Multi-center Clinical Trial of Limiting Resident Work Hours on ICU Patient Safety
Phase: NA
Conditions: Physician Fatigue
Sponsor: Brigham and Women's Hospital

This supplement contains the following items for the ROSTERS study:  
Contents: 
Page 2‐19. 
 Original protocol, from March 2013. 
Page 20‐37.  
Final protocol, from June 2015. 
Page 38.  
Summary of changes to the protocol. 
Page 39‐42. 
Original statistical analysis plan from September 2014. 
Page 43.  
Summary of additions to the statistical analysis plan requested by the Data and Safety 
Monitoring Board (DSMB) prior to unblinding of the study investigators. 
  

 
 
 
 
 
ROSTERS 
Randomized Order Safety Trial Evaluating 
Resident Schedules  
 
A Multi-Center Trial of Limiting PGY 2&3 Resident Work  
Hours on ICU Patient Safety 
 
Principal Investigators: 
Charles A. Czeisler, PhD, MD 
Christopher P. Landrigan, MD, MPH 
Katie L. Stone, PhD 
 
Supported by: 
National Heart Lung and Blood Institute 
 
Version 1.0 
 
March 5, 2013 
 

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Table of Contents 
PROTOCOL SUMMARY ......................................................................................................... 4 
1.1 
STUDY AIMS ................................................................................................................ 5 
1.1.1 Aim 1: ............................................................................................................................ 5 
1.1.2 Aim 2: ............................................................................................................................ 5 
1.1.3 Aim 3: ............................................................................................................................ 5 
1.2 
BACKGROUND AND RATIONALE .......................................................................... 5 
1.3 
STUDY DESIGN AND INTERVENTIONS ................................................................. 6 
1.4 
SELECTION AND ENROLLMENT OF PARTICIPANTS ......................................... 7 
1.4.1 
Recruitment ............................................................................................................ 7 
1.4.2 
Randomization ........................................................................................................ 7 
1.4.3 
Preparation of subjects ........................................................................................... 7 
1.5 
STUDY PROCEDURES ................................................................................................ 7 
1.5.1 
Detection of Errors and Adverse Events ................................................................ 8 
1.5.1.1 
Continuous Observation ..................................................................................... 8 
1.5.1.2 
Voluntary and solicited reports .......................................................................... 8 
1.5.1.3 
Collection of formal incident reports ................................................................. 8 
1.5.1.4 
Chart surveillance ............................................................................................... 8 
1.5.2 
Classification by severity, attribution, and preventability ...................................... 9 
1.5.3 
Identification of patient risk factors ....................................................................... 9 
1.5.4 
Measuring Sleep and Fatigue ................................................................................. 9 
1.5.4.1 
Sleep and work logs ............................................................................................ 9 
1.5.4.2 
Ambulatory physiologic monitoring .................................................................. 9 
1.5.5 
Measuring Resident Vigilance and Driving Safety ................................................ 9 
1.5.5.1 
Optalert ............................................................................................................... 9 
1.5.5.2 
 PVT. ................................................................................................................. 10 
1.5.6 Additional Measures .................................................................................................... 10 
1.5.6.1 Self-reported attentional failures, motor vehicle crashes (MVCs), and 
percutaneous injuries ........................................................................................................ 10 
1.5.6.2 Educational Measures ........................................................................................... 11 
1.5.6.3 Collection of Salivary Samples for Subsequent Genetic Analyses ...................... 11 
1.6 
SAFETY ASSESSMENTS .......................................................................................... 11 
1.7 
STATISTICAL CONSIDERATIONS ......................................................................... 11 
1.7.1 Outcomes and Statistical Analyses .............................................................................. 11 
1.7.2 Sample Size and Minimum Detectable Effects ........................................................... 12 
1.8 
DATA COLLECTION AND QUALITY ASSURANCE ............................................ 13 
1.8.1 Data Acquisition and Transmission ............................................................................. 13 
1.8.2 Data Collection and Editing ........................................................................................ 13 
1.8.3 Data Management and Study Progress ........................................................................ 14 
1.8.4 Staff Training ............................................................................................................... 14 
1.9 
PARTICIPANT RIGHTS AND CONFIDENTIALITY .............................................. 14 
1.9.1 Institutional Review Board (IRB) Review .................................................................. 14 
1.9.2 Informed Consent Forms ............................................................................................. 14 
1.9.3 Participant Confidentiality ........................................................................................... 15 
1.9.3.1 Clinical Sites ......................................................................................................... 15 
1.9.3.2 Data Coordinating Center ..................................................................................... 15 

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1.10 
COMMITTEES ............................................................................................................ 15 
1.10.1 Steering Committee ................................................................................................... 15 
1.10.2 Executive Committee ................................................................................................ 16 
1.10.3 Principal Planning Group .......................................................................................... 16 
1.10.4 Working Groups ........................................................................................................ 16 
1.10.5 Data and Safety Monitoring Board ............................................................................ 16 
1.11 
CONFLICT OF INTEREST ......................................................................................... 17 
1.12 
REFERENCES ............................................................................................................. 17 
 
 
 
 
 
 
 

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PROTOCOL SUMMARY 
 
Objective: 
To conduct a multi-center randomized crossover trial in six pediatric ICUs staffed by PGY2 
and PGY3 residents to compare the effectiveness and safety of a sleep and circadian science-
based (SCS) intervention schedule with a traditional schedule that includes frequent shifts of 
24 hours or longer. 
 
Study Population: 
Second and third year (PGY2 and PGY3) residents 
 
Study Design: 
Multi-center randomized crossover trial 
 
Interventions: 
Sleep and circadian science-based intervention schedule versus a traditional schedule 
 
Primary outcomes: 
Resident-related preventable adverse events and near misses 
 
Secondary Outcomes: 
ICU-wide preventable adverse events and near misses 
Resident neurobehavioral performance and predicted driving safety 
 
Study Duration: 
12 months (4 month wash-in period followed by 8 months of data collection) 

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1.1 
STUDY AIMS 
1.1.1 Aim 1: 
To test the hypothesis that PGY2&3 residents working on an SCS intervention schedule will 
make significantly fewer harmful medical errors (preventable adverse events) and other 
serious medical errors (near misses) while caring for ICU patients than residents working on a 
traditional schedule; (primary endpoints: resident-related preventable adverse events and 
near misses) 
 
1.1.2 Aim 2:  
To test the hypothesis that rates of harmful medical errors (preventable adverse events) and 
other serious medical errors (near misses) throughout the ICU (i.e., those involving and those 
not involving residents) will be lower in ICUs when PGY2&3 residents work on an SCS 
intervention schedule than when residents work on a traditional schedule; (major secondary 
endpoints: ICU-wide preventable adverse events and near misses) 
 
1.1.3 Aim 3: 
To test the hypothesis that resident physicians’ risk of neurobehavioral performance failures 
and motor vehicle crashes – as assessed through simple visual reaction time tasks [Johns 
Drowsiness Score (JDS) and Psychomotor Vigilance Task (PVT) lapses] – will be lower on 
the SCS intervention schedule than on the traditional schedule. (major secondary endpoints: 
resident neurobehavioral performance and predicted driving safety) 
 
1.2 
BACKGROUND AND RATIONALE 
 
Sleep deficiency and circadian disruption degrade human alertness and performance both in 
laboratory and occupational settings. Over the past decade, a series of studies have found that 
first-year residents (interns; PGY1s) working recurrent extended duration shifts (>24 hours) 
make more serious medical errors than do those working shifts of <16 consecutive hours; 
moreover, PGY1s working extended duration shifts suffer more injuries on the job, and have 
an increased risk of motor vehicle crashes (MVCs) on the drive home from work.(1-8) In 
2009, after a year-long comprehensive study, the Institute of Medicine (IOM) concluded that 
while it remained unclear whether resident sleep deprivation led to patient harm, “the 
scientific evidence base establishes that human performance begins to deteriorate after 16 
hours of wakefulness.”(9;10) They consequently called for the elimination of all resident 
physician shifts without sleep over 16 consecutive hours. 
 
In response, beginning in July 2011, the Accreditation Council for Graduate Medical 
Education (ACGME) limited interns to no more than 16 consecutive hours of work; second 
year (PGY2) and higher residents, however, will continue to work for up to 28 consecutive 
hours.(11) In choosing not to more substantively limit the hours of PGY2 and higher residents 

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– who represent approximately 80% of all physicians-in-training – the ACGME indicated that 
in its view, insufficient data existed to support policy change for more senior trainees. 
 
In this study, we seek to conclusively address two knowledge gaps: 1) the lack of data on the 
relationship between PGY2 and higher sleep deprivation and patient safety; and 2) the lack of 
data on the relationship between resident sleep deprivation and preventable patient injuries. 
 
1.3 
STUDY DESIGN AND INTERVENTIONS 
 
The study is a clustered randomized controlled trial to evaluate the effectiveness of eliminating 
residents’ traditional 24-hour shifts in ICUs. The trial will take place in 6 academic medical centers 
nationwide, in three waves of two centers each.(Figure 1) One of each pair of units will initially be 
randomly assigned to the traditional schedule (i.e., in which overnight shifts of 24-28 hours continue 
to occur every 4 nights), or to the SCS intervention schedule (i.e., in which residents are limited to 
16 consecutive work hours; sleep before night duty is promoted; and time off is arranged to allow 
recovery from sleep debt.) 
Our planned timeline will be as follows: after a 2 month planning and startup period, during which 
staff will be recruited and hired, the intervention will be implemented in one randomly selected 
PICU in study wave 1; the traditional schedule will continue in the other PICU.  There will be a 4-
month wash-in period, after which time 8 months of data collection will take place in intervention 
(in black, Figure 1) and traditional (in blue) ICUs. After 8 months of data collection, the units will 
cross over (traditional to intervention schedule; intervention to traditional). Following another 4-
month wash-in period, there will be 8 additional months of data collection. Study sites in waves two 
and three will follow the same pattern. Of note, each intervention period will be scheduled to occur 
entirely within a single academic year, and will be preceded or followed (12 months apart) by a 
control period that will also occur entirely within an academic year.  
 
Figure 1. Timeline 
 
 
 
 

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1.4 
SELECTION AND ENROLLMENT OF PARTICIPANTS  
 
All second and third year residents at the six clinical centers will be invited to enroll in the study. 
The only exclusion criteria is that the resident is at least 21 years of age. Four to eight residents will 
be recruited per month at each clinical center for total of approximately 50 residents per site and 
approximately 300 subjects study-wide.  
1.4.1 Recruitment 
Sites will submit a waiver of informed consent for the collection of patient data, but will 
obtain residents’ written informed consent to observe them, and collect resident-specific data. 
Working with program directors at each hospital, the Principal Investigators will make 
presentations each year to all residents to describe our study and request volunteer 
participants. Residents are free not to participate in the study; if they choose not to participate, 
they will not be followed by observers and no other data will be collected from them, but the 
unit schedule will proceed on the traditional or SCS intervention schedule as planned. 
1.4.2 Randomization 
The intervention will be implemented in one randomly assigned study site in each of the three 
waves and the second site will remain on the traditional schedule. After 8 months of data 
collection, the units will cross over (traditional to intervention schedule; intervention to traditional). 
The Data Coordinating Center (DCC) will be responsible for randomly assigning sites to their initial 
study arm.  
1.4.3 Preparation of subjects 
Before the start of each study, volunteers will receive a detailed explanation of the procedures 
involved in the study. They will also attend an educational seminar prior to the implementation of 
the intervention schedule designed to provide an overview of sleep and circadian science, and to 
convey the importance of complying with the protocol by attempting to sleep prior to night shifts. 
They will be asked to complete a baseline survey, which will include the Sleep Disorders and Berlin 
Sleep Questionnaires. 
 
1.5 
STUDY PROCEDURES 
 
The study will take place in pediatric intensive care units (PICUs). In general, subjects will 
continue to carry out their normal activities and responsibilities when working either the 
intervention or traditional schedule. Throughout the PICU rotations, subjects will complete a 
daily sleep diary; will wear actiwatches, described further below, to validate the results of 
self-reported sleep; and will wear Optalert glasses on the commute to and from work.  They 
will also periodically complete psychomotor vigilance tests (PVTs) to monitor their vigilance.  
At the completion of their rotations, all subjects will complete an End of Rotation survey. For 
every experimental intervention, there will be written protocols and checklists used to insure 
uniformity in the execution of standard procedures. 

