written statement of 
research were strongly considered, but there is no clear way for this to be carried out without 
compromising patient confidentiality or by overburdening clinical staff. In order for investigators to 
coordinate patient notification, additional PHI about patients and families would be required. Therefore 
it is more prudent to forego such notification and maintain anonymity of patient data. 
 
The use or disclosure of PHI poses no more than minimal risk to the privacy of individuals because a) 
processes will be in place to protect PHI from improper use or disclosure; b) PHI will be destroyed at the 
earliest possible time; and c) there will be no improper use or disclosure of PHI. 
5. Data Management 
5.1  Data Confidentiality 
The Penn Data Manager will collaborate with his/her informatics analyst counterparts within the Penn 
Data Analytics Center (DAC) and Penn Information Services (IS) to formalize secure data protocols for 
regular transfer of EHR data from DAC and IS to the Palliative and Advanced Illness Research (PAIR) 
Center’s secure fire-walled server, with restricted access by the Penn Data Manager and appropriate 
analytic staff. Data transfer is transmitted via Penn’s Secure Share, whereby files are encrypted when 
they are uploaded, downloaded, and while being stored. Qualitative data from clinician interviews will 
be transcribed and maintained in an NVivo database on the secure server with removal of all identifiers 
and deletion of original audio files.  
 
We will implement multiple, redundant protective measures to guarantee the privacy and security of 
the patient data.  All data for this project will be stored on the secure and firewalled servers of UPHS 
and PMACS in data files that will be protected by multiple password layers.  These data servers are 

15 
 
maintained in guarded facilities behind several locked doors, with very limited physical access rights. 
They are also cyber-protected by extensive firewalls and multiple layers of communication encryption. 
Electronic access rights are carefully controlled by Penn system managers. This multi-layer system of 
data security, identical to the system protecting the UPHS’ medical records, greatly minimizes privacy 
risks. 
 
5.2  Subject Confidentiality 
Only authorized project personnel will have access to the data. All study data will be stored behind 
firewalls on computer servers; none will be stored on stand-alone PCs or laptops. Clinical trial data will 
be transferred using secure data transfer protocols from the Penn Medicine Data Analytics Center (DAC) 
and Penn Information Services (IS) to the Palliative and Advanced Illness Research (PAIR) Center on a 
monthly basis.  
 
All recorded interviews will be professionally transcribed and personal identifiers removed before 
uploading to an NVivo 11 database. All study databases will be hosted on secure servers, managed by 
the PAIR Center Data Manager, and restricted to only those individuals who are authorized to work on 
the trial. Additional measures to prevent unauthorized external access to the database environment will 
be employed using network firewall technologies. 
 
5.3  Subject Privacy 
All patient data for this study will be obtained from the EPIC electronic medical record. It is information 
that is routinely documented by clinical nurses during patient care. During routine care such as patient 
rounds, clinicians and the research team will maintain the same HIPAA standards that are currently used 
in daily clinical practice. 
 
Semi-structured interviews were chosen to protect subject privacy while collecting clinician data. In 
addition, all semi structured interviews will be conducted in a private location or by telephone and 
completed by a single research coordinator, who will be trained by Dr. Kerlin in the conduct of semi-
structured interviews. All clinicians who staff the ICUs will be recruited through existing staffing lists and 
asked to complete an interview and retain the autonomy to decline. They will also be informed that 
their responses will not be shared with any identifying information with their supervisors and that any 
data shared with supervisors or ICU leaders will only be in aggregate form so as to protect their privacy. 
6. Human Subjects Protection 
6.1  Risk / Benefit Assessment 
The potential risks to human subjects include: 1) risks of breach of confidentiality of personal health 
information; The Common Rule is fairly clear that the incremental risk standard is the appropriate one 
(1), noting that in evaluating risks and benefits, the IRB should consider only those risks and benefits 
that may result from the research (as distinguished from risks and benefits of therapies subjects would 
receive even if not participating in the research). Accordingly, the first risk listed above (breach of 
confidentiality) is germane to considerations of the risks of this research. (2) risks that the interventions 
could have untoward impacts on patients or their family members. Potential untoward impacts include 
the potential risk of adverse consequences of LPV, which may increase in use due to the intervention. 
Because LPV is used heterogeneously for patients with and without ARDS in standard practice, risks of 
LPV could be considered within the “therapies subjects would receive even if not participating in the 

