Group Medical Visits in Heart Failure for Post-Hospitalization Follow-Up
Phase: NA
Conditions: Heart Failure
Sponsor: VA Office of Research and Development

Group Medical Visits in Heart Failure (MEDIC-HF)
12/17/2018
NCT02481921

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Group Medical Visits in Heart Failure for Post-Hospitalization Follow-Up 
Version 11/18/2014, 12/12/14, 3/13/2015, 4/17/2015, 6/02/2015, 9/21/2015, 11/01/2016, 12/17/2018 
 
SPECIFIC AIMS 
The primary goal of this research project is to improve the health status and decrease 
hospitalization and death for patients discharged with heart failure (HF) via self-management education 
to patients, disease monitoring and medication titration through shared medical appointments (SMAs).   
HF is a complex chronic illness where patients have a significant impairment of health status,1 with a 
high burden of morbidity and mortality. Half of Americans who develop HF die within 5 years of diagnosis2 and 
more than 1/3 of HF patients require frequent hospitalizations,3 or placement in long term care.4 Studies have 
found patient self-care behaviors in HF (e.g. medication/dietary noncompliance) and health system factors 
(e.g. care discoordination, limited access, lack of education to patients and caregivers) played important roles 
in patient outcomes to the extent that 50% of the readmissions were judged to be possibly preventable.5,6  
Based on an operational model of effective chronic disease management (Chronic Care Model),7,8 one 
potential solution to addressing patient and system factors is redesign of care delivery, via SMA’s, to provide 
self-management support to patients (and caregivers when available) while also performing disease monitoring 
and medication management in an environment of peer support. Our previous successes in conducting SMAs 
for diabetes9-11 suggested that these tasks can be accomplished in a coordinated and efficient manner by a 
multi-disciplinary team of non-physician health care professionals in an SMA setting to address patient and 
system factors related to low health status and outcomes surrounding patients with HF. However, there is a 
paucity of literature about HF-SMAs in general,12-14 and none in the effectiveness of HF-SMA in improving 
health status in HF. Given that patients discharged with HF are susceptible to declining health and 
hospitalization, it would be important to know if, how and to which groups, the successes in diabetes SMAs can 
be translated into HF, a disease with a higher morbidity and mortality. Although both Providence and Phoenix 
VAMCs have been conducting HF-SMAs for a combined total of 4 years, only 20-30% of eligible patients are 
referred to HF-SMA. A major barrier for implementation is the lack of effectiveness data. Thus, a rigorous 
assessment of HF-SMA effectiveness along with a pre-implementation assessment of potential barriers using a 
mixed method approach is needed prior to dissemination. This research, while focused at HF, will contribute to 
advancing implementation of SMAs as a team-based intervention for other chronic complex conditions. 
We propose a 2-site randomized-controlled effectiveness trial with mixed methods to test a SMA 
intervention provided by a non-physician team of nurses, nutritionists, health psychologist, and nurse 
practitioners and/or clinical pharmacists, versus usual care to improve patient’s health status and reduce 
hospitalizations and death in HF after discharge. In this trial, patients within  12 weeks of a HF hospitalization 
and/or IV diuretic therapy will be randomized to receive either HF-SMA versus usual care. The HF-SMA will 
consist of four sessions of 2-hour duration that occur every other week for 8 weeks or based on the clinics’ 
appointment availability. The session will start with an assessment of patients and their needs followed by pre-
assigned theme-based disease self-management education, followed by patient-initiated disease management 
discussion, and conclude with break-out sessions of individualized disease monitoring and medication case 
management. The study duration will be 180 days for all patients from the day of randomization.  The specific 
aims are: 
Primary Aim: 
Aim 1: To determine whether HF patients who participate in HF-SMA, as compared to usual care, experience 
better cardiac health status measured by Kansas City Cardiomyopathy Questionnaire15-17 (primary outcome), 
and overall health status (EQ-5D, secondary outcome), from baseline to 90 and 180 days. 
Hypothesis:  HF patients who participate in HF-SMA will experience better cardiac and overall health 
status than patients who receive usual care from baseline to 90 and 180 days after randomization.  
Secondary Aims: 
Aim 2: To determine whether HF patients who participate in HF-SMA, as compared to patients who receive 
usual care, have fewer hospitalization or death, at 90 and 180 days 
Hypothesis:  HF patients who participate in HF-SMA will have fewer hospitalizations or death than 
patients who receive usual care from baseline to 90 and 180 days after randomization.  
Aim 3: To determine whether HF patients in HF-SMA, as compared to patients in usual care, experience 
improvement in intermediate outcomes, namely, process (HF Self-Care behaviors) and physiologic (plasma 
BNP levels) measures from baseline to 90 and 180 days after randomization. 

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Hypothesis:  HF patients in HF-SMA, as compared to patients in usual care, will experience an increase 
in HF Self-Care behaviors and decrease in BNP levels from baseline to 90 and 180 days after randomization. 
Aim 4: To determine for HF-SMA, perceived benefits, areas in need of improvement, potential obstacles of 
implementation, and fidelity of the intervention across sites, by conducting (1) face-to-face interviews with a 
selected sample of patients and (2) telephone interviews with stakeholders (physicians of the patients who 
underwent HF-SMA and physician administrators). 

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A. BACKGROUND & SIGNIFICANCE 
The primary goal of this research project is to improve the health status and decrease 
hospitalization and death for patients discharged with heart failure (HF) via self-management education 
to patients, disease monitoring and medication titration through shared medical appointments (SMAs).   
Significance & Scope of the Problem 
HF currently affects 5.1 million people in the US and 825,000 new HF cases are being diagnosed 
annually.18 HF is a leading cause of cardiovascular disease morbidity and mortality worldwide, costing 1-2% of 
the total healthcare budget in developed countries.19 In 2009 alone, 1 in 9 deaths in the US cited HF as a 
contributing cause.20 Half of Americans who develop HF die within 5 years of diagnosis2 and more than one 
third of HF patients require frequent hospitalizations,3 or placement in long term care.4 HF has a particularly 
higher impact among older people (≥65 years old) and those with multiple co-existing illness,21,22 with ≥90% of 
HF-related deaths to occur among people ≥65 years.21,23,24 With 1 in 10 elderly living with HF25 and an aging 
population in the US, HF mortality and morbidity greatly impacts the health of our Veteran population. Indeed, 
our preliminary data from a random cohort of >100,000 patients admitted with HF at VHA hospitals nationwide, 
showed the HF veteran population to be elderly (average age = 71 years), and has 30-day and one-year 
mortality rates of 6 and 30%, respectively, after their hospitalization.26 Since the main goal of the VHA is to 
improve health of the veterans, patient-reported health status is an important outcome metric for HF patients 
that includes symptom burden, functional status and health-related-quality-of-life, and an independent predictor 
of mortality, cardiovascular events, hospitalization and cost of care.27 HF patients have a significant impairment 
of health status,27 in both physical and mental health,28,29 in addition to declines in functional status.30  
Patient and System Factors Related to Patient Outcomes in HF 
Studies have found patient and health system factors played an important role in patient’s health status 
and symptoms to the extent that 50% of the readmissions were judged to be possibly/probably preventable.5,6 
Patient factors included behaviors such as medication (15%) or dietary sodium (18%) non-compliance,31-33 and 
failure to promptly seek medical attention (20%),5 and social factors such lack of a social or peer support to call 
for problems.5 Behavioral factors were a key component and calls for the need of a structured learning and 
behavioral modification approach such as the SMA approach. Factors contributing to medication non-
adherence included too many medications,31 dissatisfaction with medicine information provided, and concerns 
about the potential adverse effects of medicines.31,34 Barriers related to dietary sodium restrictions include low 
knowledge about dietary sodium,35 and the poor taste of food on the low sodium diet.35 Lack of knowledge in 
early symptoms of HF decompensation was one of the main reasons for treatment-seeking delays, with a 
median duration of early symptoms to treatment of 5-7 day delay.5,6 Hospital factors included inadequate care 
coordination (discharge planning and/or follow-up), inadequate patient and caregiver education and support 
(e.g. who to call for problems), and limited access to providers after hospitalization.5,6 Traditional settings of 
one-to-one visits are labor intensive and inefficient in addressing these multi-disciplinary needs.7,36 SMAs, 
described further below, is poised to fulfill the above needs by providing education and behavioral intervention, 
medication management and disease monitoring in a group setting of peer support. 
SMA for Chronic Disease Management in HF and Gaps in the Evidence  
Based on an operational model of effective chronic disease management (Chronic Care Model),7,8 one 
potential solution to addressing both patient and health system factors is redesign of care delivery, via “SMA’s” 
to educate patients (and caregivers if available) about HF self-care thereby enabling behavioral modification 
while also performing disease state monitoring and medication management. Group medical visits or SMAs 
are defined as visits in which several patients meet with one or more provider(s) at the same time,37 and 
typically involve a multidisciplinary team of a health psychologist, a prescribing provider, and a documenter.38 
An important distinction is that SMAs are not ‘classes’ because they provide individualized medication 
prescribing and clinical monitoring of patient health status. SMA also distinguishes itself from the traditional 
case management or disease management models, which is usually provided by one provider to one patient at 
a time.39,40 As such, SMA is a comprehensive disease management program, where several patients with the 
same disease can meet with multidisciplinary health professionals in the same setting, in a coordinated 
fashion, for efficiency and improved access, and where behavioral change can be facilitated through education 
and group peer support (details below under behavioral change).9-11 Thus, we postulate that the change in self-
care behaviors, and individualized medication prescribing and clinical monitoring in HF-SMA will lead to 
improvement of patient’s health status, decrease in symptoms and BNP levels (a biological measure of the 
severity of HF)41-43 and subsequent decrease in hospitalizations and possibly mortality for HF.  