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1.5.1 Detection of Errors and Adverse Events 
We will use a very intensive, four-pronged data collection approach to comprehensively 
measure rates of all errors and adverse events.  
1.5.1.1 Continuous Observation  
A team of five physician research associates will conduct direct observation of resident 
subjects working in the units, 24 hours per day, 7 days per week. The observers will share this 
responsibility, working in eight-hour shifts. All suspected adverse events and errors will be 
documented on tablet-based data forms, and transmitted to the research nurse, who will gather 
follow-up data on them while conducting his or her daily chart reviews, as described below.  
The observer will also record and classify all medical activities in which the study subject 
engages, including but not limited to performance of procedures, test and medication 
ordering, and test interpretation. Suspected adverse events and incidents will be identified and 
classified. Follow-up of all suspected adverse events and errors detected by the observers will 
be performed by the nurse data extractors, who will collect additional information. 
 
1.5.1.2 Voluntary and solicited reports 
Forms will be made available and prominently posted in the ICUs to facilitate voluntary 
reporting of possible errors and events by nurses and other clinical staff. Chart reviewers will 
also request reports from staff of errors and adverse events 5 days per week. Any reported 
error or event will be pursued by the nurse data extractors, who will collect additional 
information. 
1.5.1.3 Collection of formal incident reports 
In each hospital, formal incident reports will be collected if permitted; if any institutions will 
not allow access to these data, we will request that duplicate study reports be filed by clinical 
staff on our study units when they complete formal reports. In addition, in any hospitals with 
computerized adverse event detection systems, the computerized AE monitors will also be 
interrogated for study-unit events. Nurse data extractors will collect additional information on 
each incident identified. 
1.5.1.4 Chart surveillance 
The nurse data extractors will serve as the focal point for data collection and organization, and 
will follow up and review all data collected by observers, reported by staff, and detected via 
incident reporting systems. In addition to coordinating collection from other sources, 
reviewers will examine all orders and charts 5 days per week; a focused version of the 
Institute for Healthcare Improvement (IHI) Global Trigger Tool (consisting of the intensive 
care module, cares module, and medication module triggers)(12) will be used to increase the 
sensitivity of adverse event detection. Reviews on Monday will include a review of the 
weekend. Data collected for each incident will include a description and classification of the 
event, patient information, services and personnel involved, and additional work resulting 
from the event. Medication incidents will further include name, dose, route and category of 
the drug involved. 

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1.5.2 Classification by severity, attribution, and preventability 
Physician observers and research nurses will identify suspected errors and adverse events. 
Two independent physician reviewers will subsequently classify events as errors, potential 
adverse events (near misses), or adverse events. All events will be rated on severity using the 
modified NCC-MERP scale.(12;13) Preventability will be rated using a four point Likert 
scale. Disagreements will be resolved by discussion. Events for which consensus cannot be 
reached will be re-rated by a third reviewer. Pre-discussion inter-rater reliability will be 
evaluated with the Kappa statistic.  
1.5.3 Identification of patient risk factors 
Clinical and demographic data for all patients admitted to study units will be collected by the 
observers from patient records and institutional administrative databases during lulls in unit activity. 
Severity of illness will be assessed using a standardized illness severity score, such as PRISM.(14) 
Morbidity and disability data will be collected until discharge for all patients with an adverse event, 
as will data about the complexity of conditions, interventions, and drug regimens, including number 
and types of drugs and interventions. 
1.5.4 Measuring Sleep and Fatigue 
In addition to data on patient safety, we will collect data on residents’ sleep and work hours 
using the methods described below.  
1.5.4.1 Sleep and work logs 
A diary of sleep and wake times will be maintained by the research volunteers. A post-sleep 
questionnaire will be completed immediately following wake time from all sleep episodes and 
will provide information on subjective evaluation of sleep onset, duration, consolidation, 
quality, and wakefulness during sleep, as well as daily work hours. Our sleep and work logs 
have previously been validated; hours of sleep and work reported using this methodology 
have a high correlation with polysomnographically-validated total sleep time (r=0.94) as well 
as 3rd-party documented work hours (r=0.98).(2) 
1.5.4.2 Ambulatory physiologic monitoring 
To further validate reported sleep times in this study, wrist activity and ambient light levels 
will be monitored for the entire duration of residents’ rotations with a solid-state, portable 
data collection device (Motionlogger BASIC; Ambulatory Monitoring, Inc., Ardsley, NY). 
The Motionlogger recorder is a small wrist worn device that measures activity and ambient 
light exposure; it is waterproof and powered by a 3V, 150 mAmp-hr Lithium Manganese 
battery that has a lifetime of 60 days. Data are preserved if the battery expires.  
1.5.5 Measuring Resident Vigilance and Driving Safety 
1.5.5.1 Optalert  
Optalert is an innovative technology that uses infrared oculography to 
monitor the alertness of an individual continuously. The Optalert glasses 
contain a small light emitting diode (LED) positioned below and in front 
of the eye, attached to a frame designed to hold clear or prescription 
lenses. (Figure 2) Brief pulses of invisible infrared (IR) light (each lasting 
 
Figure 2. Optalert 
glasses  

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70 μs, wavelength 935 nm) are directed up in a 30 degree cone of light centered on the lower edge 
of the upper eyelid and repeated at a frequency of 500 Hz. The total IR light reflected back from the 
eye and eyelid is detected by a phototransistor in the frame beside the LED.  
 
 
A microprocessor, housed in the arm of the glasses, controls the timing and other characteristics of 
the IR pulses, and digitizes the analogue output from the sensors. The power supply and the serial 
output from the glasses via a light cable connected to a personal digital assistant (PDA). This PDA 
provides a variety of different analyses of the recorded signals including reflecting position and the 
velocity of movements. The velocity of movements are calculated 500 times per second as the 
change in position (uncalibrated units) per 50 ms. The durations of the separate components of 
blinks and of other eye and eyelid movements, and their AVRs, are measured by software that 
included period-amplitude analysis of both the position and velocity signals and classification of all 
periods and amplitudes per minute.  
 
These analyses automatically generate an alertness score (Johns Drowsiness Scale, JDS), a 
composite measure of alertness based on many variables characterizing blinks, including the 
ratio of the amplitude to the maximum velocity (AVR) of eyelid movements for closing and 
reopening of the eyelids, as well as the duration of eyelids closing, of remaining closed, and 
of reopening during blinks. The weighting for each variable in the JDS was derived from 
multiple regression analysis, comparing results of Optalert recordings before and after sleep 
deprivation. The JDS is calculated each minute on a 0-10 scale. Normal values are 0-4, and do 
not require adjustment for individual subjects.  
1.5.5.2  PVT.  
In the proposed study, we will also have resident physician subjects complete Psychomotor 
Vigilance Testing – an established metric of vigilance that is sensitive to sleep deprivation and 
circadian misalignment (15) – during one shift per week, every five hours.  Completing the PVT 
requires 10 minutes and provides data on vigilance that will be used to derive an independent 
measure of neurobehavioral performance while subjects are on the job. 
1.5.6 Additional Measures 
1.5.6.1 Self-reported attentional failures, motor vehicle crashes (MVCs), and percutaneous 
injuries 
Through end-of-rotation surveys, we will also collect data on residents’ self-reported 
attentional failures, MVCs, near-miss MVCs, and percutaneous injuries using the instruments 
we previously developed for use in our national cohort study. Any reported MVCs and 
percutaneous injuries will be validated by the collection of objective data (e.g. police reports, 
repair bills, etc. for MVCs), as was done in our cohort study.(1;4) When MVCs occur on the 
commute to and from work, we will also have detailed Optalert data available. We believe 
that collecting MVC and percutaneous data is important given their implications for resident 
safety, but with 300 anticipated subjects in the study, and the relative infrequency of these 
occupational injuries,(1;4) we will have power to detect an effect of the intervention on these 
outcomes only if they are reduced more than two-fold. As such, analysis of these outcomes 
will be considered exploratory. 

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1.5.6.2 Educational Measures 
We will also, through the daily diaries and the end-of-rotation survey, collect preliminary data 
on residents’ educational experiences. Residents will provide daily estimates on their logs of 
the amount of time spent in didactic education and the amount of time spent reading for 
knowledge acquisition.  On their end-of-rotation surveys, they will report their impressions of 
their educational experience. 
1.5.6.3 Collection of Salivary Samples for Subsequent Genetic Analyses 
In light of the emerging science exploring the genetic predictors of susceptibility to sleep loss 
and circadian misalignment, salivary samples will be collected to measure genetic modifiers 
of the SCS intervention’s effects. Unfortunately, the limited number of subjects (~300) being 
studied in this proposed trial precludes conducting genome-wide association studies to 
determine what genes may convey an increased risk of fatigue-related error, and as yet, no 
candidate gene has been independently verified to convey altered vulnerability to the 
performance-impairment associated with sleep deprivation. However, given that this study 
will gather unprecedented data on sleep, performance, and safety, and the likelihood that one 
or more candidate genes will be verified in the near future, we will collect samples and 
analyze the DNA of all participants who agree to participate in a future genetic evaluation. 
These specimens will then be available at a later time to evaluate whether candidate genes 
verified to affect vulnerability to sleep loss predict the probability of Optalert lapses or of 
making an error that leads to an AE. 
1.6 
SAFETY ASSESSMENTS 
 
The study will be looking for the occurrence of adverse events that occur in ICU care; some 
are preventable, and some are not. Data on adverse events will be systematically collected and 
reviewed by the DSMB after each 8 month data collection period. Rates of adverse events 
will be compared and the DSMB will subsequently make periodic recommendations on 
whether to continue, modify, or terminate the study. From prior studies, we have found that 
the cause of detected adverse events in hospitals cannot in most cases be reliably assigned on 
a case by case basis (e.g., was acquisition of a catheter-related bloodstream infection due to a 
resident’s work schedule? A nurse error? Another cause?), so we anticipate that there will not 
be discrete, individual adverse events that would modify an assessment of the safety of the 
intervention or traditional work schedule’s risks; rather, we expect that through epidemiologic 
methods, we will obtain useful data on the safety of the intervention vs. traditional work 
schedules, and act as needed. However, if there are discrete events that clinical staff or study 
investigators believe are attributable to either the intervention of traditional work schedule, 
these events will be brought to the attention of the DSMB for review and action as needed.  
1.7 
STATISTICAL CONSIDERATIONS 
1.7.1 Outcomes and Statistical Analyses 
We will compare resident-related (Specific Aim 1) and total (Specific Aim 2) rates of harmful 
medical errors (preventable adverse events) on the two schedules. As a secondary measure, 
rates of non-harmful serious medical errors (i.e., near misses) will also be compared. In an 
intention-to-treat analysis, rates will be compared by schedule using Poisson models with 

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Serious medical 
errors 
Resident-related 
rate per 1000 
patient-days 
MD-RRR with 
Scale Factor of 
1.0 (2.0) 
Unit rate per 
1000 patient-
days 
MD-RRR with 
Scale Factor of 
1.0 (2.0) 
overall 
136.0 
8.0% (11.2%) 
193.2 
6.7% (9.4%) 
intercepted 
70.3 
 11.0% (15.5%) 
95.1 
9.5% (13.3%) 
non-intercepted 
44.8 
13.8% (19.2%) 
59.5 
11.9% (16.7%) 
Preventable AEs 
20.9 
19.8% (27.5%) 
38.6 
14.8% (20.6%) 
Figure 3, power table. Minimum detectable relative rate reductions (MD-RRRs) 
detectable with 90 percent power in two-sided tests (with alpha of 5%) for serious 
medical errors, by sub-type of error, using Poisson models. The primary outcomes of 
interest, resident-related and total preventable AEs, are bolded. 
compound symmetric working correlation and robust standard errors to account for both over-
dispersion and clustering by clinical center (16), and the number of patient-days at risk in 
each center and period included as so-called offset. The models will control for period effects 
and will be used to assess treatment-period interaction, a standard check with crossover 
trials(17). 
 
