Danger Signs of Worsening Heart Failure and Self-Management of Danger Signs: The Effects of Video Education
Phase: NA
Conditions: Heart Failure; With Decompensation
Sponsor: The Cleveland Clinic

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Study title 
Danger Signs of Worsening Heart Failure and 
Self-Management of Danger Signs:  The Effects 
of Video Education 
National Clinical Trial number 
NCT-03657459 
Date of the document 
11-7-2018 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Study Title:  Danger Signs of Worsening Heart Failure and Self-Management of Danger 
Signs: The Effects of Video Education   
 
 
Principal Investigator: Nancy M. Albert PhD, CCNS, CHFN, CCRN, NE-BC, FAHA, FCCM1 
 
Co-Investigators: 
Jim F. Bena, MS2  
 
 
 
 
Study Coordinator:  
Ellen Slifcak, BA, RN1 
 
1. Office of Nursing Research and Innovation 
2. Quantitative Health Sciences 
 
Cleveland Clinic, Cleveland OH 
 
 
Non-Cleveland Clinic Sites 
Navicent Health, 777 Hemlock St., Macon, Georgia 31201 
Navicent Principal Investigator:  
Dr. Erskine James, M.D. 
 
CCF contact person:  
Carol Babcock MFT, Director, Palliative Care and Healthy 
Communities; 478 633 8049; 
Babcock.Carol@NavicentHealth.org 
 
 

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ABSTRACT 
 
The most frequently cited danger signs of heart failure (HF) are new onset or worsening of 
fatigue, dyspnea and edema. In previous research, patients did not recognize worsening HF, due 
to 3 primary reasons: (1) danger signs were non-specific and misinterpreted as stress, an external 
force or another comorbidity, (2) danger signs were unrecognized due to the subtle nature of 
worsening status, or (3) when patients eliminated or minimized activities that prompted danger 
signs, they interpreted the results as improvement in status. Lack of recognition of HF danger 
signs and lack of understanding of how to control and minimize danger signs could lead to their 
escalation and prompt all-cause and HF-related health care resource utilization (HCRU:  
emergency department care, hospitalization, death/ventricular assist device/cardiac 
transplantation referral or placement, or an unscheduled/urgent office visit). During 
hospitalization, patient education is delivered, but it is assumed that patients understand the 
danger signs and simply need education in self-care behavior expectations. We hypothesize that 
patients must understand HF danger signs to have self-confidence in recognizing them and in 
taking steps to minimize or eliminate their occurrence post hospital discharge. Therefore, the 
purposes of this randomized, controlled trial are to determine if video education in HF danger 
signs recognition and control prior to discharge and post-discharge reduces all-cause and HF-
related 30-, 60-, 90- and 180-day HCRU. Research nurses will deliver the intervention during 
hospitalization, and patients and family members will receive a link to a website and a DVD of 
content to review videos as often as desired post-discharge. The primary end-point is 30-day HF-
related HCRU.  A total of 732 patients (658 + 10% attrition) with decompensated HF will be 
enrolled. Patients will be followed by telephone or medical record review to determine HCRU 
post index hospitalization.  
 

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INTRODUCTION    
 
Chronic heart failure (HF) is a costly diagnosis;1 especially for patients who are hospitalized due 
to decompensation. Heart failure decompensation and hospitalization place patients at high risk 
for rehospitalization, exacerbating costs of care and potential penalties associated with the 
Patient Portability Affordable Care Act.2  
 
Adherence to HF self-care maintenance (carrying out HF self-care behaviors recommended to 
patients with most etiologies of HF: limiting sodium intake per day, being active and exercising, 
managing fluids by daily weight monitoring and fluid restriction, monitoring for signs and 
symptoms of worsening HF, taking medications as ordered, and receiving follow-up care early 
after discharge) and management (calling a healthcare provider for new or worsening symptoms 
or taking actions to reduce sodium or fluid intake) behaviors were associated with improved 
clinical outcomes, including survival and fewer rehosptializations.3-5 Of note, when researchers 
studied 4 self-care behaviors in 830 patients with HF (weight monitoring, low sodium diet, fluid 
restriction and activity) at 30 days after hospital discharge, only 48% were adherent. At 18 
months, all-cause mortality or HF rehospitalization was lower among patients who were adherent 
to all 4 behaviors versus 0 or 1, 2, or 3 behaviors.4  
 
Patients with HF may not employ self-care behavior expectations when they do not understand 
HF danger signs (specifically: dyspnea, fatigue and edema) or understand how HF self-care 
behaviors can reduce or eliminate HF danger signs. Patients with HF may not understand that 
eliminating behaviors that lead to worsening of dyspnea and/or fatigue does not eliminate their 
risk of worsening HF. Rather, elimination of activities that worsened dyspnea and/or fatigue may 
simply mask worsening status, as the patient no longer experiences these symptoms. If patients 
recognize dyspnea, fatigue and edema as danger signs of worsening HF, they could employ self-
care behaviors that might minimize/reduce worsening status and create equilibrium.  
 