16 
 
research” and hence ought not be considered risks of the research per se. Evidence suggests that LPV 
benefits mechanically ventilated patients, and although there are theoretical concerns regarding 
adverse consequences such as increased sedative needs for ventilator discomfort, such concerns have 
never been substantiated and available evidence suggests that they are not founded. Furthermore, as 
experts advocate for broader application of LPV, many patients could, and arguably should, receive LPV 
in the absence of a trial. Thus, the interventions studied are within the current range of standard of care. 
  
6.2  Protective Measures 
The ﬁrst safeguard for protection of patients includes an experienced and well-trained study team. The 
study’s principal investigator (PI), Dr. Meeta Prasad Kerlin, is Assistant Professor of Medicine at the 
University of Pennsylvania (UPenn). She has considerable expertise in research focused on ICU 
organization and the care of mechanically ventilated patients. She co-led (with Co-Investigator Halpern) 
an ICU-based randomized clinical trial published in the New England Journal of Medicine, and was a co-
investigator on a CDC-funded multicenter implementation of an opt-out strategy to improve evidence 
uptake for sedative management and MV weaning. She is also funded by the NIH for work focused on 
the identification of barriers and facilitators of prone-positioning, another proven effective intervention 
for ARDS (R03 HL144890). Co-Investigator Dr. Scott Halpern is Professor of Medicine, Epidemiology, and 
Medical Ethics & Health Policy. He has collaborated with Dr. Kerlin on the aforementioned RCT and 
numerous other ICU-based studies. He is Director of the Palliative and Advanced Illness Research (PAIR) 
Center and a member of the Steering Committee of Penn’s Center for Health Incentives and Behavioral 
Economics. He has extensive expertise in developing and testing behavioral economics interventions to 
change healthcare delivery. He is currently leading several multicenter randomized trials using 
behavioral economic and EHR-based strategies to improve care delivery. Several key members of the 
Palliative and Advanced Illness Research Center will contribute to this project: Teresa Tran, Jasmine 
Silvestri, Stefania Scott, and Wei Wang, who all have experience working with pragmatic clinical trials 
among seriously ill patients.  
 
All patient research data for this pragmatic clinical trial will be obtained from the EPIC electronic medical 
record, through chart review. The EPIC databases will be hosted on secure Penn Medicine Academic 
Computing Server and will be restricted to only those individuals who are authorized to work on the 
trial. Authorized users are knowledgeable and experienced in secure data management and 
confidentiality and will remain up to date on their Human Subjects Research Protection training. Dr. 
Kerlin will provide oversight for all authorized users. Individual user accounts with passwords will be 
used to restrict access to databases. Specific privilege assignments within databases will also be 
employed to limit the types of functions that authorized users can perform to those functions that are 
appropriate for their roles in the trial. Additional measures to prevent unauthorized external access to 
the database environment will be employed using network firewall technologies. All analytic databases 
will be de-identified.  
 
All study investigators have completed online training programs in the Responsible Conduct of Research 
and Health Insurance Portability and Accountability Act (HIPAA) certiﬁcation in accordance with Penn 
regulations. All members of the study team will maintain active certiﬁcations throughout the study. 
Online training (the Collaborative Institutional Training Initiative [CITI]) is divided into a number of 
rubrics including: data acquisition and ownership; materials and their ownership; intellectual property; 
authorship; peer review; collaborative science; human subjects; environmental safety; research 
misconduct; conﬂict of interest; and research administration. Each rubric includes institutional and 

17 
 
federal policies, lectures, and interactive quizzes. In aggregate, these materials provide systematic 
training in the fundamental issues underlying the responsible conduct of research.  
 