In addition, actigraphy and sleep diaries will be used to ascertain the minimum and mean 
number of hours of sleep obtained per night, total sleep time, wake after sleep onset (WASO; 
minutes), and sleep efficiency. We will also compare performance on the Johns Drowsiness 
Score (JDS), based on results captured by Optalert, and the Psychomotor Vigilance Test 
(PVT).  Specifically, we will compare the time-weighted average JDS score for each shift; the 
proportion of the shift minutes spent with a JDS score above 4.5, the cutoff for impairment; 
and the numbers of lapses in vigilance, defined as a reaction time >500 ms, on the PVT. 
These Intention-to-treat comparisons by will be made using linear mixed models for repeated 
measures, with nested random effects to account for clustering within clinical center and 
residents12. Outcomes will be normalized as necessary; generalized linear mixed models 
appropriate for other outcome distributions, and/or bootstrap standard errors will be used if 
adequate normalization cannot be achieved. In preliminary analyses, we will assess the 
comparability of the residents in the intervention and control periods in terms of age, gender, 
post-graduate year (PGY2 vs PGY3), as well as other potential confounders of the 
intervention.  If imbalances are found, we will conduct sensitivity analyses in which we 
flexibly adjust for the potential confounders.   
1.7.2 Sample Size and Minimum Detectable Effects 
Based on the Intern Sleep and Patient Safety Study, during which 2,203 patient-days were 
accrued under both schedules over a total of 8.5 months at a single center with 2 ICUs totaling 
20 
beds, 
we 
estimate 
that 
approximately 
46,080 patient-
days 
will 
be 
accrued 
across 
the six centers in 
this study, each 
contributing an 
observation 
period 
of 
8 
months on each 
schedule, with an average census of 16 patients, or 80% of an average 20 beds. Assuming that 
the baseline error rates per-patient day on the standard schedule are the same as those 
observed in the Intern Sleep and Patient Safety Study, the new sample will provide 90% 
power to detect relative rate reductions (MD-RRRs) on the sleep and circadian science-based 
(SCS) intervention schedule as shown in Figure 3. Estimates are shown first assuming a scale 
factor of 1.0, corresponding to a Poisson distribution, while conservative estimates assuming 
an over-dispersed Poisson distribution with a scale factor of 2.0, are shown in parentheses. 
For overall serious medical errors, we will have 90% power to detect reductions in both 

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resident-related and unit error rates of 7-11%; MD-RRRs for intercepted and non-intercepted 
medical errors will be between 9.5 and 19%.  Even for the least frequent outcome but that of 
greatest interest, resident-related preventable AEs, we will have 90% power to detect a 
relative reduction of 19.8% if the distribution is Poisson, and 27.5% under our conservative 
assumptions about over-dispersion. The actual reductions seen in our preliminary study were 
larger than these thresholds in each sub-category of resident-related serious errors, including 
resident-related preventable adverse events.  Thus, we expect to be adequately powered to 
draw definitive conclusions regarding the effectiveness of the SCS schedule intervention.  In 
assessing interaction/period interactions, MD-RRRs will be fourfold larger than the main 
intervention effects.  However, because residents will participate in at most one period, the 
potential for carryover effects is much smaller than in most crossover studies. 
 
In addition, for sleep and work hours as well as JDS and PVT results, we estimate the expected 
sample of 300 residents will provide 90% power in 2-sided tests with alpha of 5% to detect 
standardized between-group differences of 0.30 to 0.37 standard deviations of the outcome, 
depending on the design effect due to clustering within 
centers and residents; calculations are shown in Figure 4 
for minimum detectable effects (MDEs) for sleep and 
work hours, based on standard deviations observed for 
sleep and work hours observed in the ICU pilot study 
conducted at Brigham and Women’s Hospital. Because 
this pilot study did not collect data on other sleep 
outcomes (e.g. WASO, sleep efficiency) or the 
performance outcomes (JDS and PVT), the standardized units are also shown in Figure 4. These 
calculations show that the study will be powered to detect small-to-moderate intervention effects on 
these outcomes, even if the design effect is as large as 2.  
1.8 
DATA COLLECTION AND QUALITY ASSURANCE  
1.8.1 Data Acquisition and Transmission  
The DCC will develop a front-end component for data entry and transmission. Data would be 
entered at remote sites on secure mobile computing devices and transmitted a minimum of 
once a day via secure transfer. Data received will be automatically imported into SQL tables 
and integrated into our standard data system. Data will be available for review/updating via 
the standard study website within 24-48 business hours. The DCC will create and maintain a 
comprehensive programmer’s guide for all the data systems it provides.  
1.8.2 Data Collection and Editing 
Capturing data electronically will reduce the risk of missing data. Furthermore, edits checks 
may be built into the instruments to flag out of range or inconsistent data. Further custom edit 
checks will be written and run on data received at the DCC. Each hour, the cumulative study 
data is subjected to these custom edits to ensure completeness, consistency and validity of the 
data.  The results of the error-checking procedures are posted to the study website, which the 
study staff will check daily to both confirm that the DCC has successfully received all of the 
transmitted forms and to address errors that have been detected by the edit system.  The 
Project Manager and other Clinical Coordinating Center (CCC) staff will be responsible for 
Outcome 
MDE  
Sleep hours (weekly) 
1.75 / 1.92 / 2.21 
Work hours (weekly) 
1.39 / 1.53 / 1.76 
Standardized units 
0.30 / 0.32 / 0.37 
Figure 4, minimum effects on resident 
outcomes detectable with 90% power in two-
sided 5% tests, with design effects of 
1.25/1.5/2.0.   

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checking the daily data edits and working in conjunction with the sites to address them.  This 
data entry/data editing process is monitored by a number of standard monitoring reports that 
will be available on the website.  An audit trail is maintained which includes the date of 
change, time of change, description of data change, and the study ID of the person making the 
change. 
 
The DCC will also serve as the Reading Center for the actigraphy, Optalert and PVT datasets. 
DCC staff will perform an initial review of the files upon receipt and report any issues to the 
clinical site staff; later DCC staff will clean and merge the device data with the form data.  
 
The DCC will prepare comprehensive ‘clean’ datasets for analysis, providing the analysis-
ready files to the CCC and others as necessary, for statistical analysis purposes. The DCC will 
also ensure that any entity receiving the dataset will have a Data Use Agreement on file, 
signed by the appropriate institutional authority. The DCC will also be responsible for 
preparing a public release dataset to be housed within NHLBI’s BioLINCC (or a comparable 
public data repository) no later than 3 years after the end of the trial or 2 years after the main 
paper has been published, whichever comes first.  
1.8.3 Data Management and Study Progress 
The study website which includes a number of data management features and reports to 
enable clinical sites and study investigators to monitor data collection and study progress. 
Data Management features include a data inventory, lists of missing forms and queries by 
participant ID, and tools to resolve queries and update data via the website. Reports can be 
custom-designed to meet study needs and could include: 
 Enrollment in aggregate and by site 
 Demographics in aggregate and by site 
 Early Discontinuation in aggregate and by site 
1.8.4 Staff Training 
Site staff (physician observers, nurse data extractors and study coordinators) will be trained 
intensively in the detection of medical errors and adverse events using an established training 
protocol. Inter-rater reliability will be verified during the study. Staff will also be instructed 
on procedures for entering data into electronic data collection forms and transmitting these 
data to the DCC. Lastly, staff will be trained in the operation of the actigraph and Optalert 
devices, as well as the PVT tests. 
1.9 
PARTICIPANT RIGHTS AND CONFIDENTIALITY  
1.9.1 Institutional Review Board (IRB) Review 
This protocol and informed consent documents, and any subsequent modifications, will be 
reviewed and approved by the IRB or ethics committee responsible for oversight of each of 
the clinical sites, as well as the clinical and data coordinating centers.  
1.9.2 Informed Consent Forms 
Informed Consent documents will be maintained at individual sites and coordinators must 
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Informed Consent form will be obtained from each participant. The Informed Consent will 
describe the purpose of the study, the procedures to be followed, and the risks and benefits of 
participation and must comply with the requirements of the study site’s Institutional Review 
Board.  A copy of the Informed Consent will be given to each participant and provision of the 
copy will be documented in the study participant’s record. The DCC will ensure that all 
clinical site informed consents are consistent and include required elements.  
1.9.3 Participant Confidentiality 
1.9.3.1 Clinical Sites  
In order to protect confidentiality of the research participants as well as the patients they treat, 
both will be assigned a unique study identification number, which will be used to refer to 
them on all study forms. The list of codes linking resident-subjects’ and patients’ names and 
study IDs will be kept by each site PI on a separate password protected computer in a locked 
office at that site. Each site PI will be responsible for ensuring the security of these data. 
These identifying data will not be transmitted outside of the originating institution. Risk to 
patient confidentiality will likewise be minimized. All information will be de-identified at the 
point of data analysis. 
1.9.3.2 Data Coordinating Center 
The DCC follows standard operating procedures (SOPs) for computer system security to 
ensure the confidentiality and validity of study data.  The SOPs are designed to prevent 
unauthorized access and limit authorized access to our computer systems and are in 
compliance with established standards for Information Technology Security.  Our network is 
privately maintained, hardware fire-walled and none of the workstations or database servers 
can be directly addressed from outside the Local Area Network. Study website and database 
access requires a network domain account with appropriate account-specific permission on 
the database. All requests for new accounts and access to the database must be documented by 
a System Access Request Form signed by the project director.   
 
1.10 
COMMITTEES 
1.10.1 Steering Committee 
The Steering Committee will be responsible for all decisions concerning the scientific and 
technical conduct of the study.   It will appoint the analysis and publications committee and 
writing groups, ensuring that information from the study is disseminated in the scientific 
literature and at scientific meetings. The committee will be chaired by Dr. Czeisler and will 
include the lead site investigator from the clinical and data coordinating center and each of the 
clinical sites. The Steering Committee will have one in-person meeting on an annual basis, 
and will meet by teleconference on at least a bi-monthly basis. The Steering Committee 
consists of the following members:  
Charles A. Czeisler, PhD, MD  
Chair, PI, CCC, Brigham and Women’s Hospital  
Christoper P. Landrigan, MD, MPH  PI, CCC, Brigham and Women’s Hospital  
Katie L. Stone, PhD 
PI, DCC, California Pacific Medical Center 
 
Susan Redline, MD, MPH 
Chair, Sleep Research Network 

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Ken Wright, PhD 
PI, University of Colorado 
Gwen Erkonen, MD  
PI, University of Iowa 
Pearl Yu, MD  
PI, University of Virginia 
Phyllis Zee, MD, PhD 
PI, Northwestern University 
Sue Poynter, MD 
PI, University of Cincinnati 
Michael Twery, PhD  
 
Project Scientist, NHLBI 
 
1.10.2 Executive Committee  
An Executive Subgroup of the Steering Committee will be responsible for decisions that 
require attention between Steering Committee Meetings and for major financial, 
administrative and operational decisions. The Executive Committee will meet via 
teleconference at least monthly and will consist of the following members:  
Charles A. Czeisler, PhD, MD  
PI, CCC, Brigham and Women’s Hospital  
Christoper P. Landrigan, MD, MPH  PI, CCC, Brigham and Women’s Hospital  
Katie L. Stone, PhD 
PI, DCC, California Pacific Medical Center 
 
Michael Twery, PhD  
 
Project Scientist, NHLBI 
1.10.3 Principal Planning Group 
A planning group comprised of the Principal Investigators and project staff of both the CCC 
and DCC will be responsible for the development of study documents, including the forms, 
protocol and operations manual, as well as the day-to-day management of the trial. The 
Principal Planning Group will meet via teleconference at least monthly and will consist of the 
following members:  
Charles A. Czeisler, PhD, MD  
PI, CCC, Brigham and Women’s Hospital  
Christoper P. Landrigan, MD, MPH  PI, CCC, Brigham and Women’s Hospital  
Joshua Stephens 
CCC, Brigham and Women’s Hospital 
Katie L. Stone, PhD 
PI, DCC, California Pacific Medical Center 
 
