Real-time Fatigue Mitigation With Air-medical Personnel: The SleepTrackTXT2 Randomized Trial
Phase: NA
Conditions: Poor Quality Sleep, Fatigue
Sponsor: University of Pittsburgh

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
1 
Title Page 
Sleep-Wake Patterns and Real-Time Fatigue Reduction in EMS Clinicians: 
Phase II 
 
 
Brief Title: 
The SleepTrackTXT2 Randomized Trial with Air-Medical Personnel 
 
 
ClinicalTrials.gov ID# NCT02783027 
University of Pittsburgh IRB# PRO16030345 
 
Principal Investigator: 
P. Daniel Patterson, PhD 
 
Date: March 8, 2016 
 
 

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
2 
 
 
 
 
 
Project Name: Sleep-Wake Patterns and Real-Time Fatigue Reduction in EMS 
Clinicians: Phase II 
  
  
Project Description (2000 character limit): 
Fatigue is an “unpleasant symptom incorporating feelings of tiredness to 
exhaustion creating conditions that interfere with the ability to function in a 
normal capacity.”1 Recent data show that half of clinicians in ground and air-
medical based Emergency Medical Services (EMS) operations suffer from 
fatigue and are at elevated risk of a negative safety outcome.[1, 2] Existing 
fatigue risk management programs and systems may not have the intended 
impact. Experts believe the future of fatigue risk management is real-time 
assessment and intervention of fatigued workers.[3, 4] 
  
Recently, we completed the first pilot randomized trial that tested real-time 
assessment of fatigue and sleepiness in EMS clinicians. The SleepTrackTXT 
pilot randomized trial successfully enrolled 100 paramedics, flight paramedics, 
flight nurses, emergency room nurses and several emergency physicians to 
participate over 90-days and use text-messages to report feelings of fatigue and 
sleepiness during shift work.[5] Participants in the intervention group received 
strategy messages in real-time if they reported high levels of fatigue, sleepiness, 
or difficulty concentrating at the beginning or during shift work. The study was a 
success, and participants answered 88.1% or 36,073 text messages. Participants 
in the intervention group that worked extended shifts (e.g., 12-hour shifts) 
reported lower levels of fatigue at the end of shift compared to participants in the 
control group (p<0.05). At the end of the study, participants reported high 
satisfaction with the SleepTrackTXT tool as the primary means for assessing 
fatigue in EMS settings.  
  
The overarching goal of this proposal is to address the MedEvac foundation 
priority of educational techniques and technologies and improve HEMS safety by 
determining if overall sleep quality and intra-shift fatigue of HEMS clinicians can 
be improved with real-time assessment and intervention.  
 
 
 
 
Abstract (2500 characters) 
It is widely believed that extended shift patterns such as 12-hour and 24-hour 
shifts lead to fatigue and increase the odds of negative safety outcomes for shift 
workers.[6] Our recent research shows that greater than half of EMS clinicians 

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
3 
report fatigue while at work, and poor safety outcomes are more common among 
fatigued EMS clinicians.[2] These data suggest that existing fatigue management 
programs may not be as effective as hoped, and stress the need to identify and 
reduce fatigue with new and innovative tools. 
  
Recently, we tested an innovative tool that identifies fatigue in real time and 
intervenes in real time with fatigue-reduction strategies.[5, 23] The 
SleepTrackTXT tool uses text-messaging to query EMS clinicians in real-time at 
the beginning, during, and end of scheduled shifts. From January 2014 to June 
2014, we enrolled 100 EMS clinicians in a 90-day research study, including more 
than a dozen clinicians that work in air-medical operations. Participants 
randomized to the intervention group were sent strategies via text-messages in 
real-time during shifts that can help reduce feelings of fatigue and sleepiness. 
Preliminary findings show use of text-messaging is feasible and attractive to EMS 
clinicians. Participants documented 2,621 shifts, and nearly half (48.4%) were 
greater than 12-hours in length. The SleepTrackTXT sent 40,947 text messages 
asking EMS clinicians about fatigue and sleepiness in real-time. Participants 
responded to 36,073 text-messages, 88.1%. Results show that our pilot 
intervention reduced feelings of fatigue by the end of shift work. During follow-up 
interviews, participants requested additional help with structuring sleep patterns 
and habits to deal with shift work and improve overall sleep quality.[23] 
  