Dyspnea, fatigue and edema are common in patients with HF. In 2 reports, nearly all patients 
reported dyspnea during decompensation,6,7 and even when in ambulatory care,6 and edema was 
present in over two-thirds of those assessed. 6,7 The symptoms of dyspnea and fatigue were often 
related to one another in previous research studies (r=0.408 and 0.43,9 respectively). Further, 
patients’ responses to worsening symptoms were often to go to an emergency department (92% 
of 87 subjects)7 rather than to “do something” actively at home. In fact, very few called their 
doctor (17%; n=14) and of those, even fewer reached their doctor (6%, n=5). More patients 
waited for their next doctor’s appointment (30%, n=25).7 When patients were asked about self-
management, very few reduced salt intake (11%, n=9) or increased diuretic doses (10%, n=8), 
but elevating legs was more common (48%, n=40).7  Of note, patients took actions that would 
not be considered evidence-based therapies for HF; for example, patients drank more water 
(19%, n=16), took medications other than what was prescribed (16%, n=13) and reduced activity 
level (77%, n=64).7  
 
Most education materials in HF include a definition of HF and even a brief description of 
dyspnea, fatigue and edema. However, patients may not connect these danger signs with HF,10 
especially if they believe dyspnea, fatigue and edema are associated with external forces (stress, 
too much activity/not enough rest, pneumonia, chronic lung disease, anemia, worsening kidney 

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dysfunction, peripheral vascular disease, etc.), or if they believe there is no way to control these 
danger signs. In one report, of 571 patients who were assessed for understanding of HF signs and 
symptoms, only 38.7% had complete understanding, and of those with less than complete 
understanding, 22.1% had poor understanding.11 Further, when self-care adherence was assessed, 
it was associated with more complete understanding of HF signs and symptoms.11 In an 
integrative review of symptom perception among patients with HF, not only was symptom 
perception low, self-monitoring for worsening HF signs and symptoms was also low.12 There is a 
need to teach patients with HF about the most common danger signs of decompensation or 
worsening condition (even if they believe they still feel fine), and also to provide simple, 
practical actions to reduce danger signs and restore equilibrium when recognized.  
 
Media Design.  In the mid-1950s, Stanford University professor Albert Bandura began to 
explore and establish the principles of behavioral modeling: that people learn to enact behavioral 
skills best by observing those actions being modeled correctly and copying them. Over the next 
half century, thousands of experimental and field studies in refereed journal articles and the 
medical literature have identified and supported Bandura’s Social Cognitive Theory principles 
for effecting positive behavior change.13  
 
The power of modeling for behavior change was also found to be effective via media delivery – 
film, video, even photographic stills, called symbolic modeling – as long as the depicted 
modeling is designed and displayed according to well established social cognitive theory 
principles.14  
 
Wellflix behavioral-modeling videos address one weak link in the HF admission / intervention / 
recovery process: what happens after patients with HF have returned home and are no longer in a 
controlled clinical environment. The Wellflix behavioral design, informed by social cognitive 
theory principles, depicts in-home self-care behaviors that are aimed at maintaining heart health, 
such as recognizing danger signs and taking appropriate non-pharmacological actions to 
minimize them.  
 
Given that social cognitive theory principles can be successful in meeting outcomes when using 
media delivery and that new technologies enable easy accessibility to video in homes via digital 
video disc (DVD) player, computer and smartphone, this research endeavors to assess the 
effectiveness of symbolic modeling to promote positive heart health outcomes. Video delivery – 
via online and DVD – provides a 24/7 way for patients and family supporters to know how to 
recognize and respond to new or worsening dyspnea, fatigue and edema danger signs. The 
stimulus materials, designed by myself (the Principal Investigator) and Wellflix Inc, are not one-
size-fits-all informational videos. Each video is tailored to an individual patient’s gender, 
ethnicity, and language – one of the more than two dozen social cognitive theory design 
principles built into each video.  
 
It is unknown if in-hospital video education (with repeat viewing post-discharge as desired) that 
uses symbolic modeling and is aimed at enhancing recognition of and HF self-care response 
actions to new or worsening dyspnea, fatigue and edema danger signs, (a) reduces all-cause and 
HF-related healthcare resource utilization (HCRU), (b) improves perceptions of dyspnea and 
fatigue, and (c) improves self-efficacy for managing symptoms. Learning the HCRU effects of 

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symbolic modeling video education that explains the most common HF danger signs (dyspnea, 
fatigue and edema) and provides practical actions to reduce danger signs is important, as the 
intervention is easy to deploy, uses standard HF self-care behavior expectations, and is practical 
to use in hospital and home environments.  
 