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Although studies have shown that some disease management programs may improve patient 
outcomes in HF,39 the effect and complexity of disease management programs are highly heterogeneous.44 
Some interventions did not improve patient outcomes,45 including an intensive model that involved close follow-
up by their primary care provider, beginning before discharge and continuing for six months.46 These findings 
call for the need of additional models that could potentially account for both efficacy and efficiency, such as 
SMAs in HF. Our previous successes in SMAs for diabetes,9-11 and those of others,47,48 suggest that this 
approach to be an ideal setting to empower patients with HF self-care skills and induce change in self-care 
behaviors in HF in addition to medication management and disease monitoring to improve their symptoms and 
health status. However, effectiveness of SMAs in HF management is unknown, and unlike patients with 
diabetes, a mostly asymptomatic disease in its initial stages, HF patients are vulnerable, especially after 
hospitalization, with a constant risk of further decline in health status or death.49 Indeed the national VHA data 
showed that ~20% of these patients are readmitted within 30 days of their discharge.50  
As stated by a systematic review commissioned by the VHA QUERI on SMAs, there is little evidence 
on the effectiveness of SMAs in disease conditions other than diabetes and there are uncertain effects of 
SMAs on physiological variables other than HbA1c.48 A key gap noted in this recent meta-analysis of SMAs 
was the lack of evidence for SMAs in patients with HF.48  In our literature survey, there are only 3 small studies 
of SMAs in HF reported, and 1 RCT (n=198) that is single-center, in a non-VHA setting, education-focused 
(without disease monitoring or medication titration), and not targeted to the recently hospitalized population.51 
Three small studies addressed different mechanisms at which HF-SMA may improve outcomes. An 
observational HF-SMA study (n=39) from the Naval Medical Center, San Diego, reported that HF-SMA 
resulted in improvements in self-care after 6 months.14 Another study (n=52) of HF-SMA found improvements 
in the HF knowledge in patients randomized to HF SMA.12 A pilot of 20 patients showed that satisfaction with 
SMA was high among patients and office staff. 52 But, none of these studies reported significant differences in 
health status or hard endpoints. The single-center RCT showed trend toward improvement in hospitalization or 
death that support potential for HF-SMA in improving hard outcomes in this proposal.51 Because SMAs are not 
a pharmacotherapy, the precise elements of the intervention will differ by health condition and need to be 
elucidated and refined for HF, which will be effected in this proposal. Preliminary data from Providence VAMC 
and Phoenix VAMCs indicated that hospital readmission rates for HF patients enrolled in SMAs are lower than 
secular controls (details under pilot), but only 20-30% of patients are referred to HF-SMAs. A major barrier for 
increased local implementation is the lack of rigorous effectiveness data.  Thus, there is a need for a rigorous 
assessment of effectiveness prior to being able to transfer the successes from diabetes SMAs to HF.  
HF-SMA, Patient-Centered Care and Patient Aligned Care Teams (PACT) 
HF-SMA is in alignment with the current VHA PACT principles,53 where access (currently a primary 
concern VHA wide) will be enhanced through SMAs (allows for up to 6 HF patients per session, with their 
caregivers if present), and patients will be exposed to a team of multi-disciplinary health care professionals, 
where they will receive more quantity of care but also quality of care due to providers of diverse expertise,48 in 
a single coordinated care program. Given that patients often have concerns that span several clinical 
disciplines (e.g. dietary, medications, lack of social support [who to call for problems], worsening health status), 
the opportunity of having a provider with needed expertise to help a given patient’s problem is greater in this 
HF-SMA setting as opposed to the traditional one-provider clinic setting alone. Available evidence suggests 
that approaches targeting patient’s needs for self-care and case management, such as the proposed HF-SMA, 
are likely the most clinically relevant and effective intervention for HF.54-56 This approach is also concordant 
with the Patient-Centered Medical Home model (which are also VHA PACT principles),53 characterized by: 
whole-person orientation, coordinated and integrated care, quality and safety 57-59 and enhanced access. The 
Chronic Care Model (mapped in Figure 1 below) can help explain how the SMA approach can align the needs 
of the patients with existing hospital resources.7,36  
HF-SMA and Alignment of Health System Resources with Patient-Centered Care, the Chronic Care Model  
The Chronic Care Model is a disease management approach comprised of 6 components: 1) care 
delivery system re-design (e.g. SMAs), 2) linking the patient to community resources (exposure to available 
community and VHA resources), 3) self-management support (e.g. education toward behavioral modification), 
4) provider decision support, 5) use of electronic medical record system and 6) a system-wide commitment to 
quality.7,36 Both electronic medical record system and organizational commitment to quality are both VHA 
standards. Our proposed HF-SMA will build upon the pre-existing infrastructure to complete the components of 
the Chronic Care Model. The use of non-physician health care professionals in a group approach to 

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complement traditional physician care is another example of the system re-design. The medication 
reconciliation during HF-SMAs is a good example of provider decision support and preserves quality and 
safety of care by coordinating care from different multi-disciplinary providers, and should increase stakeholder 
(treating physician) satisfaction. The patient and care-giver education (self-management support) followed 
principles of patient-centeredness for patient empowerment and engagement and should enhance patient 
satisfaction. Additional HF-related care including disease monitoring, medication effect monitoring, and 
referrals into additional support programs (link to resources) addresses the patient-centered medical home 
principles of enhanced access, whole-person orientation, quality and safety, and integrated care. 
Potential for HF-SMA to promote behavioral change  
In addition to disease state monitoring and medication management, HF patients require intense 
training in self-care, such as weight monitoring and adherence to diet and medications, and early symptom 
recognition,60 which is difficult and time-consuming to provide in the traditional one-on-one visit setting. Based 
on the self-management support and system re-design constructs of the chronic care model, HF-SMA has the 
potential to address the self-care needs of these patients in a coordinated and efficient manner. The 
mechanisms at which the self-management support in HF-SMA could lead to behavioral modification can be 
explained, at least in part by the Social Cognitive Theory (Figure 1). Based on the Social Cognitive Theory, 
promotion of healthy self-care behaviors in the SMA setting such as sodium restriction, weight-monitoring and 
medication adherence can be explained by determinants at the personal and environmental levels.61-64 At the 
personal level, the SMA providers will use interactive discussions to shape expectations (anticipatory 
outcomes of a behavior) in an environment of peer support and use the group dynamic (environmental factor) 
to promote observational learning (behavioral acquisition that occurs by watching the actions and outcomes of 
other’s behavior which include credible role models). The SMA provider will provide reinforcement for healthy 
behavior (both direct and vicarious); and will foster self-control (regulation of goal-directed behavior 
performance, self-monitoring, goal setting, problem solving and self-reward) through self-reinforcement and 
promotion of self-efficacy,65 to increase healthy behaviors stated above.  In addition, social support is also 
increased through education of family and support members when present. Our previous studies of SMAs in 
diabetes have shown positive results in improvement in self-care behaviors and glycemic control.9,11   
 
Significance of HF-SMA:  