The overarching goal of this proposal is to address the MedEvac foundation 
priority of educational techniques and technologies to improve safety, and 
determine if an enhanced SleepTrackTXT intervention, including a sleep health 
component, reduces fatigue during shift work and leads to clinically meaningful 
improvements in sleep quality. 
  
Aim 1: To determine the short-term impact of an enhanced SleepTrackTXT 
intervention on HEMS clinician fatigue reported in real-time during and at the end 
of shift work. 
  
Aim 2: To determine the long-term impact of the SleepTrackTXT intervention on 
sleep quality and sleep health indicators including hours of sleep and recovery 
between shift work. 
 
 
 
Resources and Environment (a standard form downloaded from the 
MedEvac site) 
 
Study sites include MedCenter Air of Carolinas HealthCare, STAT MedEvac of 
the University of Pittsburgh Medical Center (UPMC), MedFlight of Ohio, and 
Mercy Flight of Buffalo. All four sites have demonstrated their capability to fulfill 
multi-site studies based on successful enrollment and participation in previous 

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
4 
and ongoing research of air-medical clinicians. All sites have the required support 
staff and on-site, active site-specific co-investigators. 
 
The lead study site for this multi-site study is the Department of Emergency 
Medicine (DEM) at the University of Pittsburgh, Pittsburgh, PA. The Department 
has a long history of scientific research involving observational and experimental 
study designs and focused research on EMS safety. Dr. Patterson has 
assembled a multi-disciplinary team of experienced investigators and study 
coordinators. Our team is cohesive and actively engaged in related research 
involving our four study sites. We are well suited to undertake and complete the 
study as designed. Our research team has experience conducting research, 
completing studies on time, and presenting study findings to scientific and other 
audiences.  
 
Co-investigator Mr. Jack Doman of the University of Pittsburgh is the architect of 
the original SleepTrackTXT study tool shown effective in our recent randomized 
trial. Mr. Doman has developed an enhanced version of our novel tool for use in 
this prospective experimental study funded by the MedEvac Foundation.  
 
 
Research Protocol, Part One – Introduction, background, significance (3000 
characters): 
INTRODUCTION: Fatigue has been defined as “a subjective, unpleasant 
symptom, which incorporates total body feelings ranging from tiredness to 
exhaustion creating an unrelenting overall condition which interferes with 
individual’s ability to function to their normal capacity.”[7] There is convincing 
evidence connecting extended shift patterns, such as 24-hour shifts, to poor 
sleep health, fatigue, and negative safety outcomes.[8, 9] 
 
BACKGROUND: Emergency Medical Services (EMS) clinicians are a group of 
workers where extended shifts, inconsistent shift patterns, poor sleep, and 
fatigue are common.[2, 10-12] There are an estimated 19,000 EMS organizations 
and 800,000 to 1 million licensed EMS workers in the U.S. today.[13] EMS 
workers are often the first point of clinical contact for the acutely ill and injured. 
Many EMS workers are on the job for extended periods (e.g., 24 hours), they 
often work consecutive shifts, and accumulate many hours of overtime.[2, 10-12] 
Data show that half of EMS workers sleep less than six hours per sleep period 
and many report poor sleep quality.[2] One-third of EMS workers report 
excessive daytime sleepiness[14] and more than half report excessive mental 
and physical fatigue.[2, 10] Odds of injury are 1.9 times greater among fatigued 
EMS workers than the non-fatigued – after controlling for confounding.[2] Odds of 
making an error or experiencing a patient-related adverse event are 2.2 times 
greater among fatigued EMS workers than the non-fatigued.[2] Fatigue and poor 
sleep increase the likelihood of risky behaviors. Odds of engaging in behaviors 
that compromise safety are 3.6 times greater among EMS workers that report 
fatigue.[2] 