It is important to learn the time to the video intervention effect on (a) HCRU outcomes and (b) 
perceptions of fatigue, dyspnea and self-efficacy for managing HF symptoms. The intervention 
may have an early effect (30-days) that wanes over time, have a steady effect over a 6-month 
period, or the effect may be slow to peak (i.e., 90 or 180 days) as patients may learn through a 
recognition and self-care action “trial and error” approach.  
 
Finally, the video intervention effect on outcomes may differ based on after hospital discharge 
viewing by patients and/or family supporters, as repeated viewing and/or family supporter 
viewing of danger signs and HF self-care actions may facilitate earlier recognition of warning 
signs and/or earlier or more accurate adherence to HF self-care actions that lead to improved 
HCRU outcomes, lower perceptions of fatigue and dyspnea and improved self-efficacy for 
managing symptoms.     
 
Study Purposes 
The purposes of this study are to examine the effects of HF danger signs videos (1 each on 
dyspnea, fatigue and edema) that include 2 key features: (1) recognition of each danger sign and 
(2) common, simple, practical self-are actions known to reduce HF danger signs ([a] fatigue: 
recognizing that it may be due to dehydration and adhering to physical activity and exercise 
expectations; [b] dyspnea and edema: adhering to a low sodium diet and fluid intake limitations; 
[c] all 3: contacting a doctor when appropriate). Based on Bandura’s social cognitive theory 
symbolic modeling, video content is meant to increase self-efficacy for independently 
completing self-care actions when dyspnea, fatigue and/or edema are present.  
 
The following outcomes will be assessed:  
PRIMARY 
1. 30 ± 6 days  first occurrence of post-discharge HF-related HCRU; defined as 
hospitalization, emergency department [ED) visits, death or cardiac transplantation/ 
ventricular assist device [VAD] implant-- individual components and combined),  
SECONDARY: 
2. 90- and 180-day ± 6 days  first occurrence of post-discharge HF-related HCRU; defined as 
hospitalization, emergency department [ED) visits, death or cardiac transplantation/ 
ventricular assist device [VAD] implant-- individual components and combined),  
3. 30-, 90- and 180-day± 6 days  first occurrence of post-discharge all-cause HCRU; defined as 
hospitalization, emergency department [ED) visits, death or cardiac transplantation/ 
ventricular assist device [VAD] implant-- individual components and combined),  
4. 30-, 90- and 180-day ± 6 days time to first occurrence of all-cause and HF-related post-
discharge HCRU (individual components and combined),  
5. 30-, 90- and 180-day ± 6 days total all-cause post-discharge HCRU (individual components 
and combined); 
6. 30-, 90- and 180-day ± 6 days total HF-related post-discharge HCRU (individual 
components and combined); 

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7. Change in functional status from baseline to 30-, 90- and 180-days ± 6 days  after hospital 
discharge, 
8. Change in dyspnea scores from baseline to 30-, 90- and 180-days ± 6 days  after hospital 
discharge,  
9. Change in fatigue scores from baseline to 30-, 90- and 180-days ± 6 days  after hospital 
discharge, and   
10. Change in self-efficacy for managing symptoms from baseline to 30-, 90- and 180-days ± 6 
days  after hospital discharge 
11. Differences in primary and secondary outcomes (1-10) among intervention-group 
participants, after creating 3 sub-groups based on post-discharge video viewing ([a] total 
number of times videos were watched, [b] viewed by caregivers/family in the hospital, and 
[c] viewed by caregivers/family post hospital discharge.  
 
Specific aims and hypotheses: 
1.   Determine the effects (and time to effects) of HF danger signs education on first occurrence, 
time to first occurrence and total all-cause and HF-related HCRU after hospital discharge: 
hospitalization, ED visit, death, cardiac transplantation or VAD. 
2.  Examine if functional status, dyspnea, fatigue and self-efficacy for managing symptoms 
scores change over time and the direction of change. 
3.  Among intervention group participants, determine if post-discharge re-viewing of danger 
signs education by patients and/or viewing content by family supporters is associated with 
differences in HCRU, functional status, dyspnea, fatigue and self-efficacy for managing 
symptoms, including time to effects. 
 
Hypothesis 1a: 30-day post-discharge HCRU will be lower or trend toward lower, and 90-, and 
180-day first occurrence, and total HCRU will be lower in the HF video danger education 
group compared to the usual care group.  
 
Hypothesis 1b: Time to first HCRU occurrence will be longer at 30-, 90- and 180-days in the HF 
video danger education group compared to the usual care group. 
 