All patient research data for this pragmatic clinical trial will be obtained from the EPIC electronic medical 
record, through chart review. The EPIC databases will be hosted on secure Penn Medicine Academic 
Computing Server and will be restricted to only those individuals who are authorized to work on the 
trial. Authorized users are knowledgeable and experienced in secure data management and 
confidentiality and will remain up to date on their Human Subjects Research Protection training. Dr. 
Kerlin will provide oversight for all authorized users. Individual user accounts with passwords will be 
used to restrict access to databases. Specific privilege assignments within databases will also be 
employed to limit the types of functions that authorized users can perform to those functions that are 
appropriate for their roles in the trial. Additional measures to prevent unauthorized external access to 
the database environment will be employed using network firewall technologies. All analytic databases 
will be de-identified.  
 
7. 
Sample Size and Analysis Plan 
 
7.1  Sample Size 
The study will involve three groups of human subjects. 
  
The first group includes mechanically ventilated patients admitted to study ICUs during a pragmatic trial 
of interventions that will be applied at the level of the ICU. Patients will not be approached directly for 
inclusion in this study. The interventions will be embedded within the electronic health record that is in 
use at each hospital. The sample size will be determined by the number of eligible patients that are 
admitted to study ICUs during the study period, which we estimate will be 27 months during the trial 
monitoring period. An estimated 6000 patients undergo MV annually within 13 ICUs of the 6 hospitals of 
UPHS. By extrapolating these data to a 27-month enrollment period, excluding one ICU for strategy 
development and pilot- testing, and excluding a fraction of patients who will meet exclusion criteria 
specified above, at the start of the study, we estimated that approximately 8,000 MV patients will be 
eligible for inclusion in the trial across the remaining 12 ICUs during the study’s intervention period. At 
the time of the first interim analysis, after 9 months of enrollment and with more refined and precise 
data extraction and patient exclusion, we revised our projected estimates to 6900 patients who meet 
eligibility criteria during the intervention period.  
 
The second group includes clinicians who are practicing within study ICUs during the intervention 
period. Clinicians, including physicians, advanced practice providers, respiratory therapists, and ICU 
leaders, will be approached for participation in semi structured interviews to elicit their perceptions of 
the implementation strategies. We anticipate enrolling 5 to 10 clinicians per ICU, with approximately 
100 total.  
 
The third group includes mechanically ventilated patients admitted to study ICUs in the 6 months after 
intervention phase has been completed. During this observational phase, there will be no experimental 
interventions. Study ICUs will be free to design and implement processes of care entirely at their 
discretion. Patients will be included in the analysis if they meet eligibility criteria, which will be identical 
to those of the first interventional phase of the study. By extrapolating estimated enrollment data to a -
6 month enrollment period, we estimate this will include approximately 1,600 MV patients. 

18 
 
 
7.2 Statistical Analysis 
Full details are provided in a separate Statistical Analysis Plan document. 
7.2.1. Primary Analytic Approaches 
The primary analytic approach will use a modified intention-to-treat (MITT) approach. We choose this 
approach because we have observed in preliminary studies in the study ICUs that some patients will 
start MV and receive MV orders prior to ICU admission, and because of the constraints of the EHR to 
deploy the strategies, these episodes will not be eligible for exposure to the study interventions, which 
only “fires” with new MV orders. Because ICUs differ in their percentages of patients who will and will 
not be exposed to the strategies, and these patient groups may be systematically different, the primary 
analysis will include patients who have a new MV order after the time of ICU admission. 
 
We will repeat the primary analyses using two secondary analytic samples. The first will include the true 
ITT population; that is, the entire population of episodes of MV in any study ICU (after exclusions 
detailed above), regardless of whether or not there was exposure to an implementation strategy during 
the intervention period. This analysis will provide insight into how ICU-targeted strategies may influence 
the strategies’ effectiveness. We hypothesize that the effect of the strategies to improve administration 
of low tidal volumes will be attenuated in the true ITT population, compared to the modified ITT 
population. The second will include a per-protocol population; that is, only those episodes in which 
clinicians were actually exposed to the study interventions. We hypothesize that the effect of the 
strategies to improve administration of low tidal volumes will be enhanced in the per protocol 
population, but studying this population alone will not yield accurate information of the effectiveness in 
real-life settings where circumventing the nudges may be possible. 
 