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
5 
 
SIGNIFICANCE: There is limited real-time fatigue monitoring of EMS clinicians. 
However, there is growing enthusiasm and preliminary data to support use of 
real-time fatigue monitoring using mobile technologies such as cell phones and 
smartphones.[15, 16] Most Americans (90%) own a cell phone and half own a 
smartphone.[17, 18] Most cell phone owners (80%) send or receive text-
messages.[17] A recent systematic review of intervention studies using text-
messages or mobile applications showed a positive impact on behaviors, such as 
smoking cessation, diabetes control, weight loss, asthma self-management.[16] 
Tailored text-message based interventions may benefit EMS worker sleep habits 
and behaviors related to fatigue. Text-message interventions are a potentially 
high-impact, low-cost platform for encouraging positive sleep habits, tracking 
fatigue, and distributing information to EMS workers at risk of negative safety 
outcomes related to fatigue. In the first known study using text-messaging to 
study fatigue in EMS, we have 1) shown it is feasible to use this tool to monitor 
fatigue in real-time, and 2) produced early evidence that we can reduce 
perceived fatigue by intervening with tailored fatigue reduction strategies in real-
time. 
 
 
 
 
Research Protocol, Part Two – Objectives Hypotheses (3000 characters): 
 
The overarching goal of this proposal is to address the MedEvac foundation 
priority of educational techniques and technologies to improve safety, and 
determine if an enhanced SleepTrackTXT intervention, including a sleep health 
component, reduces fatigue during shift work and leads to clinically meaningful 
improvements in sleep quality. 
  
Aim 1: To determine the short-term impact of an enhanced SleepTrackTXT 
intervention on HEMS clinician fatigue reported in real-time during and at the end 
of shift work. 
 
Rationale Aim 1: In our recent SleepTrackTXT pilot randomized trial, we have 
successfully shown that real-time assessment of fatigue involving EMS clinicians 
and text-messages is possible. We have also shown that sending text-messages 
in real-time to clinicians that report high levels of fatigue leads to reduced fatigue 
by the end of shift. An enhanced intervention that addresses additional sleep 
health information (e.g., sleep debt), may have a greater impact. 
 
Hypothesis 1A: We hypothesize that an enhanced version of the SleepTrackTXT 
tool that includes sleep health and sleep quality components will contribute to 
significant reductions in intra-shift fatigue. 
  

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
6 
Aim 2: To determine the impact of the SleepTrackTXT intervention on sleep 
quality and sleep health indicators including hours of sleep and recovery between 
shift work. 
 
Rationale Aim 2: Preliminary findings from our pilot randomized trial using an 
Intent-To-Treat analysis shows a statistically significant improvement in sleep 
quality among participants in the intervention group. The improvement fell short 
of a cut point thought to be clinically meaningful. We believe an enhanced 
intervention focused on sleep debt may have a grater impact on sleep quality. 
 
Hypothesis 2A: We believe an enhanced version of our brief SleepTrackTXT 
intervention that includes a sleep health and sleep quality component can lead to 
clinically meaningful improvements in sleep quality over time. 
 
Our power calculation was designed to determine the number of subjects needed 
to detect a clinically meaningful difference of 3 points on the PSQI from baseline 
to the study end. We fixed alpha at 0.05 and performed one-sided hypothesis 
testing. The standard deviation of the difference was estimated as 2.2 using data 
from our recent randomized trial.[5] Group sample sizes of 27 for the intervention 
and 27 for the control group achieve 90% power to reject the null hypothesis of 
equal means with a standard deviation of 2.2 and significance level of 0.05 using 
a two-sided two-sample equal variance t-test. We estimate a 15% attrition rate 
based on our prior randomized trial.[23] We estimate 15% of participants in the 
intervention group will not abide by the intervention protocol. Based on these 
estimates, we seek to enroll a total of n=100 (50 per group) to account for 
attrition and non-compliance. 
 