Hypothesis 1c: Total HCRU will be lower at 30-, 90- and 180-days in the HF video danger 
education group compared to the usual care group. 
 
Hypothesis 2a: Functional status scores improve at 30-days and remain lower over time in the 
HF video danger education group compared to the usual care group.  
 
Hypothesis 2b: Dyspnea scores improve at 30-days and remain lower over time in the HF video 
danger education group compared to the usual care group. 
 
Hypothesis 2c: Fatigue scores improve at 30-days and remain lower over time in the HF video 
danger education group compared to the usual care group. 
 
Hypothesis 2d: Self-efficacy for managing symptoms scores are higher at 30-days and remain 
higher over time in the HF video danger education group compared to the usual care group. 
 

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Hypothesis 3a: Repeat viewing of videos by patients, compared to 1-time viewing in-hospital 
and/or viewing of videos by family supporters/caregivers in hospital and/or post discharge, 
compared to viewing only by patients will be associated with longer time to first HCRU and 
lower total HCRU. 
 
Hypothesis 3b: Repeat viewing of videos by patients, compared to 1-time viewing in-hospital 
and/or viewing of videos by family supporters/caregivers in hospital and/or post discharge, 
compared to viewing only by patients will be associated with improved functional status and 
dyspnea and fatigue scores (due to heightened awareness of danger signs, heightened 
recognition of worsening of danger signs) 
 
Hypothesis 3c: Repeat viewing of videos by patients, compared to 1-time viewing in-hospital 
and/or viewing of videos by family supporters/caregivers in hospital and/or post discharge, 
compared to viewing only by patients, will be associated with higher self-efficacy for HF 
self-care actions (due to symbolic modeling of self-care actions) 
  
METHODS 
Design: The study will use a 2-group, randomized, placebo-controlled, single blinded, design. 
Healthcare providers and unit nurses will be blinded to group assignment, but may learn about 
HF danger signs education if they enter the patients’ room during intervention delivery or discuss 
the intervention prior to hospital discharge.   
 
In brief, the research intervention involves 3 novel short videos (fatigue, dyspnea and edema) 
that will be viewed back-to-back by intervention group patients using a DVD player. Wellflix, 
Inc. videos are research-informed, use behavioral-modeling, are personally-tailored and are 
available 24/7 online. Patients will receive a handout sheet with the web address to view the 
videos after discharge and will be encouraged to view them with family members.     
 
Sample (including sample size calculation) and Setting 
A total of 732 patients will be enrolled (366 per group) and consist of adults with chronic HF 
(diagnosis ≥ 2 months) who are hospitalized for acute decompensated HF within Cleveland 
Clinic Hospitals. This sample size includes a 10% attrition rate. Sample size was based on power 
calculations using 30-day first occurrence of HF-related HCRU (hospitalization, emergency 
department visit, mortality, cardiac transplantation or VAD). The current expected 30-day HF-
related readmission rate is 20% among the control group. Allowing for other HCRU 
components, a control group HCRU rate of 28% is expected at 30 days. At 90 days, HCRU rate 
of 46% is expected in the control group. Sample size calculations were performed using SAS 
software (version 9.4; Cary, NC) and assume use of two-sided Pearson –chi square tests.  With 
329 patients in each group there will be 80% power to detect a 33% relative decrease (9.2% 
absolute decrease) in first occurrence of HF-related HCRU from a HCRU rate of 28% in the 
control group. With this sample size there would also be 85% power to detect a relative decrease 
of 25% (absolute decrease of 11.5%) from a control group event rate of 46% at 90-days. 
Allowing for 10% loss to follow-up, we will enroll 366 patients per group (732 total). 
 

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Patients will have decompensated HF with preserved or reduced ejection fraction when 
hospitalized and New York Heart Association FC III or ambulatory IV symptoms. Diagnosis and 
etiology of HF will be confirmed in the electronic medical record prior to enrollment. 
  
Inclusion Criteria: 
1. 
Not referred for cardiac transplantation or ventricular assist device placement during the 
index hospitalization (OK to be assessed for future placement), 
2. 
Minimum age 18 years (no upper age limit),  
3. 
Cognitively intact and able to view videos (adequate eyesight and hearing) with 
correction, if needed,  
4. 
Discharge to home, assisted living facility or to a family member’s home and can control 
dietary sodium and fluids as needed, 
5. 
Willing to participate; which may require up to three (3) follow-up telephone calls post-
discharge. 
 