The unit of analysis for the primary study outcome and all implementation outcomes will be the episode 
of mechanical ventilation. Patients may have multiple episodes of MV if the patient is ventilated multiple 
times. We will include only the first eligible episode during a hospital admission for the primary analysis. 
We will calculate the proportion of patients who receive multiple episodes or multiple admissions. We 
expect the proportion will be very small, based on prior data from study ICUs. In a sensitivity analysis, we 
will include all episodes of mechanical ventilation, including subsequent episodes for the same patient. 
There will be a small percentage of patients for whom the ICU undergoes a transition from control to an 
intervention, and a small percentage who are transferred from one ICU to another that has a different 
assignment. For primary analyses, the exposure group will be assigned according to the status of the 
admitting ICU (e.g., control or intervention assignment) at the time of the initiation of MV and ICU 
admission.  
All of the MITT, ITT, and per protocol analyses will be conducted with adjustment for the following pre-
specified, patient-level covariates that exist prior to randomization: age, gender, ICU admission source, a 
modified Laboratory-based Acute Physiology Score, version 2 (LAPS2) severity of illness, duration of 
hospitalization prior to ICU admission, location of initiation of MV (i.e., within study ICU or prior to ICU 
admission), and code status (i.e., the presence or absence of do-not-resuscitate or other treatment-
limiting orders).  
 
During the trial, one of the hospitals plans to open a new hospital tower, which will result in physical 
relocation and possible expansion of two study ICUs, as well as other organizational changes that may 
impact study variables (such as changes to nighttime coverage by critical care specialists). To account for 

19 
 
this occurrence, we will include a fixed effect for whether or not patients at this hospital were enrolled 
before or after the date that the hospital tower opens. 
 
In addition, in recognition of the fact that this trial will commence during the COVID-19 pandemic, and 
that ICUs may be altered in response to any surges of critically ill patients with COVID-19, we will a priori 
plan to include a fixed effect for any period of time of alterations in policies affecting mechanically 
ventilated patients due to COVID-19. Based on prior pandemic policies, this will include any periods of 
time in a hospital when (1) new, temporary ICUs are opened; (2) any ICUs are closed, and (3) restrictions 
placed on elective procedure scheduling, as these changes could influence the MV patient populations 
and workflow in unpredictable ways. 
 
For the primary outcome we will use mixed effects linear regression models with random effects for ICUs 
and fixed effects for time to account for the stepped-wedge cluster randomized design. The following 
comparisons are the primary comparisons of interest: control vs. strategy A, control vs. strategy B, 
strategy A vs. strategy B, strategy A vs. strategy A combined with strategy C, and strategy B vs. strategy B 
combined with strategy C. In addition, we will conduct secondary analyses to compare control vs. A+C, 
control (strategy A combined with Strategy C, an accountable justification targeting respiratory 
therapists), and control vs. B+C. The treatment group of each episode of mechanical ventilation will be 
assigned according to the intervention status of the admitting ICU (control group, or strategy A, B, A+C or 
B+C) at the time of initiation of mechanical ventilation.  
 
We will use the Holm method to assess the  between-arm contrasts of interest by sequentially testing 
the significance of each against progressively less restrictive alpha levels, preserving the family-wise 
Type I error rate of 5%. We will perform a sensitivity analysis including fixed effects for ICUs to account 
for the possibility of ICU-level confounding. We will build similar linear regression models for all 
continuous secondary outcomes and logistic mixed effects regression models for binary outcomes. 
 
 
7.2.3. Analyses of patient level factors 
Patient-level effect modification will be explored by repeating the analyses of the primary outcomes 
stratified by the two candidate effect modifiers described in detail above: presence or absence of ARDS 
and degree of hypoxia (as measured by the P:F ratio, calculated as the PaO2 divided by the fraction of 
inspired oxygen (FiO2)). If differences appear in stratified analyses, we will formally evaluate for effect 
modification by testing the significance of coefficients for statistical interaction terms between the 
potential effect modifier and the study groups on the primary outcome of LPV utilization, and on a 
subset of effectiveness outcomes: in-hospital mortality, hospital length of stay, and sedation measures. 
Finally, we will conduct subgroup analyses by race/ethnicity and sex/gender to determine the presence 
of effect modification on outcome.  
 
