Randomized Trial of ENABLE CHF-PC for Heart Failure Patients and Caregivers. (Comprehensive Heartcare For Patients and Caregivers)
Phase: NA
Conditions: Heart Failure
Sponsor: University of Alabama at Birmingham

Randomized Trial of ENABLE CHF-PC for Heart Failure P 
Caregivers. (Comprehensive Heartcare For Patients and 
Caregivers) 
     Study Protocol & Statistical Analysis Plan 
  NCT02505425 
June 23, 2020 
Marie Bakitas, DNSc, NP-C, FAAN, 
Principal Investigator 
  University of Alabama at Birmingham 
Birmingham, AL 35294 

SIGNIFICANCE  
A1. HF in older (>65 years) adults is an understudied public health crisis. 
Over 5 million Americans, most over age 65, carry a diagnosis of heart failure (HF);1 up to 40% of patients will die 
within 1 year of first hospitalization.2  Age3, race4 and rural environment5 are risk factors associated with the greatest 
HF morbidity and mortality.6-8 In persons over age 65;9 multiple hospitalizations often result in unrelieved physical and 
emotional suffering4,10 and immense social and economic costs.11-17 However little is known about age-dependent HF 
outcomes or treatment response because clinical exclusion criteria favor younger patients with less co-morbidity.18-20 
A2. Palliative care is highly likely to improve symptom burden, anxiety, depression, and QOL in older adults. 
Despite strong evidence for palliative treatments such as opioids for pain and dyspnea; psychotherapy, 
antidepressants, and multi-component, counseling interventions,21 few are part of routine HF care.22,23 Symptoms, 
especially dyspnea, increase with progressive HF,24-26 and may equal or exceed those reported by cancer 
patients.12,16,27-29 Dyspnea was identified as the source of ‘unbearable suffering’ in 52% of Dutch HF patients 
requesting assisted suicide.30 Pain,13,31 anxiety,32-34 and depression11,33,35 are also under-recognized and under-treated 
in HF leading to adverse effects on QOL, reduced adherence to medical regimens, and lower survival. In one large 
study,31 50% of veterans with HF reported moderate to severe pain (≥4/10); pain was more frequently reported than 
dyspnea. There is growing evidence that providing palliative care early and concurrent with routine HF care, especially 
in older adults, can improve HF symptoms and QOL,22,27,36,37 relieve physical and emotional suffering,11-17 and possibly 
reduce hospitalizations.10 However there are currently few care models that consistently provide this care.  
A3. ENABLE CHF-PC provides 2013 ACCF/AHA Guideline38-recommended HF palliative care  
Proponents of concurrent palliative HF care;15,22,28,39-44 and the 2013 ACCF/AHA guidelines specifically identify that 
palliative care for HF should include attention to “…symptom assessment, psychosocial distress, HRQOL, 
preferences about end-of-life care, caregiver support, and assurance of access to evidence-based disease-modifying 
interventions” (p.e207). The myriad challenges to providing this care are: 1) the episodic, unpredictable HF illness 
trajectory45 in patients who are not “labeled” as dying43,46 (and their professional and informal caregivers); 2) 
overcoming the barriers of late referral due to prognostic uncertainty47,48 or until all HF therapies have been 
exhausted;23 and 3) a lack of systematic, prospective patient engagement in shared decision-making and advance 
care planning.48 ENABLE CHF-PC is an evidence-based model that meets or exceeds the 2013 ACCF/AHA 
guidelines for palliative HF care and overcomes these challenges.49-51  
A4. ENABLE CHF-PC, based on the CIC, normalizes early introduction of vital palliative care principles. 