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Given the impact of HF to the US population and to the VHA, this proposal is significant because SMA 
is an innovative and potentially transformative care model to improve health status, and reduce hospitalization 
or death, for veterans with HF. The current proposal is also responsive to the VHA HSRD Research Priorities 
of “Assess innovative approaches to improve access…for a vulnerable veteran population,” such as the one 
studied, with multiple comorbid illnesses. The challenge of providing patient-centered care for veterans with HF 
is an urgent problem due to an increasing limited access to health care providers,66 an increased HF 
prevalence due to an aging population and improved heart disease survival,20 and an acute care-focused 
health system. HF-SMA is a tool of system re-design that has the potential to provide patient-centered care in 
a resource-constrained system while enhancing patient access. Given the potential benefits and evidence of its 
efficacy in diabetes, use of SMA’s have become a quality metric within the VA National Primary Care strategic 
plan,67 but steps of its use in HF is still unknown.  Thus, this project will help determine whether SMAs should 
be deployed and how they can be used in HF care. The alignment of HF-SMA with PACT principles and the 
VA National Primary Care strategic plan will facilitate implementation if proven effective. Our qualitative 
assessment will also help VHA in the understanding of potential barriers to implement HF SMAs. Given the 
impact and the potential contributions to the VHA, we have the support from CHF QUERI (Dr. Heidenreich), 
National Pact Coordinator (Dr. Kirsh) and the National Director for Cardiology (Dr. Rumsfeld) to help us 
disseminate our findings and design of wide implementation if proven effective (support letters attached).  
B. INNOVATION 
The innovations are: 1) a rigorous and well-powered experiment to test the effectiveness of SMAs in HF 
is much needed to fill the knowledge gap on HF-SMA and its effects on outcomes meaningful to the patient, 
the provider and the VHA (aims 1-4). Given the 2-site design (East and West regions), we will be able to 
perform an assessment of heterogeneity of treatment effects, if any, and select out system factors 
(hospital/provider) if any, and patient subgroups that favored SMA intervention, even when the overall trial 
shows a non-significant result. 2) Our mixed method approach and the planned pre-implementation 
assessment will help understand potential mechanisms of benefit, if any, thereby, streamline and refine the 
intervention in the next iteration, in preparation for broader implementation. 3) Given the poor health status of 
patients with HF, traditional treatment settings required intensive physician involvement to show clinical 
efficacy, especially after hospitalization.68 Therefore, our study will address whether the addition of non-
physician health professionals, via SMA approach, may improve patient outcomes. 4) If proven effective, our 
intervention will add another care delivery model to treat HF and possibly other complex chronic diseases alike 
that have frequent exacerbations. The importance of developing a new and robust intervention to 
improve patient outcomes in HF cannot be overemphasized, especially given recent literature that 
showed not all interventions in HF work as planned. Examples of such ineffective interventions are regular 
follow-up calls after discharge45 or close follow-up by primary care,46 which did not improve patient outcomes 
despite better patient satisfaction. Because experimental interventions can have a neutral or even negative 
effect on outcomes, we have chosen a neutral comparator (usual care) rather than an active comparator. 
Thus, this randomized-controlled trial to test the effectiveness of HF-SMA in improving patient 
outcomes after hospital discharge is timely and critically needed to create an innovative approach to HF 
management, and support patients with symptomatic HF. Currently, patients with HF may have limited options 
in traditional care models which strain system resources and fail to comprehensively address patient needs.  
C. PRELIMINARY WORK ON SMA  
1. Group Visits for Diabetes: Multidisciplinary Education and Intervention for Cardiac Risk 
Reduction (intervention duration 4 weeks, PI: Wu):  We have shown in a general population with diabetes 
and HbA1c >7% that the addition of multi-disciplinary educational-behavioral interventions and medication 
titration in a group visit setting to primary care are feasible and effective after 4 weekly sessions vs. usual 
primary care. HbA1cs improved from 8.1±1.6 to 7.3±1.1 (Cases) vs. 7.8±1.1 to 7.7±1.2 (controls); P<0.05).10  
2. Multi-targeted intervention in diabetes group visits (intervention duration 6 months, PI: Wu): 
We extended our weekly group visit intervention of 4 weeks to be followed by 5 monthly booster sessions to 
treat diabetes patients with multiple cardiac risk factors. After 6 months, more diabetes self-care behaviors 
improved in the SMA arm and the mean 10-year cardiac risk estimated by UKPDS calculator decreased 
significantly for SMA arm (28.4% to 20.3% p<0.01), but not usual care (27.0% to 23.4%, P=1.0).11  
3. Pharmacist-led Group Visits in Depression (intervention duration 6 months, PIs: Taveira, Wu): 
SMAs for uncontrolled diabetes and co-morbid depression. After 6 months, 10-year UKPDS risk scores 

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decreased significantly for SMA arm (20.6 to 15.7%, p<0.01), whereas there was no significant change in 
usual care (22.7 to 20.4, p=.21). There was also trend towards improvement in depression symptoms.9  
4. Group Intervention for DM Guideline Implementation” (intervention duration 1 year, PI: Wu):  
Multi-center trial (VA Providence, VA West Haven, VA Honolulu) comparing pharmacist-led SMAs vs. usual 
care to lower cardiovascular risk in patients with type 2 diabetes. After 13 months, both groups had significant 
improvement in blood pressure and lipids, but only participants in the group visits have significant reductions in 
hemoglobin A1c (0.31±1.31, p=0.02). Compared to 13 months prior, VA healthcare costs in the 13 months 
after the study decreased by 9.8% for the SMA arm but increased by 47.4% for usual care (p<0.001).69  
5. HF-SMA at Providence VA Hospital: The Providence VA instituted multi-disciplinary HF-SMA in 
2011. Patients are referred from inpatient and outpatient setting by their physicians. Dr. Wu oversees the HF-
SMA in case of difficult patient scenarios. In preparation for this proposal, we abstracted data on 70 patients 
referred to this program: Mean age: 75±12 years, Caucasian (93%), 99% male, NYHA class 3 or 4 at baseline 
visit (66%), mean left ventricular ejection fraction of 42%, and 50% of patients takes >10 prescribed 
medications. There was a mean of 41± 64 days delay from hospital discharge to attendance of HF SMA. For 
care coordination, referral into telehealth occurred in 22% and for home care was 4%.  Medication changes 
and dose titration occurred in 62% of patients. Preliminary results showed a 30-day readmission rate of 6% 
and a 180-day readmission rate of 25% for all patients enrolled in HF SMA. In contrast, data from the VA 
Inpatient Evaluation Center showed a HF readmission rate for Providence VA at 22% for 201350 and pilot data 
from a national sample of discharged HF patients ejection fraction <40% showed a 180-day readmission rate 
of 40%,70 suggesting a possible reduction in rehospitalization rate by HF-SMAs.  
Interview of patients showed that most patients would agree that HF-SMAs are helpful: “I find it 
informational..different people have different ideas..last time I came in, one of the gentlemen that was having 
trouble with his ankles..socks a little too tight..then somebody says, then cut the top of the socks off…”  
Medication reconciliation and adherence as well as diet counseling are two most frequently mentioned themes: 
“Especially the medications, which I found out the hard way...’cause I had stopped it…it got confusing to me, 
all the medications…”; “ learn a lot about diet such as fat, salt and ice cream intake,… Send a cook-I don’t 
know how to cook!” We also learned that sometimes we give too much information to patients: “…too much 
actually...I haven’t read a book in like forty years…” We also found out that at times we did not explain clearly 
why the patients are attending the HF SMAs: “I don’t remember it at all, so, that’s why they ought to let people 
know what they’re doing, exactly what they’re there for, because I really wasn’t sure why I was there..” We also 
learned that patients within 1-2 weeks of hospital discharge are often too frail to want to attend SMAs and not 
eager to interact, so they often delay their appointment until 3-4 weeks out. These lessons helped us designed 
the current study to open the window of enrollment up to  12 weeks after their discharge.  
Interview of physician stakeholders suggested that many physicians did not know about HF-SMAs or 
their patients attended HF-SMAs when referred by another provider. These observations taught us that 
communication with patient’s physicians is important after the HF-SMAs for care coordination.  
6. HF-SMA at Phoenix VA Hospital: The Phoenix VA instituted weekly HF-SMA in 2013 with capacity 
to see 4-6 patients in each session. Dr. Dev oversees the HF-SMA in case of difficult patient scenarios. Data 
on 54 patients referred to this program showed a patient population with a median age of 66 years, 82% White, 
100% male, with a mean left ventricular ejection fraction of 35%, and the median number of medications = 10.  
Preliminary results after SMA showed a 90-day readmission rate of 7% and mortality of 4%, which is in 
contrast to the 25% 30-day readmission rate for Phoenix patients with a recent HF discharge (FY2014).  
Focus groups conducted with patients after HF SMA suggested that the patients liked the open forum 
format and they believed SMA helped because it addressed a broad spectrum of concerns, provided additional 
medical information and strategies for coping with illness, had more time to talk with healthcare team, explored 
questions more deeply/reflect on answers, the conversation-like setting and support group’ environment (“Not 
alone”) and the learning from other patients’ questions/ experiences as well as opportunity to share own 
experiences. Among the concerns expressed, one patient expressed that others were judging him and 
inhibited his openness going forward and another patient expressed: “Group providers and patients don’t know 
me as well and not a safe environment to voice personal issues as they can be misconstrued”; “your personal 
doctor isn’t there”. These are important lessons learned to control group dynamics and avoid stigmatization, 
earn the trust and have guidelines for participation to protect privacy. Some patients needed clarification on 
whether SMA is meant to replace visits to doctors (possible misunderstanding among new SMA patients about 