7.2.4. Analysis of clinician and environmental contextual factors 
To explore how the strategies interact with clinician and environmental contextual elements, we will 
conduct voluntary, semi-structured interviews with ICU clinicians (ordering clinicians and RTs) during the 
first three months after strategy implementation in each study ICU. A research coordinator trained in 
qualitative interviewing will use a semi-structured script guided by several constructs of the 
Consolidated Framework for Implementation Research (CFIR) domains of characteristics of the 
individual, inner setting, and process to elicit perceptions of the implementation strategies and identify 
factors that may influence the success of the strategies to improve adherence to LPV. For example, in 
order to understand how individual clinician characteristics interact with each strategy, we will ask them 

20 
 
about their knowledge of LPV and prior experience and comfort with managing MV patients. To 
understand the role of the inner setting factors, we will inquire about how ICU leadership influences LPV 
utilization, for example, as well as communication and teamwork between different professional groups 
involved in MV management.  
 
All interviews will be audio-recorded with the participants’ consent and professionally transcribed. Two 
research staff members will code transcripts from interviews. We will use the CFIR framework as a 
preliminary codebook 35 and add themes and subthemes specific to the data as they arise. We will 
assess inter-coder reliability by double-coding every fifth transcript. The qualitative analysis will help us 
to identify the most likely relevant factors associated with implementation of LPV. We will then test 
these theories using quantitative analyses. 
 
After developing a discrete set of clinician factors from interviews (such as level of experience, assigned 
to ICU versus rotating responsibilities), we will assign them to clinicians and evaluate whether they 
modify the effects of the implementation strategies quantitatively using the sample of patients cared for 
by participating clinicians during the trial. To do so, we will first repeat the primary analysis stratified by 
clinician factors. If we find evidence of differences in the effect sizes, we will add multiplicative 
interaction terms for each clinician factor with the implementation strategy in the models to quantify 
whether interactions are significant. To explore the role of ICU factors, we will similarly perform 
quantitative analyses stratified by ICU. After developing a discrete set of environmental factors from 
interviews, we will assign them to ICUs and explore whether any patterns emerge. 
 
7.3.  Approach to Missing Data 
Based on preliminary analyses of missingness within a retrospective cohort of MV patients admitted to 
11 of 12 study ICUs, we propose the following approaches to missing data, based on specific data 
elements: 
-Missing or erroneous value for ideal body weight:  Less than 5% of patients in a retrospective patient 
cohort including 11 of 12 study ICUs have either missing or erroneous data for patient height, which 
results in a missing or erroneous value of ideal body weight. Because the EHR-based implementation 
strategies will not function for patients with missing data for height (i.e., there will be no pre-populated 
value for tidal volume, or threshold to trigger the accountable justification prompts), we will exclude 
these patients from the primary analysis and will report the percentage of missingness in the results.   
-Missing data for ventilator settings:  Ventilator flowsheet data are entered at variable intervals, 
depending on clinical circumstances (e.g., if a patient’s settings are changed) and routine practice (e.g., 
the ICU documentation standards). Therefore, there are no regular intervals during which ventilator 
flowsheet data will be entered. At any given time point, some or all relevant ventilator data may or may 
not be entered by a respiratory therapist or nurse. If ventilator data settings are partially missing for a 
given time (e.g., one setting or parameter is documented but others are not at a certain time), we will 
use single imputation, carrying forward data from the prior time of documentation for any relevant 
parameters that are missing. We choose this strategy because we suspect that if a setting or parameter 
is not documented at a subsequent time, then that setting or parameter is unlikely to have changed (i.e., 
a change in a setting or parameter would typically prompt documentation).  
-Missing or erroneous data for potential confounders, including severity of illness measures: In our 
previous experience working with data from the retrospective cohort, we anticipate minimal 
missingness for variables that will be included in severity of illness measure (LAPS2). In the rare event 