Exclusions:  
1. 
Chart documented psychiatric or cognitive conditions that limit ability to understand 
video content or adhere to self-care recommendations (Alzheimer’s condition, dementia, 
schizophrenia, other neurological history that impairs memory or concentration), 
2. 
Plans to discharge to skilled nursing facility or hospice care, 
3. 
Receiving home hospice or palliative care; or has a medical condition reflecting less than 
 
1 year of survival (cachexia, end stage liver disease or cancer or non-ambulatory New 
 
York Heart Association functional class IV HF), 
4. 
Hospitalized but at admission, in New York Heart Association functional class I or II HF  
5. 
Post-cardiac transplantation or ventricular assist device placement, 
6. 
Currently enrolled in another experimental HF research study,  
7. 
Chronic renal failure and receiving chronic hemodialysis therapy for an estimated 
glomerular filtration rate < 15 mL/minute/1.73 m2, 
8. 
A non-traditional form of HF (hypertrophic or restrictive forms of cardiomyopathy, 
congenital heart disease or Takotsubo cardiomyopathy).  
 
Intervention 
The fatigue and dyspnea video’s will be viewed back-to-back and the edema video will be added 
for patients with a history of edema. There are 4 versions of each video: (1) based on race 
(Caucasian and African-American) and sex (male and female)—to promote symbolic 
modeling— by patients who look like video models (as stated in the introduction). Scripts for 
each video were developed jointly by Peter Orton, PhD, Director of Media and Education for 
Wellflix, Inc. and Nancy Albert PhD, principal investigator and clinical nurse specialist in HF. 
Content includes recognition and assessment of fatigue, dyspnea and edema and specific actions 
to take to reduce the danger signs or prevent worsening (dietary sodium and/or fluid restriction, 
physical activity/exercise and contacting the doctor).  
 
Overall video viewing time for all 3 videos is 9:50 minutes; the fatigue and dyspnea videos that 
all intervention patients will view are 6:50 minutes:  
• Fatigue is 2:20 minutes + end text list= 3:00 minutes;  

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• Dypsnea is 1:40 minutes + dyspnea “yes” or “no” management (2 options; patient selects the 
option that matches current status) = 3.50 minutes  
• Edema is 2:40 minutes + end text list= 3:00 minutes;  
 
During hospitalization, videos will be loaded into an iPAD and will be viewed through the 
iPAD.  
 
Patients have an opportunity to view videos post-discharge as desired and able. Post discharge, 
videos can be in 2 ways: (1) via the Wellflix, Inc. site at www.wellflix.net/DangerSignsCC or (2) 
by DVD player (DVD created by Wellflix, Inc for this research), for patients who have DVD 
player capability and prefer this method.  
 
NOTE, at/after 180-day follow up data are collected, usual care group patients will be offered 
access to Wellflix, Inc. videos used in this research study via mailing of a handout sheet 
developed specifically for them (that contains the web address and a note of encouragement to 
view the videos.    
 
Outcomes and Measurement 
HCRU. Includes all-cause and HF-related hospitalization, ED visit, death, cardiac 
transplantation, or VAD placement at 30-, 90-, and 180-days ± 6 days  in both groups. Data will 
be retrieved from medical records when available or via telephone call to patients.  
 
• Patients will receive a calendar to keep track of HCRU events in-between phone calls.  
• Research nurses will use a case report form to record HCRU events 
 
Functional status: The Duke Activity Status Index (DASI)15 developed in a sample of 
people undergoing cardiac exercise testing and now routinely used to assess functional status in 
patients with cardiac disease. The DASI is a 12-item questionnaire using a Likert-like scale that 
determines a patient’s ability to participate in common, everyday activities without difficulty, 
including self-care activities (1 item), ambulation (4 items), housework (3 items), yard work (1 
item), sexual relations (1 item), and recreational activities (2 items).15 Each item is weighted to 
reflect the metabolic equivalent (MET) used during the activity. A total score reflects functional 
status based on responses to each item. Scores can range from 0 (most severe functional 
impairment) to 58.20 (no functional impairment). Several investigators have investigated the 
reliability and validity of the DASI.15-18  The internal consistency of the DASI measured by 
Cronbach’s alpha has been found to be acceptable in HF patients.16 Test-retest reliability also 
was examined and determined to be acceptable in patients with HF.16 The validity of DASI was 
demonstrated in subjects undergoing graded exercise testing who demonstrated a high 
correlation (Spearman correlation coefficient from .58 to .80) with peak oxygen uptake.15 In 
addition, the DASI varied in a consistent manner according to different clinical factors known to 
affect patient functional capacity in patients with cardiac disease.17 When DASI results were 
correlated with other functional and health status measures, moderate to strong correlations were 
found: New York Heart Association (r, -64; P < 0.001); six minute walk test (r, 44; P < 0.01);  
Kansas City Cardiomyopathy Questionnaire physical limitations component (r, 68; P < 0.001); 
Kansas City Cardiomyopathy Questionnaire clinical summary  (r, 60; P < 0.001) and estimated 

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metabolic equivalents calculated from peak treadmill speed and grade (r, 46; P < 0.01).18  DASI 
will be assessed at enrollment and scores will be used as interval level data in analysis. 
 