Dana R. Kriesel, MPH 
 
PD, DCC, California Pacific Medical Center  
 
1.10.4 Working Groups 
Members of the Steering Committee will form working groups to manage and oversee 
specific aspects of the trial. These include: (1) Data Management and Data Quality; (2) 
Patient Safety and PICU Quality Outcomes; (3) Sleep, Performance and Health Outcomes; 
and (4) Education Outcomes. Working groups will meet on an as needed basis.  
1.10.5 Data and Safety Monitoring Board  
To monitor the study for the possibility that the intervention schedule has an adverse effect on 
safety, a multidisciplinary Data and Safety Monitoring Board (DSMB) comprised of 
financially disinterested members will be appointed by NHLBI, with guidance from DCC. 
The DSMB will monitor the quality and integrity of the data emerging from the proposed 
study; assess the adequacy of recruitment, compliance, follow-up and other aspects of study 
execution; and review interim analyses of the major outcomes of the trial to identify safety 
issues and make periodic recommendations on whether to continue, modify, or terminate the 
study. The DSMB will be an advisory board to NHLBI and the Steering Committee. The 
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NHLBI. The DCC will support the DSMB by preparing interim reports for review at DSMB 
meetings; and by organizing scheduled and ad hoc meetings of the DSMB as needed. Please 
see the DSMB Charter for more details.  
1.11 
CONFLICT OF INTEREST 
 
The DCC will be responsible for surveying the key personnel at each study site on an annual 
basis regarding any conflicts of interest that may have arisen. The Executive Committee will 
review the results of these annual surveys and determine if any action is necessary.  
1.12 
REFERENCES 
 
 
1.  Barger LK, Cade BE, Ayas NT, Cronin JW, Rosner B, Speizer FE, Czeisler CA. 
Extended work shifts and the risk of motor vehicle crashes among interns. N Engl J 
Med 2005;352:125-34 
 
2.  Lockley SW, Cronin JW, Evans EE, Cade BE, Lee CJ, Landrigan CP, Rothschild JM, 
Katz JT, Lilly CM, Stone PH, et al. Effect of reducing interns' weekly work hours on 
sleep and attentional failures. N Engl J Med 2004 Oct 28;351(18):1829-37 
 
3.  Landrigan CP, Rothschild JM, Cronin JW, Kaushal R, Burdick E, Katz JT, Lilly CM, 
Stone PH, Lockley SW, Bates DW, et al. Effect of reducing interns' work hours on 
serious medical errors in intensive care units. N Engl J Med 2004 Oct 
28;351(18):1838-48 
 
4.  Ayas NT, Barger LK, Cade BE, Hashimoto DM, Rosner B, Cronin JW, Speizer FE, 
Czeisler CA. Extended work duration and the risk of self-reported percutaneous 
injuries in interns. JAMA 2006 Sep 6;296(9):1055-62 
 
5.  Grantcharov TP, Bardram L, Funch-Jensen P, Rosenberg J. Laparoscopic performance 
after one night on call in a surgical department: prospective study. B.M.J. 2001 Nov 
24;323:1222-3 
 
6.  Barger LK, Ayas NT, Cade BE, Cronin JW, Rosner B, Speizer FE, Czeisler CA. 
Impact of extended-duration shifts on medical errors, adverse events, and attentional 
failures. PLoS Med 2006 Dec;3(12):e487 
 
7.  Arnedt JT, Owens J, Crouch M, Stahl J, Carskadon MA. Neurobehavioral 
performance of residents after heavy night call vs after alcohol ingestion. JAMA. 2005 
Sep 7;294(9):1025-33 
 
8.  Philibert I. Sleep loss and performance in residents and nonphysicians: a meta-analytic 
examination. Sleep 2005 Nov 1;28(11):1392-402 
 
9.  Institute of Medicine. Resident Duty Hours: Enhancing Sleep, Supervision, and 
Safety. Washington, D.C.: The National Academies Press; 2009. 1-322 p. 

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 10.  Iglehart JK. Revisiting duty-hour limits--IOM recommendations for patient safety and 
resident education. N Engl J Med 2008 Dec 18;359(25):2633-5 
 11.  ACGME. Common Program Requirements. 2010 Sep 26. 
    12.  Griffin FA, Resar RK. Global Trigger Tool for Measuring Adverse Events: IHI 
Innovation Series white paper. Cambridge, MA: Institute for Healthcare Improvement; 
2007. 
 13.  National Coordinating Council for Medication Error Reporting and Prevention (NCC 
MERP). Index for Categorizing Errors. 2009. 
 14.  Pollack MM, Ruttimann UE, Getson PR. Pediatric risk of mortality (PRISM) score. 
Crit Care Med 1988 Nov;16(11):1110-6 
 15.  Wyatt JK, Dijk DJ, Ronda JM, Jewett ME, Powell JW, Dinges DF, Czeisler CA. 
Interaction of circadian and sleep/wake homeostatic-processes modulate psychomotor 
vigilance test (PVT) performance. Sleep Res 26, 759. 1997.  
 
 16.  Zeger SL. A regression model for time series of counts. Biometrika. 1988;75(4):621-
629. 
 
 17.  Armitage P, Hills M. The two-period crossover trial. The Statistician. 1982;31(2): 
119-131.  
 
 

 
 
 
 
 
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Randomized Order Safety Trial Evaluating 
Resident Schedules  
 
A Multi-Center Trial of Limiting PGY 2&3 Resident Work  
Hours on ICU Patient Safety 
 
Principal Investigators: 
Charles A. Czeisler, PhD, MD 
Christopher P. Landrigan, MD, MPH 
Katie L. Stone, PhD 
 
Supported by: 
National Heart Lung and Blood Institute 
 
Version 1.3 
 
June 12, 2015 
 

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Table of Contents 
PROTOCOL SUMMARY ......................................................................................................... 4 
1.1 
STUDY AIMS ................................................................................................................. 5 
1.1.1 Aim 1: ............................................................................................................................ 5 
1.1.2 Aim 2: ............................................................................................................................ 5 
1.1.3 Aim 3: ............................................................................................................................ 5 
1.2 
BACKGROUND AND RATIONALE ........................................................................... 5 
1.3 
STUDY DESIGN AND INTERVENTIONS .................................................................. 6 
1.4 
SELECTION AND ENROLLMENT OF PARTICIPANTS ........................................ 67 
1.4.1 
Recruitment .............................................................................................................. 7 
1.4.2 
Randomization ......................................................................................................... 7 
1.4.3 
Preparation of subjects ............................................................................................. 7 
1.5 
STUDY PROCEDURES ................................................................................................. 7 
1.5.1 
Detection of Errors and Adverse Events ................................................................ 78 
1.5.1.1 
Continuous Observation ................................................................................... 8 
1.5.1.2 
Voluntary and solicited reports ......................................................................... 8 
1.5.1.3 
Collection of formal incident reports ................................................................ 8 
1.5.1.4 
Chart surveillance ............................................................................................. 8 
1.5.2 
Classification by severity, attribution, and preventability ..................................... 89 
1.5.3 
Identification of patient risk factors ......................................................................... 9 
1.5.4 
Measuring Sleep and Fatigue ................................................................................... 9 
1.5.4.1 
Sleep and work logs .......................................................................................... 9 
1.5.4.2 
Ambulatory physiologic monitoring ................................................................. 9 
1.5.5 
Measuring Resident Vigilance ................................................................................. 9 
1.5.5.1 
 PVT. ................................................................................................................. 9 
1.5.6 Additional Measures .................................................................................................. 910 
1.5.6.1 Self-reported attentional failures, motor vehicle crashes (MVCs), and 
percutaneous injuries ...................................................................................................... 910 
1.5.6.2 Educational Measures ........................................................................................... 10 
1.5.6.3 Collection of Salivary Samples for Subsequent Genetic Analyses .................. 1011 
1.6 
SAFETY ASSESSMENTS ........................................................................................... 11 
1.7 
STATISTICAL CONSIDERATIONS .......................................................................... 12 
1.7.1 Outcomes and Statistical Analyses .............................................................................. 12 
1.7.2 Sample Size and Minimum Detectable Effects ........................................................... 12 
1.8 
DATA COLLECTION AND QUALITY ASSURANCE ............................................. 13 
1.8.1 Data Acquisition and Transmission ............................................................................. 13 
1.8.2 Data Collection and Editing .................................................................................... 1314 
1.8.3 Data Management and Study Progress ........................................................................ 14 
1.8.4 Staff Training ............................................................................................................... 14 
1.9 
PARTICIPANT RIGHTS AND CONFIDENTIALITY ............................................... 15 
1.9.1 Institutional Review Board (IRB) Review .................................................................. 15 
1.9.2 Informed Consent Forms ............................................................................................. 15 
1.9.3 Participant Confidentiality ........................................................................................... 15 
1.9.3.1 Clinical Sites ......................................................................................................... 15 
1.9.3.2 Data Coordinating Center ..................................................................................... 15 
1.10  COMMITTEES ......................................................................................................... 1516 

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1.10.1 Steering Committee ............................................................................................... 1516 
1.10.2 Executive Committee ................................................................................................ 16 
1.10.3 Principal Planning Group .......................................................................................... 16 
1.10.4 Working Groups .................................................................................................... 1617 
1.10.5 Data and Safety Monitoring Board ............................................................................ 17 
1.11  CONFLICT OF INTEREST .......................................................................................... 17 
1.12  REFERENCES .............................................................................................................. 17 
 
 
 
 
 
 
 

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PROTOCOL SUMMARY 
 
Objective: 
To conduct a multi-center randomized crossover trial in six pediatric ICUs staffed by PGY2 
and PGY3 residents to compare the effectiveness and safety of a sleep and circadian science-
based (SCS) intervention schedule with a traditional schedule that includes frequent shifts of 
24 hours or longer. 
 
Study Population: 
Second and third year (PGY2 and PGY3) residents 
 
Study Design: 
Multi-center randomized crossover trial 
 
Interventions: 
Sleep and circadian science-based intervention schedule versus a traditional schedule 
 
Primary outcomes: 
Resident-related preventable adverse events and near misses 
 
Secondary Outcomes: 
ICU-wide preventable adverse events and near misses 
Resident neurobehavioral performance and predicted driving safety 
 
Study Duration: 
12 months (4 month wash-in period followed by 8 months of data collection) 

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1.1 
STUDY AIMS 
1.1.1 Aim 1: 
To test the hypothesis that PGY2&3 residents working on an SCS intervention schedule will 
make significantly fewer harmful medical errors (preventable adverse events) and other serious 
medical errors (near misses) while caring for ICU patients than residents working on a 
traditional schedule; (primary endpoints: resident-related preventable adverse events and near 
misses) 
 
1.1.2 Aim 2:  
To test the hypothesis that rates of harmful medical errors (preventable adverse events) and 
other serious medical errors (near misses) throughout the ICU (i.e., those involving and those 
not involving residents) will be lower in ICUs when PGY2&3 residents work on an SCS 
intervention schedule than when residents work on a traditional schedule; (major secondary 
endpoints: ICU-wide preventable adverse events and near misses) 
 
1.1.3 Aim 3: 
To test the hypothesis that resident physicians’ risk of neurobehavioral performance failures 
and motor vehicle crashes – as assessed through drive diaries, End of Rotation Survey and 
simple visual reaction time tasks [Psychomotor Vigilance Task (PVT) lapses] – will be lower 
on the SCS intervention schedule than on the traditional schedule. (major secondary endpoints: 
resident neurobehavioral performance and predicted driving safety) 
 
1.2 
BACKGROUND AND RATIONALE 
 
Sleep deficiency and circadian disruption degrade human alertness and performance both in 
laboratory and occupational settings. Over the past decade, a series of studies have found that 
first-year residents (interns; PGY1s) working recurrent extended duration shifts (>24 hours) 
make more serious medical errors than do those working shifts of <16 consecutive hours; 
moreover, PGY1s working extended duration shifts suffer more injuries on the job, and have 
an increased risk of motor vehicle crashes (MVCs) on the drive home from work.(1-8) In 2009, 
after a year-long comprehensive study, the Institute of Medicine (IOM) concluded that while it 
remained unclear whether resident sleep deprivation led to patient harm, “the scientific 
evidence base establishes that human performance begins to deteriorate after 16 hours of 
wakefulness.”(9;10) They consequently called for the elimination of all resident physician 
shifts without sleep over 16 consecutive hours. 
 
In response, beginning in July 2011, the Accreditation Council for Graduate Medical Education 
(ACGME) limited interns to no more than 16 consecutive hours of work; second year (PGY2) 
and higher residents, however, will continue to work for up to 28 consecutive hours.(11) In 
choosing not to more substantively limit the hours of PGY2 and higher residents – who 
represent approximately 80% of all physicians-in-training – the ACGME indicated that in its 
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In this study, we seek to conclusively address two knowledge gaps: 1) the lack of data on the 
relationship between PGY2 and higher sleep deprivation and patient safety; and 2) the lack of 
data on the relationship between resident sleep deprivation and preventable patient injuries. 
 