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the role their SMA provider plays). In our current model, the patients are advised that all treatment plans are 
communicated back to their primary providers via CPRS (provider decision support). 
Overall, the above data support the feasibility of SMAs in HF, experience of the team in RCTs and 
multi-site studies.  However, the effectiveness of HF-SMA in improving patient outcomes is still unknown 
despite strong theoretical underpinnings, and further investigation is warranted. 
C. STUDY DESIGN OR APPROACH  
1. Overview This will be an open-label multi-center randomized-controlled trial of parallel design, to study the 
effectiveness of HF SMA in improving the health status (Aim 1), hospitalization or mortality (Aim 2) of patients 
discharged from a HF hospitalization. In addition, we will study intermediate outcomes such as process 
measures of HF-self-care and a biological measure of clinical status (BNP levels) (Aim 3). Finally, we will 
conduct fidelity assessments and a pre-implementation evaluation through interviews with patients (and 
caregivers if available and willing) to determine satisfaction and possibilities of refinement of the HF SMA, and 
physician stakeholders to assess for potential barriers of implementation.71 We will enroll patients within  12 
weeks of discharge from a HF admission  and/or IV diuretic therapy, who will be randomized to receive either 
HF-SMA versus usual care. The conduct of the clinical trial will follow the suggested best practices in the 
conduct of randomized trials as published in the British Medical Journal.72 The study duration will be 180 days 
from the time of randomization.  Both quantitative and qualitative methods will be utilized to assess the 
outcomes of this intervention. The HF-SMA will consist of four sessions of 2-hour duration that occur every 
other week for 8 weeks or based on the clinics’ appointment availability.   
2. Population  
Inclusion criteria: 1) All subjects >18 years old, 2) within  12 weeks of discharge from a hospitalization 
with a principal diagnosis of HF (ICD-9 codes in Appendix Table) and/or IV diuretic therapy, 3) able to 
participate in a group setting and 4) able to sign informed consent, will be eligible for enrollment. The study 
team will work with subjects with transportation problems to help resolve travel issues if needed using VA 
channels (e.g., identifying support persons to help, Veteran vans, Community-Based Outreach Clinics with 
shuttle transport to the main hospital, etc.) since in most cases, VA provides support for transportation for 
Veterans to attend clinic.  
Exclusion criteria: We will exclude patients who are: 
1) Unable to attend the group sessions due to either psychiatric instability (acutely suicidal, psychotic) 
or organic brain injury (e.g. severe dementia, encephalopathy) that precludes self-reporting on health status.  
2) Discharged to hospice or nursing home facilities for long term care, or patients with a code status of 
comfort-measures-only since the setting and goals of disease management will be very different compared to 
the general HF patients after discharge, who are the target of our intervention.  
3) Recipients of heart transplant or ventricular assist devices, patients receiving intravenous inotropic 
infusions for heart support, women who are pregnant, and patients with end-stage liver disease or renal 
disease on dialysis since these conditions would preclude them from standard HF care. All women of 
childbearing age will have a pregnancy test before study enrollment.  
We will not exclude patients who are currently enrolled in HF education classes, support group or HF 
clinics, as these co-interventions are often present in optimal “usual care” and patients are often referred to 
SMA from these settings. In addition, it would be important to know the effectiveness of the SMA intervention, if 
any, in presence of potential co-interventions. We will account for co-interventions using stratified 
randomization, so equal proportion of patients participating in above-mentioned programs would be allocated 
to each study arm. It is possible that patients are referred in the middle of the study, for which we will track 
them carefully and accounted for them in the analysis plan.  
3. Registry of excluded patients: For patients who were approached but do not wish to participate in the study, 
we will still ask them for a written consent to follow on their medical outcomes through medical chart review 
and authorization for release of medical information for 180-days after registry enrollment.  In this way, we will 
compare the outcome of these patients against those randomized, to assess for systematic differences 
between the enrolled and the excluded population.  
4. Recruitment: Patients will be recruited from 2 sites, Providence VAMC and Phoenix VAMC (please see track 
record of the investigator team in recruitment and conduction of multi-center trials from preliminary studies 
section and bio-sketch).  First, study investigators (Drs. Wu and Dev) will present the study to primary care 
physicians, hospitalists and cardiologists during staff meetings and conferences in each of the respective 

9 
 
hospitals. We will then ask the IRB for a waiver of informed consent to screen for potential participants by chart 
review of patients with HF hospitalizations within the previous 12 weeks.   
For recruitment from the inpatient setting, we will partner with hospital’s discharge planning staff to 
obtain a list of potential or soon to be discharged patients. Once eligibility is confirmed through medical record 
review, we will contact the potential participant’s inpatient providers to ask for their permission to approach 
these patients. Once permission obtained, we will approach the patient while in the hospital with an information 
sheet and ask to contact them for the study after discharge. For recruitment in outpatient settings, once 
eligibility is confirmed, we will contact the potential participant’s personal physicians to obtain permission to 
contact the patient. Once permission and endorsement is obtained, we will send a joint recruitment letter from 
the patient’s personal provider along with the investigators that will include a return envelope with a response 
card to contact them for the study. In order to enhance participation and after permission from the IRB, we will 
send information material to discharge planning staff and place signage in each of the cardiac testing 
laboratories, rehab facilities, and cardiologist and primary care physicians’ offices. Once contacted and 
agreeable, the patient will come for an initial study visit with the research assistant and informed consent will 
take place. Our preliminary data showed that in 2013, there were ~130 patients discharged with HF at 
Providence VAMC and ~250 patients at Phoenix VAMC; of which, we plan to annually recruit 50 and 75 
patients in each site, respectively, over 36 months for a total of 375 patients.   
5. Randomization and retention: Once enrolled, patients will be randomly assigned on a 1:1 ratio to 
intervention or placebo arms using a stratified block randomization method with block sizes of 4 in each site to 
ensure balance of the stratified variables. Stratification will be based on the study site and the presence or not 
of: a) co-intervention (enrollment to HF clinic, support group or education), b) ≤2 hospitalizations in the last 6 
months, and c) left ventricular ejection fraction <40%. Randomization will be done by the call-in method to a 
central computer administered by the study coordinator at Providence VAMC, the coordinating site. To ensure 
subject safety and continuous engagement in study procedures, patients will be called by phone by study staff 
on a monthly basis following randomization to answer any questions that may arise, ask for participation in HF 
programs and doctor’s visits, ER visits, document adverse events and maintain study engagement. Patients in 
the control arm will be invited to participate in HF-SMAs at the end of the study, to honor patient’s preferences. 
 
Our preliminary data showed that our recruitment in prior SMA research has been successful, ~50-60% 
of those screened and eligible agreed to enroll in SMAs; and then about 90% of those enrolled finished the 
study.  Reasons for drop out are: geographic mobility, change in work schedule, incarceration, and 
homelessness. Yet, we have been able to maintain a good retention rate, through a combination of excellent 
relationships with participants, and a perceived value of the study to clients.  
6. HF-SMA: The HF-SMA team includes a dietician, a health psychologist, a nurse, and a nurse practitioner 
and/or a clinical pharmacist; one of which will lead the group discussions. Caregivers if available and willing, 
are allowed and encouraged to attend SMAs but NOT required, similar to how family members are allowed and 
encouraged to attend usual care clinic visits, but NOT required. Inadvertent loss of privacy is a concern in 
SMAs and we will clearly state that risk in the draft informed consent form (Appendix). At the beginning of each 
session the facilitator will provide SMA group guidelines for participation for the participants, caregivers and 
providers during the group interaction. Participants will be advised regarding appropriateness in sharing, as 
well as the expectations of privacy and confidentiality for patients and caregivers. Specifically, patients will not 
be asked to reveal any sensitive information about themselves and will be advised that the providers will not 
reveal any of the participants personal information during the group sessions. The SMA providers in both sites 
are very experienced and have been trained to respect privacy and avoid eliciting sensitive information. The 
session will start with an assessment of the patients and their needs followed by pre-assigned disease self-
management education, followed by patient-initiated disease discussion, and conclude with break-out sessions 
of individualized behavioral intervention, medication reconciliation and case management by the multi-
disciplinary team. The HF-SMA group will consist of 4-6 patients (and caregivers if present), of 2h duration 
broken down into: 
1)  Patient intake (10 min): they will complete a salt intake survey (appendix), blood pressure, heart 
rate, weight, leg /sacral edema, heart and lung sounds (nurse, pharmacist, and/or nurse practitioner).  
They will also undergo medication reconciliation (10-15 minutes each patient): Clinical pharmacist or 
nurse practitioner reviews patients’ medications against hospital discharge instructions and performs brief 
medication therapy management evaluation. In order to perform a thorough assessment of medications and 
adherence, we will ask the patient to bring all the medications in all HF-SMA visits (prescribed and non-