Dyspnea: The Patient-Reported Outcomes Measurement Information System® (PROMIS®) 
Dyspnea Functional Limitations – Short Form 10a has been used in patients with idiopathic 
pulmonary fibrosis19 and systemic sclerosis.20 The tool was able to discriminate health-related 
quality of life deficits and cough severity19 and when traditional dyspnea measures were 
compared with PROMIS dyspnea short form results, significant correlations were found.20 The 
tool measures dyspnea by asking 10 questions about difficulty in completing activities in the past 
7 days. Response options use a Likert-type scale from 0, no difficulty to 3, much difficulty and 
there is an option for “I did not do this in the past 7 days”.   
 
Fatigue: Fatigue is a hallmark symptom of HF that may decrease energy and reduce the 
patient’s desire to exercise. The Fatigue Assessment Scale is a 10-item self-rated measure of 
fatigue with 5 answer categories; 1 = never to 5 = always, that has been assess in patients with 
end-stage heart failure,21 as well as in patients with stroke and in working adults. In factor 
analysis, this tool correlated strongly with 4 other fatigue scales; however, this tool had the 
highest factor loading on a clear one-factor solution.22  
 
Self-efficacy for managing symptoms. Validation of the PROMIS Self-Efficacy for 
Managing Symptoms forms were completed among 1087 subjects that included patients with 
chronic neurologic conditions (epilepsy, multiple sclerosis, neuropathy, Parkinson disease, and 
stroke) and general chronic conditions and compared with a traditional self-efficacy measure and 
5 PROMIS short forms that measured physical and mental global health, physical function, 
fatigue, depression, and anxiety.23 Researchers found strong correlation between all forms of the 
PROMIS and the traditional self-efficacy measure (rhos, 0.56 to 75).23 In this research study, the 
PROMIS Self-Efficacy for Managing Symptoms Short form 8a will be used.23 The 8-item tool 
uses a Likert-type scale from 1, I am not at all confident to 5, I am very confident.  
 
Patient characteristics and medical history at baseline. Standard patient characteristics 
that are used in many research studies of patients with HF, will be used in this research as they 
span themes of interest and provide global information about participants. Items include height 
and weight, highest education, comfort living on current household income, current signs and 
symptoms of HF, comorbid conditions and billing data retrieved from Cleveland Clinic billing 
database (age, race, gender, marital status, discharge disposition, and length of hospital stay). 
The Charlson Comorbidity Index will be used to collect medical comorbidity history. This index 
was developed to classify comorbid conditions which might change the risk of mortality.24-29 The 
score will be categorized into 3 groups (score of 1-2 = 1; 3-4 = 3; 5 or more = 5). In one study 
with 33,940 patients with ischemic heart disease, the grouping demonstrated a strong relationship 
with mortality rate.29 In 2011, the tool was reduced from 19 items to 12 items and each item was 
re-scored based on morbidity and mortality of medical conditions in the current era of medical 
therapies.30 This data will also be used to describe the sample groups for similarity in acuity.   
   
Video Watching Experiences in-hospital and at 30 day follow-up (intervention group 
only). A 3-item, investigator-developed survey will assess video watching characteristics: total 
number of watching’s, caregiver/family member video watching in the hospital, and 

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caregiver/family member video watching in the post discharge period, up to 30 days. Items use 
choose-the-best-response options.  
 
Data Collection 
Medical records will be assessed for inclusion and exclusion criteria before approaching patients.  
Research personnel will explain the study in a patient’s room (in non-private rooms, a curtain 
will be drawn to separate beds and enhance confidentiality). After received verbal informed 
consent, patients will complete baseline data that includes assessment of functional status, 
dyspnea, fatigue and self-efficacy for managing symptoms immediately before hospitalization. 
Administration of the functional status, dyspnea and fatigue questionnaires will be randomly 
changed for each participant to allow for counterbalancing, since there item themes may have 
overlap/be similar. Baseline data collection should take 10 minutes or less. 
 
After completing baseline paperwork, patients will be randomly assigned to the usual care or 
usual care plus HF danger signs video education group using block randomization; with blocks 
of 20, to decrease the influence of external factors that could alter outcomes. The randomization 
assignment will be made by a QHS statistician.  
 
 
After randomization to groups: 
• Intervention group patients will receive usual hospital care and also, HF danger signs 
education via iPad by research personnel. Danger signs education can be administered at the 
time of enrollment. There is no need to wait until day of discharge, since HF danger sign 
messages are not individualized and discharge is a very busy time. Immediately prior to 
discharge, patients’ focus may be on preparing to leave the hospital and not on education 
about HF, especially if patients believe that they have accurate perceptions of HF danger 
signals, even though in previous research, most subjects did not.   
• Usual care group patients will be educated by their healthcare providers (including 
nurse/other caregivers). Education may include Elsevier HF videos that are shown on 
Cleveland Clinic hospital televisions.   
 