1.3 
STUDY DESIGN AND INTERVENTIONS 
 
The study is a clustered randomized controlled trial to evaluate the effectiveness of eliminating 
residents’ traditional 24-hour shifts in ICUs. The trial will take place in 6 academic medical centers 
nationwide, in three waves of two centers each.(Figure 1) One of each pair of units will initially be 
randomly assigned to the traditional schedule (i.e., in which overnight shifts of 24-28 hours continue 
to occur every 4 nights), or to the SCS intervention schedule (i.e., in which residents are limited to 16 
consecutive work hours; sleep before night duty is promoted; and time off is arranged to allow 
recovery from sleep debt.) 
Our planned timeline will be as follows: after a 2 month planning and startup period, during which 
staff will be recruited and hired, the intervention will be implemented in one randomly selected PICU 
in study wave 1; the traditional schedule will continue in the other PICU.  There will be a 4-month 
wash-in period, after which time 8 months of data collection will take place in intervention (in black, 
Figure 1) and traditional (in blue) ICUs. After 8 months of data collection, the units will cross over 
(traditional to intervention schedule; intervention to traditional). Following another 4-month wash-in 
period, there will be 8 additional months of data collection. Study sites in waves two and three will 
follow the same pattern. Of note, each intervention period will be scheduled to occur entirely within 
a single academic year, and will be preceded or followed (12 months apart) by a control period that 
will also occur entirely within an academic year.  
 
Figure 1. Timeline 
 
 
 
 
 
1.4 
SELECTION AND ENROLLMENT OF PARTICIPANTS  
 

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All second and third year residents at the six clinical centers will be invited to enroll in the study. The 
only exclusion criteria is that the resident is at least 21 years of age. Four to eight residents will be 
recruited per month at each clinical center for total of approximately 50 residents per site and 
approximately 300 subjects study-wide.  
1.4.1 Recruitment 
Sites will submit a waiver of informed consent for the collection of patient data, but will obtain 
residents’ written informed consent to observe them, and collect resident-specific data. 
Working with program directors at each hospital, the Principal Investigators will make 
presentations each year to all residents to describe our study and request volunteer participants. 
Residents are free not to participate in the study; if they choose not to participate, they will not 
be followed by observers and no other data will be collected from them, but the unit schedule 
will proceed on the traditional or SCS intervention schedule as planned. 
1.4.2 Randomization 
The intervention will be implemented in one randomly assigned study site in each of the three 
waves and the second site will remain on the traditional schedule. After 8 months of data 
collection, the units will cross over (traditional to intervention schedule; intervention to traditional). 
The Data Coordinating Center (DCC) will be responsible for randomly assigning sites to their initial 
study arm.  
1.4.3 Preparation of subjects 
Before the start of each study, volunteers will receive a detailed explanation of the procedures 
involved in the study. They will also attend an educational seminar prior to the implementation of the 
intervention schedule designed to provide an overview of sleep and circadian science, and to convey 
the importance of complying with the protocol by attempting to sleep prior to night shifts. They will 
be asked to complete a baseline survey, which will include the Sleep Disorders and Berlin Sleep 
Questionnaires. 
1.5 
STUDY PROCEDURES 
 
The study will take place in pediatric intensive care units (PICUs). In general, subjects will 
continue to carry out their normal activities and responsibilities when working either the 
intervention or traditional schedule. Throughout the PICU rotations, subjects will complete a 
daily sleep diary and wear actiwatches, described further below, to validate the results of self-
reported sleep..  They will also periodically complete psychomotor vigilance tests (PVTs) to 
monitor their vigilance.  At the completion of their rotations, all subjects will complete an End 
of Rotation survey. For every experimental intervention, there will be written protocols and 
checklists used to insure uniformity in the execution of standard procedures. 
1.5.1 Detection of Errors and Adverse Events 
We will use a very intensive, four-pronged data collection approach to comprehensively 
measure rates of all errors and adverse events.  

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1.5.1.1 Continuous Observation  
A team of five physician research associates will conduct direct observation of resident subjects 
working in the units, 24 hours per day, 7 days per week. The observers will share this 
responsibility, working in eight-hour shifts. All suspected adverse events and errors will be 
documented on tablet-based data forms, and transmitted to the research nurse, who will gather 
follow-up data on them while conducting his or her daily chart reviews, as described below.  
The observer will also record and classify all medical activities in which the study subject 
engages, including but not limited to performance of procedures, test and medication ordering, 
and test interpretation. Suspected adverse events and incidents will be identified and classified. 
Follow-up of all suspected adverse events and errors detected by the observers will be 
performed by the nurse data extractors, who will collect additional information. 
 
1.5.1.2 Voluntary and solicited reports 
Forms will be made available and prominently posted in the ICUs to facilitate voluntary 
reporting of possible errors and events by nurses and other clinical staff. Chart reviewers will 
also request reports from staff of errors and adverse events 5 days per week. Any reported error 
or event will be pursued by the nurse data extractors, who will collect additional information. 
1.5.1.3 Collection of formal incident reports 
In each hospital, formal incident reports will be collected if permitted; if any institutions will 
not allow access to these data, we will request that duplicate study reports be filed by clinical 
staff on our study units when they complete formal reports. In addition, in any hospitals with 
computerized adverse event detection systems, the computerized AE monitors will also be 
interrogated for study-unit events. Nurse data extractors will collect additional information on 
each incident identified. 
1.5.1.4 Chart surveillance 
The nurse data extractors will serve as the focal point for data collection and organization, and 
will follow up and review all data collected by observers, reported by staff, and detected via 
incident reporting systems. In addition to coordinating collection from other sources, reviewers 
will examine all orders and charts 5 days per week; a focused version of the Institute for 
Healthcare Improvement (IHI) Global Trigger Tool (consisting of the intensive care module, 
cares module, and medication module triggers)(12) will be used to increase the sensitivity of 
adverse event detection. Reviews on Monday will include a review of the weekend. Data 
collected for each incident will include a description and classification of the event, patient 
information, services and personnel involved, and additional work resulting from the event. 
Medication incidents will further include name, dose, route and category of the drug involved. 
1.5.2 Classification by severity, attribution, and preventability 
Physician observers and research nurses will identify suspected errors and adverse events. Two 
independent physician reviewers will subsequently classify events as errors, potential adverse 
events (near misses), or adverse events. All events will be rated on severity using the modified 
NCC-MERP scale.(12;13) Preventability will be rated using a four point Likert scale. 
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will be re-rated by a third reviewer. Pre-discussion inter-rater reliability will be evaluated with 
the Kappa statistic.  
1.5.3 Identification of patient risk factors 
Clinical and demographic data for all patients admitted to study units will be collected by the research 
nurses from patient records and institutional administrative databases during lulls in unit activity. 
Severity of illness will be assessed using ICD-9 codes.  
1.5.4 Measuring Sleep and Fatigue 
In addition to data on patient safety, we will collect data on residents’ sleep and work hours 
using the methods described below.  
1.5.4.1 Sleep and work logs 
A diary of sleep and wake times will be maintained by the research volunteers. A post-sleep 
questionnaire will be completed immediately following wake time from all sleep episodes and 
will provide information on subjective evaluation of sleep onset, duration, consolidation, 
quality, and wakefulness during sleep, as well as daily work hours. Our sleep and work logs 
have previously been validated; hours of sleep and work reported using this methodology have 
a high correlation with polysomnographically-validated total sleep time (r=0.94) as well as 3rd-
party documented work hours (r=0.98).(2) 
1.5.4.2 Ambulatory physiologic monitoring 
To further validate reported sleep times in this study, wrist activity and ambient light levels will 
be monitored for the entire duration of residents’ rotations with a solid-state, portable data 
collection device (Motionlogger BASIC; Ambulatory Monitoring, Inc., Ardsley, NY). The 
Motionlogger recorder is a small wrist worn device that measures activity and ambient light 
exposure; it is waterproof and powered by a 3V, 150 mAmp-hr Lithium Manganese battery that 
has a lifetime of 60 days. Data are preserved if the battery expires.  
1.5.5 Measuring Resident Vigilance  
1.5.5.1  PVT.  
In the proposed study, we will also have resident physician subjects complete Psychomotor Vigilance 
Testing – an established metric of vigilance that is sensitive to sleep deprivation and circadian 
misalignment (14) – during one shift per week, every five hours.  Completing the PVT requires 10 
minutes and provides data on vigilance that will be used to derive an independent measure of 
neurobehavioral performance while subjects are on the job. Subjects will also be asked to complete 
the Karolinska Sleepiness Scale (KSS), a self-report scale that measures alertness, before and after 
each test. 
1.5.6 Additional Measures 
1.5.6.1 Self-reported attentional failures, motor vehicle crashes (MVCs), and percutaneous 
injuries 
Through end-of-rotation surveys, we will also collect data on residents’ self-reported attentional 
failures, MVCs, near-miss MVCs, and percutaneous injuries using the instruments we 

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previously developed for use in our national cohort study. Any reported MVCs and 
percutaneous injuries will be validated by the collection of objective data (e.g. police reports, 
repair bills, etc. for MVCs), as was done in our cohort study.(1;4) When MVCs occur on the 
commute to and from work, we will also have drive diary data available. We believe that 
collecting MVC and percutaneous data is important given their implications for resident safety, 
but with 300 anticipated subjects in the study, and the relative infrequency of these occupational 
injuries,(1;4) we will have power to detect an effect of the intervention on these outcomes only 
if they are reduced more than two-fold. As such, analysis of these outcomes will be considered 
exploratory. 
1.5.6.2 Educational Measures 
As part of the study, participants will have the option of enrolling in an online educational 
platform entitled OPENPediatrics. OPENPediatrics is a free, open access, peer-reviewed, 
digital learning platform that utilizes the latest in innovative technology to provide robust 
continuing medical education. OPENPediatrics is sponsored through Boston Children’s 
Hospital and IBM and located at Boston Children’s Hospital (Website: 
http://openpediatrics.org). Through a feature entitled the Learning Pathways, participants will 
have access to the ROSTERS curriculum, or a similar ICU learning curriculum approved by 
each participant’s hospital. This curriculum is comprised of 18 lessons by educational experts. 
Each lesson begins with a pre-test followed by a didactic or procedural demonstration video 
and concludes with a post-test. This unique format will allow for asynchronous learning, so 
that participants can complete their educational lessons outside the hospital and apply their 
knowledge during on-duty hours. OPENPediatrics’ robust analytics will allow research staff 
to track each participant’s submissions as they progress through the curriculum. Pre-test and 
post-test scores as well as duration in each module will allow researchers to note the 
educational gains made throughout the curriculum, and compare each participant’s results in 
the control and Sleep and Circadian Science-based (SCS) intervention arms. A vigorous set of 
security measures will allow the analytic data from the application to be securely passed from 
the application to the data collection program, Cognos. As standard practice for the 
OPENPediatrics data storage procedures this data will be stored on IBM’s secure servers, and 
IBM’s analytic department will control access to this data. All residents in the unit will have 
access to the platform so no delineation between non subject residents and subject residents 
can be made by anyone except each site coordinator who will maintain the only identified list 
of subjects for the site. Resident data specific to each site will be sent from OPENPediatrics to 
each site coordinator; the site coordinator will then delete all data associated with non-subject 
residents. These measures are being taken so only site coordinators have knowledge of which 
data sets are associated with resident subjects. The team will work with the site PI to de-
identify the data by removing the user’s name/email. The data will only be stored on 
password-protected computers. Data will only be reported as de-identified, aggregated data. 
On their end-of-rotation surveys, they will report their impressions of their educational 
experience. 
1.5.6.3 Collection of Salivary Samples for Subsequent Genetic Analyses 
In light of the emerging science exploring the genetic predictors of susceptibility to sleep loss 
and circadian misalignment, salivary samples will be collected to measure genetic modifiers of 
the SCS intervention’s effects. Unfortunately, the limited number of subjects (~300) being 

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studied in this proposed trial precludes conducting genome-wide association studies to 
determine what genes may convey an increased risk of fatigue-related error, and as yet, no 
candidate gene has been independently verified to convey altered vulnerability to the 
performance-impairment associated with sleep deprivation. However, given that this study will 
gather unprecedented data on sleep, performance, and safety, and the likelihood that one or 
more candidate genes will be verified in the near future, we will collect samples and analyze 
the DNA of all participants who agree to participate in a future genetic evaluation. These 
specimens will then be available at a later time to evaluate whether candidate genes verified to 
affect vulnerability to sleep loss or of making an error that leads to an AE. 
1.6 
SAFETY ASSESSMENTS 
 
1.6.1 Patient Safety 
The study will be looking for the occurrence of adverse events that occur in ICU care; some are 
preventable, and some are not. Data on adverse events will be systematically collected and 
reviewed by the DSMB after each 8 month data collection period. Rates of adverse events will 
be compared and the DSMB will subsequently make periodic recommendations on whether to 
continue, modify, or terminate the study. From prior studies, we have found that the cause of 
detected adverse events in hospitals cannot in most cases be reliably assigned on a case by case 
basis (e.g., was acquisition of a catheter-related bloodstream infection due to a resident’s work 
schedule? A nurse error? Another cause?), so we anticipate that there will not be discrete, 
individual adverse events that would modify an assessment of the safety of the intervention or 
traditional work schedule’s risks; rather, we expect that through epidemiologic methods, we 
will obtain useful data on the safety of the intervention vs. traditional work schedules, and act 
as needed. However, if there are discrete events that clinical staff or study investigators believe 
are attributable to either the intervention of traditional work schedule, these events will be 
brought to the attention of the DSMB for review and action as needed.  
 