21 
 
that we do have missingness for a parameter included in an acute physiology score, we will use single 
imputation of a normal value for that parameter, as is the common approach in calculation of severity of 
illness measures. This strategy would bias the results towards the null. We will report percentage of 
missingness and discuss the risk of bias in the limitations. 
7.4.  Statistical Power Calculations 
We estimated the power of pairwise comparisons of any of the intervention groups (Strategy A or B 
alone or in combination with C – i.e., four separate intervention groups) with the control group. We 
initially based our power calculations on the following conservative assumptions:  sample size of 8,000 
episodes across 12 ICUs; an intracluster correlation within ICUs of 0.1; and a baseline mean value of the 
primary outcome of 45% with a standard deviation of 45% (based on estimates from a retrospective 
cohort of patients admitted to ICUs in study hospitals during a 6-month period in 2020, including 
patients with COVID-19). With these assumptions, we estimated that we will have >95% power to detect 
an increase of 25% in the mean value of the primary outcome (from 45% to 70%), which would 
approximate the utilization rates of the study ICU with the highest adherence to tidal volume < 6.0ml/kg 
ideal body weight. This sample size also has >90% power to detect a difference of 20% and nearly 80% 
power to detect a difference as low as 15% in any pairwise comparisons. Finally, this sample size has 
80% power to detect a reduction in in-hospital mortality from an estimated 25% to 16%.  
At the time of the first interim analysis, based on the rate of accrual during the first 9 months of the trial 
and with application of more precise exclusion criteria, we found that the number of eligible patients 
admitted to study ICUs was lower than projected. Therefore, we repeated power calculations with 
smaller estimated samples sizes of 5100 for the MITT (primary) population and 6900 for the ITT 
population. With these new estimates, and using the same assumptions as above, we estimated that we 
have at least 97% power to detect an increase of 25% in the mean value of the primary outcome (from 
45% to 70%) and greater than 80% power to detect an increase as low as 17% in the mean value of the 
primary outcome within the MITT population. In addition, the new estimated MITT sample size has 
approximately 80% power to detect an 11% reduction in hospital mortality from an estimated 25% to 
14%. 
 
8. 
Data and Safety Monitoring 
8.1.  Adverse Events and Unanticipated Problems 
The study team will be responsible for identifying and reporting all serious adverse events, protocol 
deviations/violations, and unanticipated problems to the IRB, DSMB, and funding agency promptly, as 
appropriate. In order for the PI to remain blinded, expert critical care clinicians (attending physician, 
fellow physician, or advanced practice provider) trained by PI Kerlin will lead adverse event monitoring 
and reporting, with the support of the project manager. We will proactively perform surveillance of 
three adverse events – life-threatening acidemia, and death or cardiac arrest within 24 hours of trial 
enrollment. Adverse events possibly or likely related to the intervention will be reported immediately to 
the Data and Safety Monitoring Board (DSMB, see below) within 7 days of occurrence, if fatal or life-
threatening. Unanticipated problems will be reported to DSMB within 14 days of identification.   
 
8.2.  Data and Safety Monitoring Board 
An important safeguard to protect research participants is the development of a plan for ongoing data 
and safety monitoring to anticipate, and protect against, any human subjects research concerns that 

22 
 
may arise. We will convene a DSMB comprising noted experts in critical care, palliative care, and 
biostatistics to guard against the possibility of any unforeseen risks arising during the study. Members of 
the DSMB will not be involved in the conduct of the trial. Once convened, the DSMB will perform several 
duties. First, they will review and approve the research protocol and plans for data and safety 
monitoring prior to the study’s implementation. Second, they will evaluate the progress of the trial. This 
will include assessment of data quality, participant accrual and retention, participant risk versus benefit, 
and study outcomes. Third, they will make recommendations to ensure that any identified issues are 
appropriately addressed. The DSMB will meet after 9 months and 18 months (one-third and two-thirds 
of the way through the trial enrollment.  We will charge DSMB members with using their judgment in 
simultaneously considering many data points in making decisions about trial design modifications and 
trial continuation or termination. The PI (Dr. Kerlin), the project manager, and the data analyst (Dr. 
Wang), will participate in all DSMB meetings as non-voting members. The PI, assisted by the project 
manager, will be responsible for maintaining communication between the DSMB, the IRB, and study 
sites. 
   