A research nurse will use telephone calls or mailing methodologies to have the following 4/5 
tools (40/43 items in total for usual care and intervention groups, respectively) completed at 30 ± 
6 days: functional status, dyspnea, fatigue, self-efficacy for managing symptom and video 
watching experiences. Administration of functional status, dyspnea, and fatigue questionnaires 
will be randomly ordered (counterbalanced). The intervention-only group survey on video 
watching experiences will be administered last. It is expected that data collection will take ~ 10 
minutes or less.  
 
A research nurse will review EMRs of enrolled patients after the index (baseline) hospital 
discharge and at 30-, 60-, 90- and 180-days (± 6 days) for HCRU events.   
• If not found in the EMR, telephone calls will be made to gather data.  
• At baseline, research nurses will obtain home telephone number and the telephone number of 
a close relative or friend that can provide patient contact information, as needed.  
 
 

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Analyses 
Patient characteristics will be summarized overall and by randomized group using frequencies 
and percentages for categorical factors and means and standard deviations for continuous 
measures. First occurrence HCRU use (all-cause and HF-related) will be compared using 
Pearson chi-square tests. Time to first HFCU use will be summarized using Kaplan-Meier 
estimates, and compared using log-rank tests and Cox proportional hazards models.  Total 
HCRU use will be compared using Poisson regression models. Linear mixed effect models will 
be used to evaluate trends in functional, dyspnea, fatigue, and self-efficacy measures over time 
and, if trends significantly differ, comparisons within time point will be performed.  Secondary 
analyses will use similar methods to compare patients in the video group, stratified by video 
viewership, on the same outcomes. If appropriate, exploratory analyses will also be performed, 
comparing the above outcomes between treatment groups, adjusting for any patient 
characteristics that differ between randomized groups. Analyses will be performed using SAS 
software (version 9.4; Cary, NC), and an overall significance level of 0.05 will be assumed for 
all endpoints. Comparisons between the 3 subgroups of patients in the video group will use 
Bonferroni corrected significance criteria to preserve the overall error rate when making multiple 
comparisons. 
 
Feasibility 
The main campus of Cleveland Clinic has a high volume of HF discharges each year. Other 
hospitals in the system have moderate volumes of HF discharges, and are less likely to have 
patients who meet exclusion criteria due to enrollment in another research study or non-
ambulatory NHYHA FC IV (advanced) HF. Electronic medical records allow for review of data 
on events that occur in all system hospitals and regional medical practice ambulatory care sites; 
decreasing the need to rely on patient recall of HCRU.  
 
The HF danger signs videos provide information that patients should understand, but that may 
not have been explicitly explained previously; therefore, it may be considered an extension of 
usual care education. Ideally, no new information is presented; as patients receive content about 
HF signs and symptoms and HF self-care actions via CC video education (in-hospital, when 
attentive) and via the HF handbook, which is sent home and can be re-given in ambulatory care. 
Danger signs video content was based on symbolic modeling; and has a repeatable format, if 
patients in the intervention group choose to utilize the on-line 24/7 viewing option post 
discharge. Patients do not need to be able to read and if they are forgetful or have mild memory 
impairment that was not documented at enrollment, they can replay videos multiple times.  
 
Research personnel from the Office of Nursing Research and Innovation will recruit subjects, 
apply the intervention and collect data (at all sites). The main campus has multiple research 
projects in place, led by physicians, myself and other RNs. Research team personnel are 
accustomed to working with cardiology research nurses, as needed, to ensure patients are not 
approached for more than 1 research study.    
 
Instruments that will be completed at baseline may be self- or research nurse-administered 
(patient demographics, HF characteristics, danger signs [dyspnea and fatigue], functional status 
and self-efficacy for managing symptoms). The patient demographics and HF characteristics 
instruments have been used many times in previous HF research and are short, simple and quick 

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to complete. Patients may become fatigued when completing baseline data collection forms; 
however, all 6 tools have only 71 items (in total) and all tools are short (12 or less items; each 
one should take about 3 minutes to complete).  
• At baseline, all 6 tools should take and take under 20 minutes to complete. In previous 
research, patients were NOT burdened by data collection that included similar length 
instruments.  
• At follow-up, telephone calls are only made when HCRU data is not available in medical 
records at 60-, 90- and 180-days. Data obtained from electronic medical records is 
consistently present, minimizing the occurrence of missing data.  
• At 30-day follow-up, there are 2 options to collect data on 4 tools with 40 items in total, that 
will take ~ 10 minutes or less to complete (usual care group) or 5 tools with 43 items in total, 
that will take ~ 10 minutes to complete (intervention group) and include functional status, 
dyspnea, fatigue self-efficacy, and a 3-item video viewing experience survey for the 
intervention group, by telephone or mail. As a secondary method, patients who are 
hospitalized during the follow-up period may receive tools in person by a research nurse.    
 