1.6.2 Resident Safety 
As part of this study, we will ask resident subjects questions about depression, including 
questions about suicidal thoughts and plans, motor vehicle incidents, drowsy driving, including 
falling asleep at the wheel, and occupational exposures. The Data Coordinating Center for the 
study reviews survey responses, and if responses indicate suicidality, 3 or more occupational 
exposure reports, and/or motor vehicle crashes in which the damage was >$1000 and/or 
drowsiness was reported as a factor, the study principle investigator will be asked to follow up 
with the resident subject. Near misses will not be followed up on. Additionally, initial reports 
of falling asleep at the wheel will trigger a follow up with by each site’s research study 
coordinator; 3 or more responses of falling asleep while driving will trigger a follow up by each 
site’s principle investigator. Specifically in regards to questions concerning suicide, if resident 
subjects respond to the question “Over the past two weeks, how often have you thought about 
or wanted to commit suicide?” with “Some of the time,” “Most of the time,” or “All of the 
time,” regardless of whether they respond “Yes” or “No” to “Do you have a plan?”, the 
following message will appear on the form:  “Your response to the previous questions causes 
us to be concerned for your welfare. All reports of suicide ideation will be reported to your site 
PI, who will then initiate your institution’s protocols for timely intervention and action, in 
compliance with their organizational rules and standards.” These criteria were discussed and 

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decided on by the Clinical Coordinating Center, Steering Committee, and voted on and 
approved by the Data Safety Monitoring Board for this protocol.  
1.7 
STATISTICAL CONSIDERATIONS 
1.7.1 Outcomes and Statistical Analyses 
We will compare resident-related (Specific Aim 1) and total (Specific Aim 2) rates of harmful 
medical errors (preventable adverse events) on the two schedules. As a secondary measure, 
rates of non-harmful serious medical errors (i.e., near misses) will also be compared. In an 
intention-to-treat analysis, rates will be compared by schedule using Poisson models with 
compound symmetric working correlation and robust standard errors to account for both over-
dispersion and clustering by clinical center (15), and the number of patient-days at risk in each 
center and period included as so-called offset. The models will control for period effects and 
will be used to assess treatment-period interaction, a standard check with crossover trials(16). 
 
In addition, actigraphy and sleep diaries will be used to ascertain the minimum and mean 
number of hours of sleep obtained per night, total sleep time, wake after sleep onset (WASO; 
minutes), and sleep efficiency. We will also compare performance based on results captured by 
the Psychomotor Vigilance Test (PVT).  Specifically, we will compare the the numbers of 
lapses in vigilance, defined as a reaction time >500 ms, on the PVT. This Intention-to-treat 
comparison will be made using linear mixed models for repeated measures, with nested random 
effects to account for clustering within clinical center and residents12. Outcomes will be 
normalized as necessary; generalized linear mixed models appropriate for other outcome 
distributions, and/or bootstrap standard errors will be used if adequate normalization cannot be 
achieved. In preliminary analyses, we will assess the comparability of the residents in the 
intervention and control periods in terms of age, gender, post-graduate year (PGY2 vs PGY3), 
as well as other potential confounders of the intervention.  If imbalances are found, we will 
conduct sensitivity analyses in which we flexibly adjust for the potential confounders.   
1.7.2 Sample Size and Minimum Detectable Effects 
Based on the Intern Sleep and Patient Safety Study, during which 2,203 patient-days were 
accrued under both schedules over a total of 8.5 months at a single center with 2 ICUs totaling 
20 
beds, 
we 
estimate 
that 
approximately 
46,080 patient-
days 
will 
be 
accrued 
across 
the six centers in 
this study, each 
contributing an 
observation 
period 
of 
8 
months on each 
schedule, with an average census of 16 patients, or 80% of an average 20 beds. Assuming that 
the baseline error rates per-patient day on the standard schedule are the same as those observed 
Serious medical 
errors 
Resident-related 
rate per 1000 
patient-days 
MD-RRR with 
Scale Factor of 
1.0 (2.0) 
Unit rate per 
1000 patient-
days 
MD-RRR with 
Scale Factor of 
1.0 (2.0) 
overall 
136.0 
8.0% (11.2%) 
193.2 
6.7% (9.4%) 
intercepted 
70.3 
 11.0% (15.5%) 
95.1 
9.5% (13.3%) 
non-intercepted 
44.8 
13.8% (19.2%) 
59.5 
11.9% (16.7%) 
Preventable AEs 
20.9 
19.8% (27.5%) 
38.6 
14.8% (20.6%) 
Figure 3, power table. Minimum detectable relative rate reductions (MD-RRRs) 
detectable with 90 percent power in two-sided tests (with alpha of 5%) for serious 
medical errors, by sub-type of error, using Poisson models. The primary outcomes of 
interest, resident-related and total preventable AEs, are bolded. 

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in the Intern Sleep and Patient Safety Study, the new sample will provide 90% power to detect 
relative rate reductions (MD-RRRs) on the sleep and circadian science-based (SCS) 
intervention schedule as shown in Figure 3. Estimates are shown first assuming a scale factor 
of 1.0, corresponding to a Poisson distribution, while conservative estimates assuming an over-
dispersed Poisson distribution with a scale factor of 2.0, are shown in parentheses. For overall 
serious medical errors, we will have 90% power to detect reductions in both resident-related 
and unit error rates of 7-11%; MD-RRRs for intercepted and non-intercepted medical errors 
will be between 9.5 and 19%.  Even for the least frequent outcome but that of greatest interest, 
resident-related preventable AEs, we will have 90% power to detect a relative reduction of 
19.8% if the distribution is Poisson, and 27.5% under our conservative assumptions about over-
dispersion. The actual reductions seen in our preliminary study were larger than these thresholds 
in each sub-category of resident-related serious errors, including resident-related preventable 
adverse events.  Thus, we expect to be adequately powered to draw definitive conclusions 
regarding the effectiveness of the SCS schedule intervention.  In assessing interaction/period 
interactions, MD-RRRs will be fourfold larger than the main intervention effects.  However, 
because residents will participate in at most one period, the potential for carryover effects is 
much smaller than in most crossover studies. 
 
In addition, for sleep and work hours as well as PVT results, we estimate the expected sample of 300 
residents will provide 90% power in 2-sided tests with alpha of 5% to detect standardized between-
group differences of 0.30 to 0.37 standard deviations of the outcome, depending on the design effect 
due to clustering within centers and residents; 
calculations are shown in Figure 4 for minimum 
detectable effects (MDEs) for sleep and work hours, 
based on standard deviations observed for sleep and 
work hours observed in the ICU pilot study conducted 
at Brigham and Women’s Hospital. Because this pilot 
study did not collect data on other sleep outcomes (e.g. 
WASO, sleep efficiency) or the performance outcomes 
(PVT), the standardized units are also shown in Figure 4. These calculations show that the study will 
be powered to detect small-to-moderate intervention effects on these outcomes, even if the design 
effect is as large as 2.  
1.8 
DATA COLLECTION AND QUALITY ASSURANCE  
1.8.1 Data Acquisition and Transmission  
The DCC will develop a front-end component for data entry and transmission. Data would be 
entered at remote sites on secure mobile computing devices and transmitted a minimum of once 
a day via secure transfer. Data received will be automatically imported into SQL tables and 
integrated into our standard data system. Data will be available for review/updating via the 
standard study website within 24-48 business hours. The DCC will create and maintain a 
comprehensive programmer’s guide for all the data systems it provides.  
1.8.2 Data Collection and Editing 
Capturing data electronically will reduce the risk of missing data. Furthermore, edits checks 
may be built into the instruments to flag out of range or inconsistent data. Further custom edit 
Outcome 
MDE  
Sleep hours (weekly) 
1.75 / 1.92 / 2.21 
Work hours (weekly) 
1.39 / 1.53 / 1.76 
Standardized units 
0.30 / 0.32 / 0.37 
Figure 4, minimum effects on resident 
outcomes detectable with 90% power in two-
sided 5% tests, with design effects of 
1.25/1.5/2.0.   

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checks will be written and run on data received at the DCC. Each hour, the cumulative study 
data is subjected to these custom edits to ensure completeness, consistency and validity of the 
data.  The results of the error-checking procedures are posted to the study website, which the 
study staff will check daily to both confirm that the DCC has successfully received all of the 
transmitted forms and to address errors that have been detected by the edit system.  The Project 
Manager and other Clinical Coordinating Center (CCC) staff will be responsible for checking 
the daily data edits and working in conjunction with the sites to address them.  This data 
entry/data editing process is monitored by a number of standard monitoring reports that will be 
available on the website.  An audit trail is maintained which includes the date of change, time 
of change, description of data change, and the study ID of the person making the change. 
 
The DCC will also serve as the Reading Center for the actigraphy and PVT datasets. DCC 
staff will perform an initial review of the files upon receipt and report any issues to the 
clinical site staff; later DCC staff will clean and merge the device data with the form data.  
 
The DCC will prepare comprehensive ‘clean’ datasets for analysis, providing the analysis-
ready files to the CCC and others as necessary, for statistical analysis purposes. The DCC will 
also ensure that any entity receiving the dataset will have a Data Use Agreement on file, 
signed by the appropriate institutional authority. The DCC will also be responsible for 
preparing a public release dataset to be housed within NHLBI’s BioLINCC (or a comparable 
public data repository) no later than 3 years after the end of the trial or 2 years after the main 
paper has been published, whichever comes first.  
1.8.3 Data Management and Study Progress 
The study website which includes a number of data management features and reports to enable 
clinical sites and study investigators to monitor data collection and study progress. Data 
Management features include a data inventory, lists of missing forms and queries by participant 
ID, and tools to resolve queries and update data via the website. Reports can be custom-
designed to meet study needs and could include: 
 Enrollment in aggregate and by site 
 Demographics in aggregate and by site 
 Early Discontinuation in aggregate and by site 
1.8.4 Staff Training 
To ensure inter-rater reliability, the physician observers and research nurses will undergo 
training in the detection of medical errors and adverse events prior to observing residents. The 
training will include evaluation of test cases designed to calibrate the observers’ assessments. 
At least twice during each 8 month period of data collection, for each wave of sites, the DCC 
will examine the rates of events by observer at each of the sites to determine if there is 
significant variability. Re-training of physician observers will occur as needed to ensure 
consistent reporting of suspected medical errors across staff and sites. Documentation of the 
analyses of event rates as well as the staff training will be maintained by the DCC. Staff will 
also be instructed on procedures for entering data into electronic data collection forms and 
transmitting these data to the DCC. Lastly, staff will be trained in the operation of the actigraphs 
as well as administration of the PVT tests. 