 
 
 
Research Protocol, Part Three – Methods (3000 characters): 
 
STUDY DESIGN: We will use a two-arm parallel, randomized, controlled and 
single-blinded trial. Our design is similar to the original SleepTrackTXT trial with 
100 EMS clinicians.[5, 23] 
 
SETTING AND POPULATION: We will recruit and enroll study participants from 
four air-medical EMS organizations: 1) Carolina’s MedCenter Air; 2) STAT 
MedEvac; 3) MedFlight of Ohio, and 4) MercyFlight of Buffalo, NY. 
 
Site 1: MedCenter Air (MCA) is a CAMTS accredited critical care transport 
service offering ground, rotor wing, and fixed wing services. MCA utilizes 
nurse/nurse or nurse/respiratory therapist crew configuration. Rotor wing 
services are based at airports surrounding the Charlotte area of North Carolina 
(Hickory, NC; Concord, NC; Rock Hill, SC). MCA performs approximately 2,200 
rotor wing transports yearly. MCA employs 170 clinicians that work 12-hour 

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
7 
shifts. 
 
Site 2: STAT MedEvac site is a CAMTS accredited, regional critical care service 
with 17 base sites across Eastern Ohio, Pennsylvania, Northern Maryland, and 
the District of Columbia. STAT MedEvac has an annual patient volume of 10,000. 
STAT MedEvac employs 160 prehospital flight nurses and paramedics that have 
a minimum of three years of critical care experience and required certification of 
CFRN or FP-C. Shift schedules are mostly 24-hours in duration, with some that 
work 12-hour shifts.  
 
Site 3: MedFlight of Ohio is a CAMTS accredited rotor and ground critical care 
service operating from 12 bases in Ohio. MedFlight serves primarily central Ohio 
but also transports patients originating from Pennsylvania and West Virginia. In 
2013, MedFlight of Ohio completed approximately 7,000 transports. MedFlight of 
Ohio employs 150 clinicians certified or licensed as nurses or paramedics. 
Employees are classified as either full-time or part-time and work shifts of 12-
hours and 24-hours in duration.  
Site 4: Mercy Flight of Buffalo, NY. Mercy Flight operations are conducted from 
three bases (Buffalo, Olean and Batavia), 24 hours a day / 7 days a week. The 
Mercy Flight Team consists of 26 paramedics, 27 nurses,13 pilots, 9 air medical 
communications specialists, 6 aircraft mechanics and an 11 member 
administrative, development, finance and facilities management team 
that provides the necessary support service for flight operations. Each helicopter 
crew consists of a Pilot, Paramedic and Nurse. Flight Paramedics have at least 
two years of high volume, critical care EMS experience. Flight Nurses have more 
than 2 years of critical care experience in an Emergency Room (ER), Intensive 
Care Unit (ICU) or other critical care field. Over the past 30+ years, Mercy Flight 
has conducted more than 20,000 patient missions and thousands of Ground 
Crew Safety Training and Community Education sessions throughout its primary 
service area of Western New York, Northwest Pennsylvania and Southern 
Ontario. The dispatch center is staffed 24/7 by Communications Specialists who 
field, prioritize, dispatch and coordinate incoming flight requests. They are 
certified by the National Association of Air Medical Communication Specialists 
(NAACS). Mercy Flight a Part 145, FAA Certified Repair Station and our in-house 
aircraft mechanics utilize more than 100 years of combined experience to keep 
the helicopters flight-ready.  
 