10 
 
prescribed). This list of medications will be corroborated with electronic medical records and local pharmacy (if 
non-VA medication) during the education sessions, so no time is spent in waiting. The same will be done if 
patients informed that a change had occurred since discharge from the hospital, so that the current list can be 
corroborated against the medication list from physician’s offices records.  
2) “Meet and Greet” and patient need assessment (5 minutes, all team members).  Patients are 
introduced to the team and to each other and are asked about self-care topics they would like to discuss.  
3)  Group Education (15-30 minutes):  theme-based discussion based on curriculum published by the 
HF Society of America73 into 4 sessions:  
a) Taking control of HF and Self-care: we will discuss the causes and types of HF, early 
detection of HF symptoms and how to monitor for signs of worsening (i.e. leg swelling, shortness of breath), 
when to call provider, daily weights, and VA resources to help them in disease monitoring such as telehealth. 
b) How to follow a low-sodium diet: discussion of low and high sodium foods, read food 
labels, eating out, cooking tips, supermarket tips/tour, cooking demo and meal planning. 
c) HF Medicines: HF medication types and how they work, adherence, pill boxes, side effects 
and when to report them, medications or foods to avoid, among other topics.  
d) Managing Feelings about HF and advanced care planning: coping with negative emotions  
such as depression symptoms, family and caregiver support, recognizing anxiety and depression, when to 
seek medical help, advance care planning discussion with their physician and when to consider turning off 
defibrillators (this topic was suggested by a caregiver) 
4) Patient-initiated guided discussion about HF self-care barriers (15-30 min) 
5) Individual break-out session (45-60 min): patients rotate with providers depending on their needs 
for Individualized Self-Management and Support (15-20 minutes each patient): needs-based problem 
solving, e.g. clinical pharmacist or nurse practitioner if medication discrepancies are found or dose up titrations 
are needed. They can also meet with the nutritionist, psychologist, and/or nurse. Our experience suggests that 
the patient meets health care professionals of an average of 2 disciplines during the break-out sessions. 
6) Documentation: chart documentation of the visit interventions will be performed by SMA team 
members. Communication of the treatment plan with the primary care provider and/or the cardiologist will be 
through electronic alerts in medical records and/or letter to non-VHA providers. Phone calls and/or encrypted 
emails will be used when clinically indicated.  
7. Usual Care in HF:  All patients will receive standard of care in HF as dictated by their cardiology physicians 
and primary care providers. It is highly encouraged that all patients see their physicians/health care providers 
within 14 days after their HF discharge. Physician follow-up after that may vary depending on the patient and 
physician, for which we will capture carefully through chart review and patient interview to compare attention 
given to patients in both arms of the study. In institutions such as Providence VAMC or Phoenix VAMC, 
patients are often referred to HF clinics (traditional one-to-one visits) with nurse practitioner for closer 
monitoring, which will be carefully tracked for analysis. This usual care arm will allow us to study the additive 
effects of HF-SMA and not in replacement of another intervention. In addition, there can be unexpected effects 
of active comparators in patient’s outcomes as stated previously with interventions that have worsened 
rehospitalization risk.45,46 Therefore, a neutral standard of comparison such as usual care would be important. 
It will also allow the measurement of variation in effect size across different sites since usual care may vary. 
8. Study Visits, Data Collection and Study Outcomes:  There will be 3 research visits: 1) baseline for 
enrollment consent and data collection, and 2) at 90 days (+ or - 30 days) and 3) at 180 days (+ or - 30 days) 
after randomization for outcome collection, in addition to monthly phone calls in between study visits. All 
surveys will be self-administered unless the patient prefers otherwise. Only experienced interviewers will 
conduct the interviews, proficiency must be demonstrated to site PI. Training for the qualitative aspects of the 
study will be provided by the Cleveland site. All patient self-reported measures and interviews will be 
performed during the three research study visits. To accommodate patients, per request, study visits may be 
conducted over the phone or in a private location of their choosing with two study members present. Also to 
further accommodate patients, per request, de-identified surveys using only a study ID number may be mailed 
out along with a postage paid, self addressed return envelope. Patients will be instructed not to include their 
name on any of the returned surveys. Research assistants must demonstrate proficiency in data collection 
techniques to the site PI’s.   
Aim 1: Primary outcome is change in KCCQ and secondary is change in EQ5D. 

11 
 
Kansas City Cardiomyopathy Questionnaire (KCCQ)15,17(Appendix): is a 23 item instrument validated in 
stable and decompensated HF patients with preserved or reduced ejection fraction.15 The questionnaire takes 
4-6 minutes to complete, and reflects disease-specific health status over the prior two weeks.  The domains of 
KCCQ are physical limitation, symptoms, self-efficacy, social limitation, and quality of life.  The domains of the 
KCCQ have a high internal consistency with a Cronbach’s alpha of 0.95 for the Overall Summary Score and 
≥0.62 for all individual scales.  The KCCQ has a significantly higher responsiveness to changes in health 
status than the Minnesota Living with Heart Failure Questionnaire and the SF-36.15 The overall summary score 
is 0-100 where higher score is better. The minimal clinically important change in survey score is 5 points, with 
a 10- and 20-point change reflecting moderate and large clinical changes, respectively.74 In the Eplerenone 
Post-AMI Heart Failure Efficacy and Survival Trial (EPHESUS), each 5-point decline in KCCQ Overall 
Summary Score on serial assessments was associated with a hazard ratio of 1.11 (95% CI, 1.05-1.17) for 
subsequent cardiovascular death or hospitalization.75  Preliminary data from Phoenix VA found a median 
Summary Score of 52.4±27.8 (n =32) in HF-SMA participants indicating fair/poor health status.  
Overall health status (EQ5D) (Appendix):  The EQ-5D is a well-known generic measure of health 
status. It has 5 questions that address five dimensions (mobility, self-care, usual activities, pain/discomfort, 
anxiety/depression) with five levels ranging from ‘no problems’ to ‘extreme problems’ each.76  Each health state 
(up to 3125) has a corresponding value reflecting references of the general population in various countries. 
Thus, the EQ5D can be summarized into an index value (utility) from 1 (full health) to 0 (dead) that can be 
used to calculate quality-adjusted-life-years in cost-utility analyses.77 The instrument takes only a few minutes 
to complete and is undemanding for self-completion. The EQ5D also contains a self-rated 20cm visual 
analogue scale (EQ VAS) ranging from ‘best health you can imagine’ to ‘worse health you can imagine.’ The 
EQ5D has moderate-strong convergent validity in relation to other measures of health-related quality of life as 
well as discriminative validity to detect clinical changes.  However, it is less responsive to HF-related clinical 
changes than KCCQ.74 HF Studies reported strong correlation with disease severity in EQ-5D scores ranging 
from mean values of 0.78 ± 0.18 in mild disease to 0.51 ± 0.21 for severe disease.78 
Aim 2: Event outcomes (hospitalization or death) will be captured immediately after randomization.  All events 
will be captured by monthly phone calls and chart reviews, as well as interview to study patients or caregivers 
during study visits. Copy of medical records for the reported hospitalizations, emergency room visits, or deaths 
will be obtained to confirm the event.  
Aim 3: change from baseline in patient’s HF Self-Care activities will be measured by HF Self-care Index and 
change in baseline BNP levels will be assessed through routine blood draw. 
HF Self-Care - The HF Self-care Index (v.6)(Appendix): is a 22-item self-administered instrument 
composed of 3 scales: self-care maintenance, management, and confidence. It addresses diet, exercise, 
medication use, when to call the health provider, keeping doctor’s appointments, weight monitoring, and 
recognition of change in health status or symptoms.  Each scale is scored separately and has a range of 0-
100. A score of ≥70 on each scale is considered adequate self-care, though benefit occurs at even lower 
levels.  A score change of half standard deviation (≈8 points) is considered a clinically relevant change.79,80 
Pilot data from Phoenix VA showed low self-care scores in HF patients (64.9±19.9) at baseline. 
Plasma BNP levels: is a hormone released mainly by the heart in response to excessive stretching of 
heart muscle cells in cases such as HF.81 It is a test that is already being collected routinely in the clinical 
setting for HF patients. A cut-off of >100 pg/mL in patients with new-onset dyspnea is suggestive of acute HF. 
It can also be used in outpatients after HF discharge to monitor for clinical deterioration and is highly predictive 
of death or rehospitalization,42,43 with a hazard ratio per unit increase of ln BNP of 1.84 (95% CI: 1.42 to 2.39). 
BNP provides clinicians with an objective and simple measure of the loading conditions of the heart.43   
Aim 4: Pre-implementation assessment. 
1) Patients: We will conduct interviews of 20-25 patients in each study site who have undergone HF-SMA 
(with their caregivers if willing). Interviews will attend to patient (and caregiver) satisfaction and feedback on 
refinements for continuous quality improvement and determine, in what ways, the HF-SMA helped or did not 
help them feel better and/or avoid hospitalizations. We will strive for a maximum variation sampling of patients 
based on sociodemographic characteristics (age, women and minorities), number of co-existing conditions, 
social support and engagement during the sessions to achieve maximal thematic heterogeneity. 
2) Stakeholders – Providers and administrators: We will interview ~10 physician stakeholders at each site,  
which will include primary care providers or cardiologists and one physician administrator (e.g. Chief of 
Cardiology, Medicine or Primary Care). We will purposefully select physicians who oversee HF patients who 