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1.9 
PARTICIPANT RIGHTS AND CONFIDENTIALITY  
1.9.1 Institutional Review Board (IRB) Review 
This protocol and informed consent documents, and any subsequent modifications, will be 
reviewed and approved by the IRB or ethics committee responsible for oversight of each of the 
clinical sites, as well as the clinical and data coordinating centers.  
1.9.2 Informed Consent Forms 
Informed Consent documents will be maintained at individual sites and coordinators must 
ensure that they are using an up-to-date, IRB approved version of the consent form.  A signed 
Informed Consent form will be obtained from each participant. The Informed Consent will 
describe the purpose of the study, the procedures to be followed, and the risks and benefits of 
participation and must comply with the requirements of the study site’s Institutional Review 
Board.  A copy of the Informed Consent will be given to each participant and provision of the 
copy will be documented in the study participant’s record. The DCC will ensure that all clinical 
site informed consents are consistent and include required elements.  
1.9.3 Participant Confidentiality 
1.9.3.1 Clinical Sites  
In order to protect confidentiality of the research participants as well as the patients they treat, 
both will be assigned a unique study identification number, which will be used to refer to them 
on all study forms. The list of codes linking resident-subjects’ and patients’ names and study 
IDs will be kept by each site PI on a separate password protected computer in a locked office 
at that site. Each site PI will be responsible for ensuring the security of these data. These 
identifying data will not be transmitted outside of the originating institution. Risk to patient 
confidentiality will likewise be minimized. All information will be de-identified at the point of 
data analysis. 
1.9.3.2 Data Coordinating Center 
The DCC follows standard operating procedures (SOPs) for computer system security to ensure 
the confidentiality and validity of study data.  The SOPs are designed to prevent unauthorized 
access and limit authorized access to our computer systems and are in compliance with 
established standards for Information Technology Security.  Our network is privately 
maintained, hardware fire-walled and none of the workstations or database servers can be 
directly addressed from outside the Local Area Network. Study website and database access 
requires a network domain account with appropriate account-specific permission on the 
database. All requests for new accounts and access to the database must be documented by a 
System Access Request Form signed by the project director.   
 
1.10 
COMMITTEES 
1.10.1 Steering Committee 
The Steering Committee will be responsible for all decisions concerning the scientific and 
technical conduct of the study.   It will appoint the analysis and publications committee and 

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writing groups, ensuring that information from the study is disseminated in the scientific 
literature and at scientific meetings. The committee will be chaired by Dr. Czeisler and will 
include the lead site investigator from the clinical and data coordinating center and each of the 
clinical sites. The Steering Committee will have one in-person meeting on an annual basis, and 
will meet by teleconference on at least a bi-monthly basis. The Steering Committee consists of 
the following members:  
Charles A. Czeisler, PhD, MD  
Chair, PI, CCC, Brigham and Women’s Hospital  
Christoper P. Landrigan, MD, MPH  PI, CCC, Brigham and Women’s Hospital  
Katie L. Stone, PhD 
PI, DCC, California Pacific Medical Center 
 
Susan Redline, MD, MPH 
Chair, Sleep Research Network 
Ken Wright, PhD 
PI, University of Colorado 
Jeffrey Segar, MD  
PI, University of Iowa 
John McGuire, MD 
PI, Seattle Children’s Hospital 
Pearl Yu, MD  
PI, University of Virginia 
Sue Poynter, MD 
PI, University of Cincinnati 
Phyllis Zee, MD, PhD 
PI,  
Robert Smith, PhD 
Project Scientist, NHLBI 
 
1.10.2 Executive Committee  
An Executive Subgroup of the Steering Committee will be responsible for decisions that 
require attention between Steering Committee Meetings and for major financial, 
administrative and operational decisions. The Executive Committee will meet via 
teleconference at least monthly and will consist of the following members:  
Charles A. Czeisler, PhD, MD  
PI, CCC, Brigham and Women’s Hospital  
Christoper P. Landrigan, MD, MPH  PI, CCC, Brigham and Women’s Hospital  
Katie L. Stone, PhD 
PI, DCC, California Pacific Medical Center 
 
Robert Smith, PhD 
 
 
Project Scientist, NHLBI 
1.10.3 Principal Planning Group 
A planning group comprised of the Principal Investigators and project staff of both the CCC 
and DCC will be responsible for the development of study documents, including the forms, 
protocol and operations manual, as well as the day-to-day management of the trial. The 
Principal Planning Group will meet via teleconference at least monthly and will consist of the 
following members:  
Charles A. Czeisler, PhD, MD  
PI, CCC, Brigham and Women’s Hospital  
Christoper P. Landrigan, MD, MPH  PI, CCC, Brigham and Women’s Hospital  
Conor O’Brien 
CCC, Brigham and Women’s Hospital 
Katie L. Stone, PhD 
PI, DCC, California Pacific Medical Center 
 
Dana R. Kriesel, MPH 
 
PD, DCC, California Pacific Medical Center  
 
1.10.4 Working Groups 
Members of the Steering Committee will form working groups to manage and oversee 
specific aspects of the trial. These include: (1) Data Management and Data Quality; (2) 
Patient Safety and PICU Quality Outcomes; (3) Sleep, Performance and Health Outcomes; 
and (4) Education Outcomes. Working groups will meet on an as needed basis.  

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1.10.5 Data and Safety Monitoring Board  
To monitor the study for the possibility that the intervention schedule has an adverse effect on 
safety, a multidisciplinary Data and Safety Monitoring Board (DSMB) comprised of financially 
disinterested members was appointed by NHLBI, with guidance from DCC. The board is 
comprised of five members with expertise in pediatric intensive care, pediatric critical care, 
sleep medicine, clinical trial design and biostatistics, bioethics, healthcare quality and outcomes 
research. The DSMB will monitor the quality and integrity of the data emerging from the 
proposed study; assess the adequacy of recruitment, compliance, follow-up and other aspects 
of study execution; and review interim analyses of the major outcomes of the trial to identify 
safety issues and make periodic recommendations on whether to continue, modify, or terminate 
the study. The DSMB will be an advisory board to NHLBI and the Steering Committee. The 
DSMB will work under a Charter that will be developed by the DCC, working in tandem with 
NHLBI. The DCC will support the DSMB by preparing interim reports for review at DSMB 
meetings; and by organizing scheduled and ad hoc meetings of the DSMB as needed. Please 
see the DSMB Charter for more details.  
1.11 
CONFLICT OF INTEREST 
 
The DCC will be responsible for surveying the key personnel at each study site on an annual 
basis regarding any conflicts of interest that may have arisen. The Executive Committee will 
review the results of these annual surveys and determine if any action is necessary.  
1.12 
REFERENCES 
 
 
1.  Barger LK, Cade BE, Ayas NT, Cronin JW, Rosner B, Speizer FE, Czeisler CA. 
Extended work shifts and the risk of motor vehicle crashes among interns. N Engl J 
Med 2005;352:125-34 
 
2.  Lockley SW, Cronin JW, Evans EE, Cade BE, Lee CJ, Landrigan CP, Rothschild JM, 
Katz JT, Lilly CM, Stone PH, et al. Effect of reducing interns' weekly work hours on 
sleep and attentional failures. N Engl J Med 2004 Oct 28;351(18):1829-37 
 
3.  Landrigan CP, Rothschild JM, Cronin JW, Kaushal R, Burdick E, Katz JT, Lilly CM, 
Stone PH, Lockley SW, Bates DW, et al. Effect of reducing interns' work hours on 
serious medical errors in intensive care units. N Engl J Med 2004 Oct 
28;351(18):1838-48 
 
4.  Ayas NT, Barger LK, Cade BE, Hashimoto DM, Rosner B, Cronin JW, Speizer FE, 
Czeisler CA. Extended work duration and the risk of self-reported percutaneous 
injuries in interns. JAMA 2006 Sep 6;296(9):1055-62 
 
5.  Grantcharov TP, Bardram L, Funch-Jensen P, Rosenberg J. Laparoscopic performance 
after one night on call in a surgical department: prospective study. B.M.J. 2001 Nov 
24;323:1222-3 

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6.  Barger LK, Ayas NT, Cade BE, Cronin JW, Rosner B, Speizer FE, Czeisler CA. 
Impact of extended-duration shifts on medical errors, adverse events, and attentional 
failures. PLoS Med 2006 Dec;3(12):e487 
 
7.  Arnedt JT, Owens J, Crouch M, Stahl J, Carskadon MA. Neurobehavioral 
performance of residents after heavy night call vs after alcohol ingestion. JAMA. 2005 
Sep 7;294(9):1025-33 
 
8.  Philibert I. Sleep loss and performance in residents and nonphysicians: a meta-analytic 
examination. Sleep 2005 Nov 1;28(11):1392-402 
 
9.  Institute of Medicine. Resident Duty Hours: Enhancing Sleep, Supervision, and 
Safety. Washington, D.C.: The National Academies Press; 2009. 1-322 p. 
 10.  Iglehart JK. Revisiting duty-hour limits--IOM recommendations for patient safety and 
resident education. N Engl J Med 2008 Dec 18;359(25):2633-5 
 11.  ACGME. Common Program Requirements. 2010 Sep 26. 
    12.  Griffin FA, Resar RK. Global Trigger Tool for Measuring Adverse Events: IHI 
Innovation Series white paper. Cambridge, MA: Institute for Healthcare Improvement; 
2007. 
 13.  National Coordinating Council for Medication Error Reporting and Prevention (NCC 
MERP). Index for Categorizing Errors. 2009. 
 14.  Wyatt JK, Dijk DJ, Ronda JM, Jewett ME, Powell JW, Dinges DF, Czeisler CA. 
Interaction of circadian and sleep/wake homeostatic-processes modulate psychomotor 
vigilance test (PVT) performance. Sleep Res 26, 759. 1997.  
 
 15.  Zeger SL. A regression model for time series of counts. Biometrika. 1988;75(4):621-
629. 
 
 16.  Armitage P, Hills M. The two-period crossover trial. The Statistician. 1982;31(2): 
119-131.  
 
 

 
1 
 
Modifications to the original ROSTERS protocol: 
Section 1.1.3 Aim 3: Assessment of motor vehicle crashes was changed from Johns Drowsiness Score to 
drive diaries and data gathered on the End of Rotation Survey. 
Section 1.5, Study Procedures. Data collection with Optalert was deleted. 
Section 1.5.3, Identification of patient risk factors. Severity of illness was changed from assessment by 
PRISM scores to use of ICD‐9 codes. 
Section 1.5.5.1, Optalert.  This section was deleted because the Optalert was not used to assess driving 
safety. 
Section 2.5.5.2, PVT. The measurement of alertness via the Karolinska Sleepiness Scale (KSS), before and 
after each PVT test, was added. 
Section 1.5.6.2, Educational measures. The optional enrollment of residents in OpenPediatrics was 
added.  
Section 1.6.2, Resident safety. This section was added at the request of the Data and Safety Monitoring 
Board (DSMB). 
Section 1.7, Statistical considerations. Information regarding the analysis of Optalert data was removed. 
Section 1.8.4, Staff training. This additional information was added regarding the reliability of the 
detection of medical errors as follows: To ensure inter‐rater reliability, the physician observers and 
research nurses will undergo training in the detection of medical errors and adverse events prior to 
observing residents. The training will include evaluation of test cases designed to calibrate the 
observers’ assessments. At least twice during each 8 month period of data collection, for each wave of 
sites, the DCC will examine the rates of events by observer at each of the sites to determine if there is 
significant variability. Re‐training of physician observers will occur as needed to ensure consistent 
reporting of suspected medical errors across staff and sites. Documentation of the analyses of event 
rates as well as the staff training will be maintained by the DCC.  
Section 1.10.1, Steering Committee.  Changes in membership were noted. 
Section 1.10.2, Executive Committee.  Changes in membership were noted. 
Section 1.10.3, Principal Planning Group.  Changes in membership were noted. 
Section 1.10.5, Data and Safety Monitoring Board. This information was added: . The board is comprised 
of five members with expertise in pediatric intensive care, pediatric critical care, sleep medicine, clinical 
trial design and biostatistics, bioethics, healthcare quality and outcomes research.   
  

ROSTERS  
 
September 23, 2014 
1 
 
ROSTERS Statistical Analysis Plan 
 
Definition of medical error outcomes.  The primary outcome of the study will be resident‐related harmful medical 
errors (preventable adverse events) and other medical errors (near misses), as determined by the adjudication 
process specified in the protocol. In brief, all potential medical errors and adverse events reported by the study 
sites will be reviewed by two site investigators, blinded to the site of origin. Physician reviewers will classify events 
as: (1) adverse event / harm; (2) intercepted near misses with potential for harm; (3) non‐intercepted near miss 
with potential for harm; (4) error with little or no potential for harm; and (5) exclusion. If an event is classified as 
“adverse event / harm”, the reviewers will then classify the level of harm and indicate to what extent the incident 
was preventable. Discordant reviews will be resolved by teleconference or assigned to a 3rd reviewer, as needed. 
Total ICU‐wide preventable adverse events and near misses will be secondary outcomes.  
 