PROTOCOL: We will recruit via email and study flyers sent directly to eligible 
individuals employed at the study sites. We seek to enroll n=100 clinicians. 
Clinicians with an interest in the study will complete a telephone screening 
appointment. Inclusion criteria include: 1) 18 years of age and older, 2) working 
clinically at a study site, 3) currently working in shifts, 4) has a smartphone, and 
5) willing to take part in a research study that requires the sending and receiving 
of multiple text messages daily over 4-months. Eligible clinicians will complete a 
standard enrollment process with an IRB-approved informed consent procedure. 

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
8 
Randomization into the intervention versus control groups will occur immediately 
after completion of informed consent. All consented participants will receive a 
unique login account to access the study website. Participants will use the secure 
study website to document shift schedules for four months. Participants will 
receive $100 remuneration.  
 
INTERVENTION GROUP: The intervention and control group participants will 
use an online sleep diary, a shift scheduling tool to document shift schedules, 
answer text-message queries about their fatigue and sleep health between shifts 
(inter-shift) and during shiftwork (intra-shift). The intra-shift text-messages are 
modeled after the original SleepTrackTXT trial (clinicaltrials.gov identifier: 
NCT02063737). Participants in the intervention group will receive tailored text-
messages (“Alertness Promoting Messages”) if they report high levels of fatigue, 
sleepiness, or difficulty with concentration during shiftwork (intra-shift). The inter-
shift messages will be sent on days off from work at noon (12:00pm). These 
messages will include queries about sleep obtained, perceived recovery since 
last shift, fatigue, sleepiness, and difficulty with concentration. Participants in the 
intervention group will also receive a Sleep Debt text-message that highlights the 
participant’s calculated sleep debt over the past 7 days, followed by 
recommendations for obtaining adequate sleep. Finally, the intervention group 
will also have access to a graphic illustration of reported fatigue levels over time. 
The Y-axis will be the fatigue score 0=not at all to 5=very much and the X-axis 
will be over time (the study period). One line will represent the participant’s 
reported fatigue. Other lines will include de-identified aggregated data from other 
participants in the study. A select group of n=10 intervention participants will 
wear wrist actigraphy for purposes of validating self-reported sleep diary 
information. This same select group of 10 participants will be asked to complete 
psychomotor vigilance tests (PVTs) at the beginning and end of a select number 
of shifts during the study period.  
 
CONTROL GROUP: The control group participants will use an online sleep diary, 
a shift scheduling tool to document shift schedules, answer text-message queries 
about their fatigue and sleep health between shifts (inter-shift) and during 
shiftwork (intra-shift). The intra-shift text-messages are modeled after the original 
SleepTrackTXT trial (clinicaltrials.gov identifier: NCT02063737). Control group 
participants will receive inter-shift messages on days off from work at noon 
(12:00pm). These inter-shift messages will query the participant’s sleep obtained, 
perceived recovery since last shift, fatigue, sleepiness, and difficulty with 
concentration. A select group of n=10 control group participants will wear wrist 
actigraphy for purposes of validating self-reported sleep diary information. This 
same select group of 10 control group participants will be asked to complete 
psychomotor vigilance tests (PVTs) at the beginning and end of a select number 
of shifts during the study period. 
 
 

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
9 
 
 
Research Protocol, Part Four – Outcome Measures & Data Analysis (3000 
characters): 
 
One outcome of interest (linked to Aim 2) is sleep quality, which will be measured 
with the widely used Pittsburgh Sleep Quality Index (PSQI).[19] A PSQI score of 
6 or more on a 21-point scale indicates poor sleep quality. A reduction in PSQI of 
3-points suggests a clinically meaningful improvement in sleep quality.[22] We 
will administer the PSQI at baseline and then again at the end of the 4-month 
study period. 
 