Limitations and Anticipated Problems 
Patients and caregivers may never view the Wellflix, Inc. HF danger sign videos after discharge, 
and/or forget content viewed during hospitalization. Patients may view/hear, but ignore, message 
content. Patients may drop out before the 180-day follow-up data collection. Analyses will be 
completed using “intent to treat” methods. In this way, we will be able to learn the effect size of 
the intervention among all patients randomized to the intervention group.   
 
No adverse effects are anticipated, as the intervention in this research are HF danger signs videos 
that cannot create harm to patients. Video scripts provide messages that may be available in 
commercially available videos and or written materials used in usual HF care education and 
discharge instruction materials. There are no risks of adverse events from the intervention itself.  
 
Human Subjects Protection 
Approval by the Cleveland Clinic Institutional Review Board will be sought prior to study 
initiation. We believe this study is minimal risk as the intervention is composed of back-to-back 
video viewing of 3 HF danger signs (fatigue, dyspnea and edema). Video self-care messages 
delivered through demonstration, imitation and modeling are part of usual heart failure post-
discharge care, but are delivered using principles of Bandura’s social learning theory, to enhance 
ability to complete independently after viewing videos.  
 
One data collection form will use a research number and CCF medical record number; as it will 
also contain names and phone numbers; however, all other baseline and follow-up data collection 
forms contain only research numbers. Only the research number will be recorded in the 
electronic database. Paper forms will be kept in a locked cabinet, in a locked office of the 
principal investigator and will be destroyed upon assurance that data in the electronic database is 
high quality, after enrollment is completed. Electronic data for analysis will use a research 
number; no patient identifiers will be used. All study results will be reported in aggregate.  
 

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SPSS will be the electronic database used to capture paper data. The electronic database will be 
maintained for 6 years after study completion. Paper documents will be destroyed once the initial 
analysis is complete.  
 
This research project will be registered in www.clinicaltrials.gov.  
 
References 
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Sciff GD, Fung S, Speroff T, McNutt RA. Decompensated heart failure: symptoms, 
patterns of onset, and contributing factors. Am J Med. 2003;114:625-630.  
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Stephen SA. Fatigue in older adults with stable heart failure. Heart Lung 2008;37:122-
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Timeline* 
 
Work 
2018 
2019 
Apr 
May 
Jun 
Jul 
Aug 
Sept 
Oct 
Nov 
Dec 
Jan 
Feb 
Mar 
Apr 
Startup 
work** 
 
 
 
 
 
 
 
 
 
 
 
 
 
Patient 
enrollment, 
data 
collection 
and data 
entry into 
database 
 
 
 
 
 
 
 
 
 
 
 
 
 
Patient  
follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
Data entry 
 
 
 
 
 
 
 
 
 
 
 
 
 
**, secure video links/iPADs to play videos; secure web link for post discharge video viewing 
(Wellflix to do); identify/train research nurses; prepare randomization cards/envelopes; obtain 
IRB approval; develop database  
 
Timeline*, continued 
 
Work 
2019 
2020 
May Jun 
Jul 
Aug Sept Oct 
Nov Dec 
Jan 
Feb Mar Apr 
May Jun 
Patient 
enrollment 
and data 
collection 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Patient 
follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Data entry   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Timeline*, continued 
 
Work 
2020 
2021 
Jul 
Aug 
Sep Oct 
Nov  Dec Jan Feb Mar 
Apr 
May Jun 
Patient follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
Data Cleaning  
 
 
 
 
 
 
 
 
 
 
 
 
Data Analysis 
 
 
 
 
 
 
 
 
 
 
 
 
 
2021 
2022 
Work 
Jul 
Aug 
Sep Oct 
Nov  Dec 
Jan 
Feb 
Mar 
Apr 
May 
Abstract shared w 
stakeholders 
 
 
 
 
 
 
 
 
 
 
 
Abstract submission 
at Nat’l Mtg; 2021† 
 
 
 
 
 
 
 
 
 
 
 
Publication develop/ 
submit 
 
 
 
 
 
 
 
 
 
 
 

18 
NCT-03657459 
V2_11-07-18  
 
*, Timeline subject to change based on number of sites participating and cases enrolled/month. 
The prepared timeline is conservative; timeline may be shortened to 1.5 years if multiple sites;  
† i.e. late breaking clinical trial at HFSA or AHA, or submit to a 2022 annual meeting (i.e., 
ACC).