Definition of secondary sleep outcomes. Actigraphy data and sleep diaries will be used to ascertain the minimum 
and mean 24‐hour sleep times. If there is sufficient data collected, we will also measure performance on the Johns 
Drowsiness Score (JDS), based on results captured by Optalert. Specifically, we will calculate the time‐weighted 
average JDS score for each commute; the proportion of the shift minutes spent with a JDS score above 4.5, the 
cutoff for impairment. Additional outcomes include variables derived from the Psychomotor Vigilance Test (PVT), 
including the numbers of lapses in vigilance, defined as a reaction time >500 ms, on the PVT. 
 
Definition of safety outcomes.  Safety outcomes consist of motor vehicle accidents (MVAs) and near misses, 
drowsy driving, needle sticks and other body fluid exposures, suicide ideation and resident SAEs. MVAs, near 
misses, and drowsy driving are captured both in the End of Rotation Survey (completed by all enrolled residents) 
and in the Drive Diary (completed by residents who drive to and from the hospital). Information about needle 
sticks, body fluid exposures, depression, and suicidal ideation are captured in the End of Rotation Survey as well. 
Resident SAEs are reported as they occur.   
 
Preliminary analyses.  Preliminary analyses include ongoing efforts to check and clean the data. The electronic 
data collection forms are designed to minimize missing data and skip pattern errors, by requiring responses to 
questions and only displaying sub‐questions, based on responses to parent questions. A series of edit checks are 
run daily to detect data inconsistencies (eg, inconsistent dates). Furthermore, additional checks are run on the 
entire data set to check for inconsistencies or errors across forms. The Resident Sleep/Work and Drive Diary data 
is reviewed a few times per week for errors and missing data. Diary findings are communicated to the sites, who 
confirm any diary changes or additions with Residents.   
 
Objectively measured sleep data will be collected using an actigraph (Motionlogger‐L model;  Ambulatory 
Monitoring Inc, Ardsley, NY). Actigraph files will be processed at the DCC using manufacturer‐specific software 
(Action‐W2 software, version  2.7.2288).  Participating residents will complete sleep diaries for the time period 
they wore the actigraph, which includes time into and time out of bed and times the actigraph was removed. This 
information will be used in editing the actigraphy data files to set intervals for when the participant was in bed 
trying to sleep, and to delete time when the actigraph was removed. Inter‐scorer reliability for editing the 
actigraphy data files has been previously found to be high in our group (intra‐class coefficient = 0.95). (Blackwell 
2005) Sleep‐scoring algorithms available in the software will be used to determine sleep from wake times. (Cole 
1992, Girardin 2001) These algorithms calculate a moving average, which takes into account the activity levels 
immediately prior to and after the current minute, to determine if the time point should be coded as sleep or 
wake. The summary measure of total sleep time across a 24‐hr period will reflect data averaged over all 24‐hr 
periods the device was worn in order to obtain a more representative characterization of usual sleep patterns 
during the rotation. 
 

ROSTERS  
 
September 23, 2014 
2 
 
Once we have needed data from the site, we will determine whether the observers report similar rates of 
suspected events within centers, by schedule and period. We will also examine rates of discordance between 
adjudicators periodically to identify and address potential problems.  
 
Assessment of balance between schedules. To assess balance of the treatment and control samples, we will 
compare resident characteristics by schedule, stratified by clinical center, assessing within‐center and overall 
differences, as well as center by schedule interaction.  These checks will use linear, logistic, and other generalized 
linear models as appropriate to the distribution of each of the baseline covariates.  Baseline variables to be 
considered will include resident age, gender, race, post‐graduate year (PGY2 vs PGY3), body mass index, lifestyle 
factors (including smoking, alcohol use and caffeine intake), physical activity and medical history (including sleep 
apnea).   
 
Analysis of medical error outcomes.  Rates per 1000 patient‐days of the medical error outcomes will be compared 
by schedule using log‐link Poisson models, with clinical center, period, and schedule as fixed effects, robust 
standard errors to account for potential over‐dispersion, and the log of the number of patient‐days at risk as an 
offset. Outcome events and total patient days will be summed over each study period for each clinical site, 
omitting missed observer shifts, based on reports of the missed shifts and corresponding patient censuses from 
the sites. We will also assess treatment‐period interaction, a standard check with crossover trials.   
 
Analysis of secondary outcomes.  Comparisons of actigraphic outcomes will be made using regression models for 
summary outcomes constructed for each resident over their entire period, again controlling for clinical center and 
period. These outcomes will be normalized as necessary; generalized linear models appropriate for other outcome 
distributions, and/or bootstrap standard errors will be used if adequate normalization cannot be achieved.  
 
Analyses of safety outcomes.  Numbers of resident needle sticks, fluid exposures, MVAs, MVA near misses, MVAs 
with injuries, as well as numbers of each reported as related to fatigue or drowsy driving, will be compared by 
schedule using the methods proposed above for harmful medical errors.  Offsets will be calculated as the numbers 
of resident days determined using work and drive diaries.  Because MVA injuries are expected to too uncommon 
for meaningful statistical comparison, they will be presented using individual narrative descriptions. 
 
Mediation of the effects schedule on medical errors by sleep measures. We will assess mediation of the effects of 
schedule on resident‐related harmful medical errors by the effects of schedule on 24‐hour sleep times and PVT 
scores. We will use simulation methods (Imai 2010) as implemented in the mediation package in R [R Foundation 
for Statistical Computing, Vienna]. 
 
Sensitivity analyses. Two sensitivity analyses will be performed.    
 
If imbalances are found between schedules in our preliminary assessment, described above, we will conduct 
sensitivity analyses, both for primary and secondary outcomes, in which we flexibly adjust for the potential 
confounders that are associated at P<0.1 with schedule either overall or within at least one center.  These will 
include analyses adjusting for the number of residents with sleep disordered breathing, including sleep apnea; 
additional sensitivity analysis of the secondary outcomes will exclude these residents.  
 
If the numbers of missed observer shifts are imbalanced by schedule, we will conduct sensitivity analyses 
using multiple imputation of resident and total medical errors during unobserved shifts under both standard 
missing at random (MAR) and also plausible missing not at random (MNAR) assumptions.  Specific MNAR 
scenarios will include doubling of the error rates during unobserved shifts in both schedules, first 
simultaneously, then one at a time. 
 
 
 
 

ROSTERS  
 
September 23, 2014 
3 
 
Stopping Guidelines 
 
Stopping for benefit and harm.  The DSMB Guidelines for recommending continuation, modification, or stopping 
the study will explicitly include consideration of both statistical and non‐statistical issues and include the 
possibilities of early stopping for benefit, stopping early for harm, stopping for futility, and modification of 
protocol.  
 
Primary outcome for assessing benefit and harm. We propose to use the numbers of resident‐related harmful 
medical errors as the primary outcome for both benefit and harm. Additional considerations for stopping for harm 
could include serious adverse events among residents, including needle sticks, fluid exposures, and MVAs.  
 
Rules for stopping.  We propose to use Lan‐DeMets methods (Lan 1983) to define symmetric stopping boundaries; 
the DSMB may decide to use a more liberal rule for stopping for harm or to allocate type‐I error differentially to 
efficacy and harm.  We will use an alpha spending function resulting in boundaries similar to O’Brien‐Fleming, 
making it difficult to stop early but inducing minimal shrinkage in the alpha for the end‐of‐trial analysis. We 
propose two interim analyses of treatment effects on the primary benefit/harm endpoint.  The first analysis will 
occur when Sites 1 and 2 will have completed both schedules; and the second when Sites 1‐4 will have completed 
both schedules. To aid in decision making, partial data will be provided for sites 3 and 4 at the first look, as well as 
for sites 5 and 6 at the second, but not included in the interim analysis; the rationale for these exclusions is that 
between‐site differences would confound schedule if the sites contributing outcomes for only one schedule were 
included. With an overall type‐I error rate of 5% allocated equally to benefit and harm, critical values of the Z‐
statistics at the first, second, and final analyses will be 2.67, 2.32, and 2.03 respectively, corresponding to 2‐sided 
p‐values of 0.008, 0.021, and 0.043. The DSMB will consider stopping the study early for efficacy or safety if the 
absolute Z‐statistic at the first and second interim analysis exceeds the boundary values of 2.67 and 2.32 
respectively. 
 
Stopping for futility.  The decision to stop for futility will be informed using simulations of conditional power, given 
the current data, to detect a 10% reduction in overall resident‐related medical errors, and a 25% reduction in 
resident‐related preventable AEs (Lan 1982; Halperin 1982). These analyses entail no inflation of the overall type‐I 
error rate, and will be conducted in conjunction with the two interim analyses of benefit/harm.  The DSMB will 
consider stopping the study for futility if estimated conditional power to detect the specified treatment effects 
falls below 50% for both outcomes. These decisions are complex and the guidelines may be further developed by 
the DSMB and NHLBI, with the assistance of the DCC.  
 
Interim Analyses 
 
An unblinded statistical analyst at the DCC will analyze the major endpoints at the time points specified above, 
and reports will be prepared for presentation to the DSMB. Except for designated NHLBI and DCC staff, all 
investigators and staff will remain blinded to interim results. Interim reports will be derived from the database as 
it exists on pre‐specified dates, and full copies of the database at the time of each interim analysis will be 
archived. The interim analysis tables will be the same as the tables used in the open and closed sessions of the 
DSMB meetings, but results will be stratified by sites and include P‐values. Please see a list of the tables below:  
 
 
Interim Analysis Tables  
Study Progress 
Table 1: Summary of Residents Declined Participation 
 
Table 2: Enrollment Status by Schedule, Wave and Site 
 
Figure 1: Cumulative Enrollment by Month, by Site/Schedule 
Table 3: Patient Days by Schedule, Wave and Site 
 

ROSTERS  
 
September 23, 2014 
4 
 
Descriptives 
 
Table 4: Summary of Disposition and Follow‐up by Schedule 
 
Table 5: Summary of Demographic and Baseline Characteristics 
by Schedule 
Primary Outcome 
Table 6: Resident Incidents Occurring During Rotation  
Table 7: Patient Incidents Occurring During Rotation 
Secondary Outcomes 
Table 8: Summary of Quality of Work Experienced by Schedule 
Table 9: Summary of Depression by Schedule 
Table 9: Summary of Self‐Reported Sleepiness by Schedule 
 
 
 
References: 
 
Blackwell T, Ancoli‐Israel S, Gehrman PR, Schneider JL, Pedula KL, Stone KL. Actigraphy scoring reliability in the 
study of osteoporotic fractures. Sleep 2005;28:1599‐605. 
 
Cole RJ, Kripke DF, Gruen W, Mullaney DJ, Gillin JC. Automatic sleep/wake identification from wrist actigraphy. 
Sleep 1992;15:461‐ 9. 
 
Girardin JL, Kripke DF, Mason WJ, Elliot JA, Youngstedt SD. Sleep estimation from wrist movement quantified by 
different actigraphic modalities. J Neurosci Methods 2001;105:185‐91. 
 
Imai K, Keele L, Yamamoto T.  Identification, inference, and sensitivity analysis for causal mediation effects.  
Statistical Science, 2010:25(1):51‐71. 
 
Lan KKG, DeMets DL. Discrete sequential boundaries for clinical trials. Biometrika. 1983;70:649‐653 
 
Lan KKG, Simon R, Halperin M. Stochastically curtailed tests in long‐term clinical trials. Comm Statist, Series C 
(Sequential Analysis). 1982;1:207‐219.  
 
Halperin M, Lan KKG, Ware JH, Johnson WJ, DeMets DL. An aid to data monitoring in long‐ term clinical trials. 
Controlled Clin Trials. 1982;3:311‐323.  
 

 
1 
 
Modifications to the original ROSTERS statistical analysis plan: 
Additional analysis were requested by the DSMB as follows: 
o Requested at April 2016 meeting. Show medical errors results broken down by severity 
of error. 
o Requested at November 2016 meeting. Adjust models with medical errors outcomes by 
patient risk score.