Our power calculation was designed to determine the number of subjects needed 
to detect a clinically meaningful difference of 3 points on the PSQI from baseline 
to the study end. We fixed alpha at 0.05 and performed one-sided hypothesis 
testing. The standard deviation of the difference was estimated as 2.2 using data 
from our recent randomized trial.[5] Group sample sizes of 27 for the intervention 
and 27 for the control group achieve 90% power to reject the null hypothesis of 
equal means with a standard deviation of 2.2 and significance level of 0.05 using 
a two-sided two-sample equal variance t-test. We estimate a 15% attrition rate 
based on our prior randomized trial.[23] We estimate 15% of participants in the 
intervention group will not abide by the intervention protocol. Based on these 
estimates, we seek to enroll a total of n=100 (50 per group) to account for 
attrition and non-compliance. 
 
One outcome measure is linked to Aim 1 and is intra-shift fatigue reported at the 
beginning, during, and end of scheduled shifts. We will use a single-item 
measurement of fatigue, which is the preferred approach for research that 
involves real-time data capture and/or ecological momentary assessment 
(EMA).[20] This measure was constructed based on prior EMA research of 
insomnia, it has been tested in our pilot trial and shown to be sensitive to change 
in fatigue over the course of shift work.[21] We hypothesize that over time and 
after repeated exposure to the intervention, participants in the intervention group 
will report lower levels of fatigue at the end of shift than participants in the control 
group. 
We will use linear mixed-model analyses to examine the effectiveness of the 
intervention on reducing reported fatigue at the end of shift among participants in 
the intervention group and compare reported values to the control group. We will 
construct a model where the outcome is the reported fatigue at the end of each 
shift, a fixed effect of time in study, and a random effect for participants to 
account for multiple shifts within each person. We will examine the estimated 
change in fatigue per shift and over multiple shifts throughout the study period. 
Post-estimation testing will be used to describe the correlation in fatigue scores 
within the subjects across shifts.  

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
10 
Independent measures of interest include age, sex, health status indicators, and 
other demographic and person-level variables that address employment status, 
shift schedule/pattern, general fatigue, co-morbidities/diagnoses, and psycho-
social factors that may be associated with sleep and shiftwork. We will use 
descriptive statistics to examine the distribution of these variables, parametric 
and non-parametric tests to assess change in values/scores on measures that 
may change over the course of the 4-month study period.  
 
 
 
 
Research Protocol, Part Five – Limitations (3000 characters): 
We recognize that clinicians participating in this study may be different based on 
demographic factors, including experience-related variables of other HEMS 
clinicians not participating. We believe that once a participant has enrolled, 
he/she will most likely demonstrate a high level of adherence with fidelity to the 
design of the study. We wish to point out that participation in our pilot randomized 
SleepTrackTXT trial was excellent, and included 12 air-medical clinicians. We 
also wish to point out success in the recent observational study funded by 
MedEvac, where we successfully enrolled n=120 individual air-medical clinicians, 
of which 18 participated twice for a total of n=138 study participations. Based on 
these data, we believe that once a person has enrolled, compliance with required 
queries will be high. Based on our prior experience, we are confident we will 
reach the goal of 100. 
 
Finally, we are limited by the lack of a gold standard in fatigue measurement. The 
literature is clear that no such standard exist and that most assessments of 
fatigue in any population must rely on self-reported and subjective assessments 
of fatigue signs and symptoms. We have completed numerous studies of fatigue 
involving EMS clinicians. We have demonstrated use of psychometrically sound 
tools, which is a minimum standard when using measures involving self-report. 
For purposes of this proposal, we will use single-item measures of fatigue and 
sleepiness. We have developed these measures based on the best available 
science, including recent research analogous to our research involving repeated 
– hourly – queries of symptoms related to insomnia.  
 
We will include a validation component whereby a select sample of 20 
participants selected at random (10 from intervention and 10 from control group) 
will answer additional fatigue questions from previously validated tools over the 
course of the study period in a repeated fashion. These data will be used to 
examine construct and predictive validity as well as internal consistency 
reliability. 
 