12 
 
participated in HF-SMA, and were interviewed, as part of the Aim 4 of the study. These will be informant 
interviews71 intended to provide insights on provider’s perceived benefits of HF-SMA (any added value or 
detriment), and potential barriers for referrals. We will inquire specifically what type of patients, providers would 
refer to HF-SMA and what barriers may exist for them to incorporate this intervention into their referral practice. 
3) Formative Evaluation: Will consist of fidelity assessment based on direct observation of HF-SMA. Dr. 
David C Aron and his research staff will perform fidelity assessments for Providence VAMC, and through 
video-teleconferencing unit for Phoenix VAMC, in addition to two in-person site visits for direct observation 
as guided by the Fidelity sheet in Appendix. As an accompaniment to the fidelity assessment worksheet, 
we will also jot down explanatory field notes which will flesh out and provide depth to the assessment 
score. In line with field research best practices,71 raw records will be typed up within 36 hours to 
accompany the numerical scores, and this data—along with the interview data—will provide a rich and 
multi-sourced qualitative depth to the study. Dr. David C Aron and his research staff will provide training on 
how to collect and record field notes. We will observe one HF-SMA session per site each month for 24 
months to ensure fidelity. 
Other data collection tools: 
 
Aside from demographics (age, gender, housing situation, social support, marital status, service 
connection, employment, education), we will also collect data about depression symptoms and patient’s 
perception of care coordination for subgroup analysis and risk adjustment. 
Depression symptoms – The Patient Health Questionnaire-8 (PHQ-8, appendix) is a 8-item well 
validated self-administered instrument that is a reliable measure of depression severity and depression 
symptom burden and is responsive to treatment outcomes over time.82 Scores can range from 0 to 24, with a 
higher score indicating a greater burden of depressive symptoms.83 PHQ-8 scores of 5, 10, and 20 
represented mild, moderate, and severe depression, respectively.  Internal reliability estimates range from 0.86 
to 0.89 using Cronbach’s alpha. Two day test-retest reliability is estimated to be 0.84 with nearly identical 
mean total scores. The advantages of the PHQ-8 include the following: 1) It is self-administered; 2) It contains 
only 8 questions that help identify patients with clinically meaningful symptoms of depression; 3) Can be 
reasonably administered in 5-10 minutes; and 4) Can be scored in 1-2 minutes. For safety guards in place 
regarding suicidal ideation, please refer to Human Subjects section.82,83 
Perceived patient-centeredness and coordinated care (PACIC survey) (Appendix):84 The PACIC is a 
well-validated 20-item questionnaire that has 5 subscales: Patient Activation, Delivery System Design/Decision 
Support, Goal Setting, Problem-solving/Contextual Counseling, Care Coordination; with the various scales, as 
well as the overall score, to be both internally consistent and moderately stable during test-retest. This tool 
assesses the health care system from the patient’s perspective (patient centeredness). The questions are 
general enough that we can ask the patient to answer in the context of their heart disease care. 
Medical co-morbidities and cardiac history: based on the Charlson Co-morbidity index, this data will be 
collected through chart abstraction by our research assistants at baseline and confirm it with patient and 
caregiver. The Charlson Co-morbidity index is a weighted index that takes into account the number and the 
seriousness of comorbid disease.85 The index is well validated for its ability to predict risk of death from co-
morbidities at 1-year and 10-year follow-up periods. We will also obtain cardiac testing data including 
echocardiography, cardiac catheterization, and stress test data through review of medical records. Non-VA 
sources will be contacted if indicated to track non-VA care (Table 1 of data collection below)  
Table 1. Timeline of Data Collection 
Baseline 
90 days 
180 days 
Data Source 
Charlson Comorbidity Index 
X 
 
 
Patient, family and chart 
Caregivers / Demographics 
          X 
 
 
Patient, family and chart 
Echocardiography, cardiac testings 
X 
 
 
Patient and chart 
KCCQ, EQ-5D 
X 
          X 
          X 
Patient 
HF Self-care Index, PACIC, PHQ-8, BNP 
X 
X 
X 
Patient 
          Patient (± caregiver) satisfaction  
Ongoing 
Interview 
          Provider perception 
Ongoing 
Interview 
Hospital admission or death 
Ongoing 
          Patient, family and chart 
HF clinics / programs  
Ongoing 
          Patient, family and chart 
Outpatient physician and ER visits 
Ongoing 
          Patient, family and chart 
9. Quantitative Analytic Plan:  

13 
 
Aim 1: To compare between the intervention versus usual care arms in the change from baseline in KCCQ 
(Primary outcome) and EQ5D (secondary outcome) at 90 and 180 days. The analysis will be performed from 
an intention to treat principle. First, descriptive statistics (mean, standard deviation, median, inter-quartile 
range, and frequency distribution) will be calculated to summarize, at baseline, patients’ demographic and 
comorbidities including previous hospitalizations, cardiac history (heart function and coronary disease), 
medical and health service utilization information (including medication possession ratio, HF self-care index, 
BNP levels, enrollment into HF clinics / programs, visits with primary care and cardiologists), and the primary 
outcome of interest (KCCQ, overall score) according to randomized arms. Log-transformation of variables and 
outcomes of interest will be performed to approximate normality when appropriate. Linear mixed-effects (LME) 
model86 will be utilized for the analysis of this aim, where the response variable is KCCQ, fixed effects include 
treatment group, time (0 = baseline, 1 = at 90 days, 2 = 180 days), treatment group by time interaction, and 
other important demographic variables identified in the descriptive analysis, and random effects include site-
specific random intercept, subject-specific random intercept (nested within site) and subject-specific random 
slope of time. This modeling approach has been shown to provide an unbiased and efficient estimate of the 
longitudinal treatment effect in a variety of situations, such as in the presence of missing data, imbalance of the 
primary outcome at baseline, and covariance heterogeneity between treatment groups.87,88 In this way, we 
could compare the intervention effects at 90 days and whether residual effects exist at 180 days. The random 
site effect is used to model the clustering effect of patients in the same study site and random subject effects 
are used to model the variability in the subject-specific trajectory and the correlation of repeated measures 
within subject. Residual analysis will be conducted to examine the appropriateness of the functional forms of 
each fixed effect, and Information criteria (AIC, BIC) will be used to choose the correlation structure. 
 