Our DSMB members to monitor the scientific conduct of the study are as follows: 
• 
Todd Rice, MD, MSc Associate Professor of Medicine in the Division of Allergy, Pulmonary and 
Critical Care Medicine at Vanderbilt University  (DSMB Chair) 
• 
Daniella Meeker, PhD Assistant Professor of Preventive Medicine and Director of Clinical Research 
Informatics at the  Keck School of Medicine University of Southern California 
• 
Kristin Riekert, PhD Professor of Medicine in the Division of Pulmonary and Critical Care Medicine, 
Department of Medicine at Johns Hopkins University and Director of the Johns Hopkins Adherence 
Research Center (JHARC) and the Director of the Cystic Fibrosis Adherence Program 
• 
Jing Cheng, MD, MS, PhD Professor of Biostatistics within the University of California San 
Francisco Division of Oral Epidemiology & Dental Public Health and Division of Epidemiology and 
Biostatistics 
 
8.3.  Interim Analyses 
The trial will be monitored routinely for issues of data quality and study conduct (including participant 
enrollment and technical issues with EHR order sets) via monthly data extraction and analysis by our 
research team's data manager, Stefania Scott. We will conduct two interim analyses – after 
approximately 9 months and 18 months (one-third and two-thirds of the trial duration, respectively) – of 
two study outcomes:  (1) fidelity to LPV (primary outcome, as specified above), and (2) in-hospital 
mortality.   
We do not plan to stop the trial early for evidence of effectiveness of the implementation strategies 
because doing so would reduce our power for secondary analyses and analyses of effect modification. 
We will propose to stop the trial for early evidence of harm based on in-hospital mortality. 
 
8.4.  Institutional Review Board (IRB) 
The convened University of Pennsylvania IRB (FWA: 00004028) have approved the INPUT study 
(#833340) with a waiver of informed consent and waiver of patient notification. Penn IRB will provide 
regulatory oversight for the trial activities at the study hospitals.  All modifications to the protocol will be 
submitted to both IRBs for approval prior to implementation.   

23 
 
 
8.5.  Clinicaltrials.gov 
The INPUT study is registered on clinicaltrials.gov (NCT04663802). Although not required by law for 
clinical trials not involving drugs or devices, trial registration is required by the International Committee 
of Medical Journal Editors (ICMJE) as a condition of the publication of research results generated by a 
clinical trial and by the National Institutes of Health (NIH) for all funded clinical trials. The study profile 
will be regularly updated on the website and summary results uploaded to make information about the 
study publicly available and promote transparency. 
 
 

24 
 
 
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15. Rubenfeld GD, Cooper C, Carter G, Thompson BT, Hudson LD. Barriers to providing lung-protective ventilation 
to patients with acute lung injury. Crit Care Med 2004;32:1289-93. 
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in acute respiratory distress syndrome: survey development, validation, and results. Crit Care Med 
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17. Weiss CH, Baker DW, Tulas K, et al. A Critical Care Clinician Survey Comparing Attitudes and Perceived Barriers 
to Low Tidal Volume Ventilation with Actual Practice. Ann Am Thoracic Soc 2017;14:1682-9. 
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Potential Effect on Clinical Study Results. Ann Am Thoracic Soc 2016;13:1123-8. 
19. Sjoding MW, Hofer TP, Courey A, Cooke CR, Iwashyna TJ. Interobserver Reliability of the Berlin ARDS Definition 
and Strategies to Improve the Reliability of ARDS Diagnosis. Chest 2017. 
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increase sedation use in patients with acute lung injury. Crit Care Med 2005;33:766-71. 
21. Serpa Neto A, Simonis FD, Barbas CS, et al. Association between tidal volume size, duration of ventilation, and 
sedation needs in patients without acute respiratory distress syndrome: an individual patient data meta-
analysis. Intensive Care Med 2014;40:950-7. 
22. Serpa Neto A, Cardoso SO, Manetta JA, et al. Association between use of lung-protective ventilation with 
lower tidal volumes and clinical outcome 

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23. Campbell MJ and Walter SJ. How to design, analyse and report cluster randomised trials in medicine and 
health related research: John Wiley; 2014.