 
 
 

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
11 
 
 
 
 
Research Protocol, Part Six – Impact on the medical transportation 
community (3000 characters): 
 
The medical transportation community requires that skilled providers are 
available and accessibly 24 hours a day, necessitating shifts that diverge from 
normal circadian sleep cycles. In addition, the cost of readiness in medical 
transportation often necessitates long shifts due low unit hour utilization and 
remote locations. In these instances, providers are asked to perform cognitively 
complex duties with limited sleep and under conditions of poor sleep health. 
Fatigue in these situations has been associated with medical error, provider 
injury, and poor patient outcomes.[2]  
 
This study provides a novel mechanism for fatigue risk management through 
improved real-time surveillance and targeted, individualized, and tailored 
interventions. This study will have a significant impact on the transportation 
community. First, the future of fatigue risk management is use of real-time 
monitoring. Real time knowledge of fatigued providers will allow for improved 
fatigue and risk management strategies, which may include interventions such as 
prompting the provider to use caffeine or take a nap. In our recent pilot 
randomized trial with 100 EMS participants, findings reveal that a simple 
intervention of prompting EMS clinicians to take a nap or drink caffeine with 
fatigued leads to reductions in fatigue, sleepiness, and difficulty with 
concentration.[5, 23] These data support the addition of real-time monitoring and 
intervention with use of a mobile technology like text-messages. With additional 
data produced from this study, it may be appropriate for the agency to integrate 
this type of technology and protocol as part of a larger fatigue risk management 
system that includes brief rest periods or other strategies. This research may 
also lead to the technology being used to proactively to identify HEMS clinicians 
with poor sleep health and offer them resources to mitigate fatigue related risk 
and improve their quality of life. 
 
Operationally, long shifts (those greater than or equal to 12 hours) provide a 
convenience to provider and agency alike. In more remote areas of the country, 
they may be a necessity as it would be impracticable for them to work shorter 
shifts. As a result, agencies and their employees bear the responsibility to 
operate safely in this challenging environment. Real time tools for fatigue 
management hold the promise to be impactful by improving patient and provider 
safety and simultaneously ensuring round the clock access to this important 
resource. 
 
 

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
12 
References: 
1. 
Patterson PD, Suffoletto BP, Kupas DF, Weaver MD, Hostler D: Sleep quality 
and fatigue among prehospital providers. Prehosp Emerg Care 2010, 
14(2):187-193. 
2. 
Patterson PD, Weaver MD, Frank RC, Warner CW, Martin-Gill C, Guyette FX, 
Fairbanks RJ, Hubble MW, Songer TJ, Callaway CW et al: Association 
between poor sleep, fatigue, and safety outcomes in emergency medical 
services providers. Prehosp Emerg Care 2012, 16(1):86-97. 
3. 
Lerman SE, Eskin E, Flower DJ, George EC, Gerson B, Hartenbaum N, Hursh 
SR, Moore-Ede M, ACOEM: Fatigue risk management in the workplace. J 
Occup Environ Med 2012, 54(2):231-258. 
4. 
Balkin TJ, Horrey WJ, Graeber RC, Czeisler CA, Dinges DF: The challenges 
and opportunities of technological approaches to fatigue management. 
Accid Anal Prev 2011, 43(2):565-572. 
5. 
Patterson PD, Moore CG, Weaver MD, Buysse DJ, Suffoletto BP, Callaway CW, 
Yealy DM: Mobile phone text messaging intervention to improve 
alertness and reduce sleepiness and fatigue during shiftwork among 
emergency medicine clinicians: Study protocol for the SleepTrackTXT 
pilot randomized controlled trial. Trials 2014, 15(1):244. 
6. 
Rogers AE: Chapter 40: The Effects of Fatigue and Sleepiness on Nurse 
Performance and Patient Safety. In: Patient Safety and Quality: An 
Evidence-Based Handbook for Nurses. Edited by Hughes RG. Rockville, MD: 
Agency for Healthcare Research and Quality; 2008. 
7. 
Ream E, Richardson A: Fatigue: a concept analysis. Int J Nurs Stud 1996, 
33(5):519-529. 
8. 
Williamson A, Lombardi DA, Folkard S, Stutts J, Courtney TK, Connor JL: The 
link between fatigue and safety. Accid Anal Prev 2011, 43(2):498-515. 
9. 
Fisman DN, Harris AD, Rubin M, Sorock GS, Mittleman MA: Fatigue 
increases the risk of injury from sharp devices in medical trainees: 
results from a case-crossover study. Infect Control Hosp Epidemiol 2007, 
28(1):10-17. 
10. 
Patterson PD, Jones CB, Hubble MW, Carr M, Weaver MD, Engberg J, Castle 
NG: The longitudinal study of turnover and the cost of turnover in 
emergency medical services. Prehosp Emerg Care 2010, 14(2):209-221. 
11. 
Bauder B: Safety fears rise with city's use of overtime. In: Pittsburgh 
Tribune-Review. Pittsburgh, PA; 2012. 
12. 
Frakes MA, Kelly JG: Sleep debt and outside employment patterns in 
helicopter air medical staff working 24-hour shifts. Air Med J 2007, 
26(1):45-49. 
13. 
National EMS Assessment 
[http://www.ems.gov/pdf/2011/National_EMS_Assessment_Final_Draft_122
02011.pdf] 
14. 
Pirrallo RG, Loomis CC, Levine R, Woodson BT: The prevalence of sleep 
problems in emergency medical technicians. Sleep Breath 2012, 
16(1):149-162. 