Secondary: Same modeling technique will be used to study EQ5D as the outcome instead of KCCQ. 
Aim 2: To compare between the intervention versus usual care arms in hospitalization or death at 90 and 180 
days after the randomization. For this analysis Cox proportional hazards model89 will be utilized where the 
event is a composite outcome that represents either hospitalization or death. Any patient who does not 
experience the event by 180 days will be denoted as censored. The main exposure is treatment group and 
other covariates include patient demographic and comorbidity information as described above. We will 
examine the differences in outcome at both 90 and 180 days. The appropriateness of the proportional hazards 
assumption will be examined and any violation of the assumption will be addressed. The appropriateness of 
the functional forms of each covariate will be assessed through residual analysis.  
Aim 3: To compare between the intervention versus usual care arms in the change from baseline in patient’s 
(a) HF Self Care index and (b) BNP levels, we will use the same linear mixed-effects modeling approach as 
described in Aim 1.  
Subgroup and Sensitivity Analyses: In order to understand potential heterogeneity of treatment effects, 
stratified analyses will be conducted by our randomization stratifiers such as co-interventions or not, ejection 
fraction (≥40% & <40%),  and hospitalizations in the previous 6 months (>2 & <2). Given that baseline KCCQ 
scores,15 HF self-care behavior,90,91 comorbidity burden,85,92 depression symptoms93 and caregiver support94,95 
could potentially change the outcome of HF, we will conduct test for multiplicative interaction between the 
condition of interest  (e.g. depression with PHQ-8≥10 vs.<10) and the study arm allocation (intervention vs. 
usual care arm) on the patient outcomes of interest described in Aims 1and 2. If any these interaction terms 
are significant at an alpha level of 0.05 or less, subgroup analyses will be conducted (e.g. number of 
comorbidities below and above the median, baseline KCCQ scores above and below the median, and by 
presence or absence of significant depression symptoms or caregiver support) depending on the feasibility by 
sample size. Sensitivity analyses will be performed by study site to determine the impact of setting in our study 
findings and potential variation of findings.  
Mediating Factor Analyses: In order to understand the mechanisms by which HF-SMA improves health status 
and hospitalization or death, we will explore potential mechanisms from the process measures such as HF-
self-care index and perceived care coordination (PACIC survey).  In order to prove mediation, four conditions 
must be met: (1) correlation between the change in treatment variable (HF-SMA or not) with the change in 
mediator (change in process measure, e.g. HF self-care index); (2) variation in the mediator must be correlated 
with variation in the outcomes (e.g. KCCQ); (3) controlling for the mediator substantially reduces or eliminates 
the relationship between the treatment and outcomes; and (4) the treatment variable must temporally precede 
the mediator, which is inherent in our study because enrolled patients will be treatment naive.96 We will 

14 
 
compare multivariate regression model specifications that serially exclude and include the potential mediators 
and the treatment variable.  
Exploratory Analysis on Study Generalizability and External Validity: We will compare the baseline 
characteristics and study outcomes of enrolled patients with those in the Registry of Excluded patients to 
assess for potential differences in characteristics and outcomes. If there are significant differences in baseline 
characteristics, an “as treated” analysis will be performed to compare on the study outcomes while adjusting 
for differences in baseline characteristics between excluded patients and patients who received HF-SMA using 
the same approaches we described for Aims 1 and 2. Although we understand that the excluded patients may 
be fundamentally distinct from the study population, these analyses will help to make inferences on the 
potential effects of the intervention on untreated patients and explore the generalizability of our findings. 
Missing Data Issues: Since these are primary data collected as part of a clinical trial, we do not anticipate 
significant missing data. We will also record and report all reasons for dropout and missing data, and account 
for all patients in our reports as well as study publications. Overall, if the number of observations with missing 
values is small (<5%), we will conduct analyses by removing the variables with missing values. If the number 
of observations with missing values is many, we will compare characteristics between dropouts and those who 
had completed all the study visits. If it is determined that missing data is random, we will resort to methods that 
impute values, SAS Proc MI and MIANALYZE readily impute maximum likelihood estimates from incomplete 
data.97,98 If significant differences are found in the attrition rates across study arms, both ‘intention to treat’ and 
‘as treated’ analyses will be performed to determine the extent to which the missing data may be biasing the 
results. For the ‘intention to treat’ analysis, we will generate actual random raw data values suitable for filling in 
gaps in an existing database. Typically, five to ten databases are created in this fashion. We will then analyze 
these data matrices using an appropriate statistical method, treating these databases as if they were based on 
complete case data. The results for these analyses are then combined into a single summary finding.  
Sample Size and Power Considerations: The overall study sample will be 375 (225 patients from 
Phoenix VAMC and 150 patients from Providence VAMC). Statistical power for the aims 1 and 2 is estimated 
given these are the most relevant and the most restrictive in terms of power estimations. Under a conservative 
dropout rate of 15% for 180 days of follow-up for the main outcomes (Aims 1 and 2), we estimate the power 
with an effective sample size of 316 (15% less than the total sample) and a 2-sided significance level of 0.05 
using nQUERY Advisor 7.0®. For aim 1, we assess the power to detect a clinically significant change in KCCQ 
of 5 points, assuming a baseline score of 63 (our preliminary studies), with a common standard deviation of 15 
for the study arms, using a 2-sample t-test. For aim 2, we assess the power to detect a relevant decrease in 
rehospitalization or death risk of 25-30% at 180 days using a Cox Proportional Hazards model. Based on our 
preliminary data of 20,000 Veterans with ejection fraction <40% hospitalized with HF, their rehospitalization 
rates at 6 months is ~40%.70 Assuming similar event rates for rehospitalization or death, as shown in Table 2, 
we have good power to detect the proposed outcomes at very conservative estimates of effective sample size 
(n=158 in each arm, which is 85% of the total proposed recruitment target). Repeated measures at 90 and 180 
days are also likely to add to the statistical power in Aim 1 to detect differences at the subgroup levels. 
 
 
 
 
 
 
 
 
 
 
10. Qualitative Analysis: All interviews will be audio recorded and fully transcribed. We will use qualitative data 
analysis software, NVivo (QSR International, Melbourne, Australia)99 to organize, code and retrieve qualitative 
data, summarize linkages across themes and maintain analytic notes of the coders. Transcripts and field notes 
from observations of the intervention (not video recorded for privacy reasons) to monitor fidelity will be entered 
in the database and line- by-line open and thematic coding will be conducted to identify key themes/factors. 
Qualitative data analysis will be conducted through an iterative process in which members of the research 
team engage in both data collection and analyses throughout the study. This allows for researchers to refine 
Table 2. Power / Effect Size Calculations at 180 days Intervention vs. Usual Care 
Aim 1: Difference in KCCQ 
Aim 2. Risk of Rehospitalization or death  
Difference in mean KCCQ 
Power 
Hazard Ratio 
Power 
4.5 
.76 
0.74 
0.75 
5 
.84 
0.73 
0.80 
5.5 
.90 
0.71 
0.85 
6 
.95 
0.69 
0.90 

15 
 
interview questions as needed to address the goals and foci of the study, to create accurate thematic analysis 
that are reflective of the emerging data, and to cease data collection when theoretical saturation has been 
achieved.71 It is anticipated that 20+ interviews for patients and their caregivers (it is anticipated that at least 10 
caregivers per 20 patients will participate), 10+ for providers and one physician administrator (e.g. Chiefs of 
Medicine) at each site will be sufficient to identify common themes relevant to intervention refinement, as well 
as to identify unanticipated themes and issues (i.e. to obtain saturation of the data).100 The participation of the 
patient’s caregivers is voluntary and only if permitted by the study subjects (draft consent form for the interview 
subgroup attached in appendix). Data will be examined by multiple coders for themes on the perceived 
effectiveness of SMAs. Experienced coders at the Cleveland VA site will participate in a training session on the 
specifics of this study as well as an approach to coding that will maximize the usefulness of patients’ feedback 
to program improvement. The coders will meet on a monthly basis via conference call to create a qualitative 
codebook, compare results to assure comparability of perspectives, and to discuss and resolve competing 
interpretations. On a bi-monthly basis, we will invite patients and caregiver consultants (2 from each site) from 
both sites to participate in the interpretation of the interviews. We will specifically elicit participant (“insider”) 
interpretation of the themes and transcripts from patients and caregivers by utilizing tools from Beebe’s Rapid 
Assessment Process.  This team-based approach ensures data analysis and findings are representative of 
participant perspectives and experiences by “checking back with the local participants” and seeking their level 
of agreement with emergent themes presented by the researchers. Upon consultation with participant 
informants, the study team will identify themes/factors that are evident in the 2 study sites and determine how 
these differ or not across sites, thus providing insight into how our intervention changed the patient, caregiver 
and other stakeholder’s perceptions, attitudes and satisfaction. In anticipation for this study, we already asked 
1 patient and 1 caregiver at each site to participate as consultants (see letters of support). 
11. Limitations and potential shortfalls: First, it is possible that secular trends such as an increase in the 
availability for co-interventions threaten our experimental design and cause underestimation of our treatment 
effects. We are using stratified randomization to balance current co-interventions and will track this carefully 
during the enrollment period. Adjusted analyses for imbalanced in exposure to co-interventions during follow-
up will be performed when necessary and stratified analyses by co-interventions will also be explored as 
detailed in our analysis plan. In addition, it is likely that the effects of secular trends should be randomly 
distributed in a randomized controlled study, such that co-interventions should not have a differential effect. 
Second, our study duration is only 6 months. Based on our previous data on diabetes, the effect of SMAs on 
patient’s outcomes are the highest while the patient is enrolled in the program and gradually declines after the 
stop of sessions unless booster sessions are planned. Given limitation of resources, we would like to test the 
short and mid-term effectiveness of the intervention first, prior to studying maintenance programs. Third, there 
is always a risk of not achieving the targets for patient recruitment.  Fortunately, the project team is very 
experienced, and has had excellent track records in patient recruitment and retention in previous studies of 
similar characteristics. The use of 2 study sites will provide us with additional protection to achieve recruitment 
goals. Fourth, variation in effect size: It is possible that we found that the intervention may be effective in one 
site but not another, or in certain patient subgroups but the overall effect may not be large. This problem can 
arise due to distinct standards of usual care provided to patients and different settings of care. However, 
understanding these differences through this study will be important to know which settings and patients to 
target to derive the most benefits.  
D. RESEARCH TEAM AND ENVIRONMENT 
Please refer to investigator biosketch for details in qualifications and letters of support from consultants. 
The study team led by Dr. Wu has a long history of collaboration as well as of expertise in conducting SMAs. 
Drs. Wu, Taveira and Cohen have conducted 4 RCTs in SMAs including a 3-site multicenter trial (please see 
preliminary data section). This team will partner with Dr. Dev’s team at Phoenix VAMC. Dr. Dev has been 
collaborating with Dr. Wu for 2 years and has been conducting HF SMAs for a year (preliminary data under 
Phoenix VAMC).  Both sites have a robust research infrastructure, with Providence VAMC being home for the 
HSRD Center of Innovation in Long Term Care Services and Support for Vulnerable Veterans.   The Cleveland 
site will support Dr. Wu in the training and analysis of the qualitative data. For the quantitative portion of the 
study, the statistician Lan Jiang has known and worked with Dr. Wu since Lan Jiang’s previous Brown 
University employment and has maintained their research collaborations. This team is greatly enhanced by Dr. 
Grady (Northwestern) and Dr. Kim (Loma Linda VAMC). Both Drs. Grady and Kim have a background in 
cardiovascular nursing and care organization. Dr. Grady is a well-funded researcher (NIH, AHA) with expertise 

16 
 
in patient-centered outcomes. Dr. Kim has strong experience in disease management from the private sector 
and plan to initiate HF-SMA in Loma Linda VAMC if this trial yielded positive results. In addition, we have 
engagement from 2 patient and 2 caregiver consultants from each site who will serve as consultants to help us 
interpret the qualitative data (see qualitative analysis above).  
E. DISSEMINATION AND IMPLEMENTATION PLAN 
The dissemination will be performed via direct and indirect (meetings and publications) methods.  
1) Presentation of our findings at National meetings: at the last year of the grant at National VA (if available) 
and non-VA scientific meetings: American Heart Association and/or the Heart Failure Society of America.  
2) Publication in peer-reviewed journals: The manuscripts will follow the format set forth by the “Consolidated 
standards of reporting trials (CONSORT) and the completeness of reporting of randomized controlled trials 
(RCTs) published in medical journals”. Authorship requirements in each manuscript will be followed as outlined 
by the recommendations of the International Committee of Medical Journal Editors. We will provide guidance 
and scientific support to our patient and caregiver consultants to meet the publication criteria if so they wish for 
the qualitative papers. Our trial will be registered in ClinicalTrials.gov. We anticipate the writing of articles 
during the LAST year of the grant, which will include:  
a) “Effectiveness of a multi-disciplinary HF group intervention program to improve patient centered 
outcomes” will analyze the effectiveness of the group intervention and its comparison with usual care. 
b) “Group Intervention in HF Collaborative Care: Pre-Implementation Assessment” will describe the 
qualitative results and will serve as the guide for the implementation to other VHA or non-VHA hospitals.  
c) “Mediating factor analyses of the HF SMA”, analyzes the factors that mediate the change in KCCQ 
and reduction of hospitalization or death, if any, in HF SMA intervention.  
3) Direct Dissemination: Although SMAs have been advocated by the VHA, the applicability and effectiveness 
of this intervention in HF is unknown. For effective dissemination, our results will be presented at multiple 
levels of hospital leadership for immediate implementation if found effective:  
a) Hospital Level: The results of the study will be presented to the Hospital Director, the Chief of Staff, 
Chief of Medicine, Chief of Primary Care, Clinical Pharmacy, Nutrition, and Nursing of the respective study 
sites at the last year of the study. This will be done by Drs. Wu (for Providence) and Dev (for Phoenix).  
b) National Level: Nationwide dissemination and implementation of the HF SMA will be facilitated by the 
HF-SMA manual which will be drafted in the last year of the grant and submitted to CHF QUERI for website 
upload. If proven effective, the nationwide implementation of HF SMA will be performed through design of an 
implementation trial through either the VA Cooperative Studies Program or the VA Service Directed Research 
mechanisms.  We have already engaged national stakeholders (CHF QUERI – Dr. Heidenreich, VHA National 
PACT Coordinator – Dr. Kirsh and National VA Coordinator for Cardiology – Dr. Rumsfeld) as consultants in 
the grant to help us disseminate the results. Dissemination to the private sector will be facilitated by Dr. Grady. 
If effective, they will also facilitate and support the design of a cost-effectiveness study for broad 
implementation within the VA. Through these additional funding mechanisms, study investigators will be able to 
provide training to conduct the group sessions across different sites. The study investigators will also be able 
to visit hospitals to aid on the set-up of HF-SMA on solicitation.  
Based on our previous experience with implementation of SMAs, it is possible that clinical inertia and 
lack of provider interest exist as barriers to nationwide HF-SMA implementation. In anticipation, we have 
included physicians in our stakeholder interviews to understand their opinion and perception of HF- SMAs. If 
the results of this study are positive, we will be able to overcome potential clinical inertia with the support of the 
same clinicians that helped us shape and refine the SMAs as well as organizational leaders.  
F. PROJECT MANAGEMENT PLAN  
The project will last 4 years. It will be divided in 3 parts: randomized controlled trial, data analysis, and 
dissemination of results. Although all investigators are involved in all the aspects of the study, specific 
committees are formed to take advantage of each person’s expertise. Dr. Wu is the Providence PI and the 
overall PI, ultimately responsible for the coordination and execution of the entire research program. Dr. Dev is 
the Phoenix PI and the study co-PI. Both Drs. Wu and Dev will be in charge of the study execution and ensure 
completion of the randomized trial. Lan Jiang is the study’s statistical analyst, and will ensure completion of the 
quantitative data analysis. The qualitative portion of the study is ongoing and will be overseen by the Cleveland 
site. Dr. David C Aron and his research staff from the Louis Stokes Cleveland VA Medical Center will conduct 
interviews, analyze qualitative data and conduct fidelity assessments of the Heart Failure –Shared Medical 
Appointments (HF-SMA) for both the Providence and Phoenix sites. All qualitative researchers will have 

17 
 
monthly conference calls (in addition to the study conference calls) to discuss about coding and ongoing 
analysis of the qualitative data. Dr. Tracey Taveira is an SMA expert and will oversee the conduction of HF 
SMAs in both Providence and Phoenix (through Vtel). Dr. Lisa Cohen is an expert in HF SMA and will be 
responsible to lead the HF-SMA efforts in Providence as she is currently doing. Upon completion of the trial, 
Drs. Wu and Dev will work with our study consultants, Drs. Rumsfeld, Kirsh, Grady, Kim and CHF QUERI 
leader (Heidenreich) to disseminate the results and plan the implementation efforts if proven effective. Monthly 
investigator meetings (separate from the qualitative analysis sessions), in form of conference calls (VANTs 
line) of one hour duration, will take place to discuss the progress of the entire project and future objectives to 
be achieved. Face-to-face meetings of key study staff will take place yearly, both in Providence and Phoenix 
VAMC, in an alternate fashion. At the end of the study, we will track healthcare utilization and costs of our 
participants in all sites for an economic analysis.  The Gantt chart outlines the key study tasks and activities 
(below).   
 
 
 
 
 
 
 
 
 
 
 
 
 
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STUDY TIMETABLE 
Year 1 
Year 2 
Year 3 
Year 4 
Months of Study 
Function 
0-
3 
4-
6 
7-
9 
10-
12 
13-
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manuals and results  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Local dissemination and 
presentation  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Preparation of National 
Dissemination through 
CSP or SDP 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

18 
 
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