ClinicalTrials.gov ID# NCT02783027 
Date: March 8, 2016 
 
13 
15. 
Free C, Phillips G, Galli L, Watson L, Felix L, Edwards P, Patel V, Haines A: The 
effectiveness of mobile-health technology-based health behavior 
change or disease management interventions for health care 
consumers: a systematic review. PLoS Med 2013, 10(1). 
16. 
Buhi ER, Trudnak TE, Martinasek MP, Oberne AB, Fuhrmann HJ, McDermott 
RJ: Mobile phone-based behavioral interventions for health: A 
systematic review. Health Education Journal 2012, 72:564-583. 
17. 
Duggan M: Cell Phone Activities 2013. In: Pew Research Center's Internet & 
American Life Project. Washington, DC: Pew Research Center; 2013. 
18. 
Smith A: Smartphone Ownership - 2013 Update. In: Pew Research Center's 
Internet & American Life Project. Washington, DC: Pew Research Center; 
2013. 
19. 
Buysse DJ, Reynolds CFr, Monk TH, Berman SR, Kupfer DJ: The Pittsburgh 
Sleep Quality Index: a new instrument for psychiatric practice and 
research. Psychiatr Serv 1989, 28(2):193-213. 
20. 
Shiffman S, Stone AA, Hufford MR: Ecological momentary assessment. 
Annu Rev Clin Psychol 2008, 4:1-32. 
21. 
Buysse DJ, Thompson W, Scott J, Franzen PL, Germain A, Hall M, Moul DE, 
Nofzinger EA, Kupfer DJ: Daytime symptoms in primary insomnia: a 
prospective analysis using ecological momentary assessment. Sleep Med 
2007, 8(3):198-208. 
22. 
Buysse DJ, Germain A, Moul DE, Franzen PL, Brar LK, Fletcher ME, Begley A, 
Houck PR, Mazumdar S, Reynolds CFr et al: Efficacy of brief behavioral 
treatment for chronic insomnia in older adults. Arch Intern Med 2011, 
171(10):887-895. 
 
23. 
Patterson PD, Buysse DJ, Weaver MD, Doman JM, Moore CG, Suffoletto BP, 
McManigle KL, Callaway CW, Yealy DM. Real-time fatigue reduction in 
emergency care clinicians: The SleepTrackTXT randomized trial. Am J 
Ind Med. 2015, 58(10):1098-113.