In HF, adequately-powered intervention studies and meta-analyses examining Wagner’s Chronic Illness Care (CIC) 
model have demonstrated improved disease-focused HF self-management and survival outcomes; 52-58 some gains 
have equaled guideline-based drug therapy.58,59 To our knowledge, ENABLE was the first early concurrent palliative 
care intervention to successfully apply the CIC model to an advanced oncology60-62 and now an advanced HF 
population.63 ENABLE-CHF-PC is a multi-component, coaching approach comprising an in-person palliative care 
team (PCT) assessment64 and phone-based, patient and caregiver sessions (described in Approach). These 
components are complementary and reinforcing; the in-person PCT consultation provides a guideline-based65 
comprehensive assessment and builds a foundation for future consultation if needed and the phone-based coaching 
sessions provide comprehensive information in an unhurried, convenient home setting. These components are 
standardized but tailored to individual patient and caregiver needs (see Charting Your Course patient and caregiver 
guidebooks and coaching manuals in Appendix B). Similar to oncologists66 and advanced cancer patients,67 clinicians, 
patients and caregivers in our recently completed HF pilot study68 described ENABLE as non-threatening and 
empowering. ENABLE-CHF PC maintains the original CIC framework fostering patient activation and 
empowerment,62 effective communication about advanced care planning, treatment goals, prognosis, and symptom 
management.69-71 However, HF clinicians are reluctant to discuss these topics and their struggle to identify the “right 
time” often leaves HF patients and their families unaware of potentially beneficial supportive palliative care 
services.37,71 Our approach normalizes the early introduction of 2013 ACCF/AHA Guideline-recommended palliative 
care content38,32,33,37 (e.g. dyspnea management, informed decision-making, etc.) by embedding palliative nurse 
coaches within the cardiology team. Thus HF clinicians and patients can be exposed to palliative care principles early 
but still have the “assurance of access to evidence-based disease-modifying interventions”.38 
A5. ENABLE targets disparities created by rural location and low health literacy. The Deep South, and Alabama in 
particular, has the lowest prevalence of palliative care in large (50%) and second lowest in small (4%) hospitals in the 
United States.72 Among the myriad, complex issues contributing to Alabama’s “D” grade (A (best) to F (failing) 
scale),72 indicative of poor overall palliative care performance, rural location73-75 and low health literacy are two major 
factors that greatly contribute to this public health crisis.  Rural Healthy People 2010 identified HF as a leading 
healthcare priority75 for the 40% of the population who live in rural areas.76 Rural advanced HF patients are at high risk 
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for social isolation and disparities in palliative care77,5 due to long distances, low population density,78 and few local 
palliative care specialists or primary-care or hospice clinicians with palliative care expertise.73-75,5 Rural location is 
associated with less and later hospice use79 and hospitalized death.80 The challenge of rural location is often 
compounded by patients having low health literacy. Low literacy in HF patients has been estimated to be between 34-
54%.81 This is particularly concerning due to mounting evidence linking HF patients’ low health literacy with higher 
hospitalization rates82-84 and health care costs,81 poor self-care and disease management skills,84-86 worse quality of 
life, 86 and higher mortality.82,87  Recognizing this, the Heart Failure Society of America (HFSA)88 issued a consensus 
statement recommending the development of interventions that evaluate social support, patient follow-up, disease 
management, and educational tools—all of which are included in the proposed ENABLE CHF-PC intervention.  
Specifically, components of ENABLE CHF-PC have demonstrated success in combating the effects of rural 
location50,64,73 and low literacy:  self-care training,89,90 multi-session training,89,90 and phone-based support.90  
A6 There is a critical need to discover effective interventions to assist caregivers of patients with advanced HF  
The bedrock of successful HF self-care is having a family caregiver;53,91 but caregivers’ invaluable contributions to 
patients’ well-being come at a personal cost. 92,93 High levels of caregiver strain have been associated with poorer 
physical health94 and higher mortality risk.95,96 A number of interventions aimed at supporting family caregivers of 
patients with life limiting illnesses have undergone randomized testing, however the results have been marginal.21,97 A 
2011 Cochrane review and meta-analysis97 of 11 RCTs comparing interventions for family caregivers of terminally ill 
patients with usual care (n=1836) showed significant though small improvements in psychological distress 
(standardized mean difference, -0.15) and non-significant small improvements in QOL (-0.11). One possible 
explanation for these small intervention effects may relate to the late timing of these interventions relative to the 
patient’s advanced illness trajectory. Thus early intervention, such as we propose, has been suggested as a means to 
reduce or prevent the caregiver strain and distress that has been noted to peak at the diagnosis of advanced illness 
and as death approaches. 98-101 Intervention timing is equally important as content. To date HF-specific caregiver 
interventions have primarily focused on improving patients’ disease-related self-management outcomes (e.g. sodium 
self-management)102 rather than specifically targeting caregiver burden, QOL, and bereavement. One exception is the 
successful problem-solving approach103-105 that was originally applied in hospice family caregivers106,107 and which we 
adapted, tested and will use in this proposal of caregivers early in the HF disease trajectory.68 While our pilot 
demonstrated a positive impact on HF patients’ caregiver mood, burden and QOL outcomes in the setting of  
introducing palliative care content much earlier than has been previously offered, caregivers continued to report that 
this content would have been appreciated even earlier in the diagnosis (see Preliminary Work). 
A7 There is surprisingly little data-based theory on the operative mechanisms of palliative care. The AHA Statement 
on “Promoting Self-Care in Persons with Heart Failure” identified the 
importance of determining the operative mechanisms of effective tele-
health and self-management strategies.108-110 While ENABLE 
improved QOL, mood, and in some cases survival,63 the operative 
mechanisms of these effects had not yet been fully explored.  Our 
proposal directly addresses this issue. As depicted in Figure 1a, we 
hypothesize, based on the CIC model111,112 that the intervention may 
have relatively immediate effects on patients’ behaviors (activation, 
goal setting, problem solving, follow-up /coordination, and decision 
support) and adoption of these behaviors may operate as proximal 
mediators and have more distal effects on patients’ sense of social 
support and coping. Ultimately, these proximal and distal intervention 
effects are hypothesized to serve as the mechanisms whereby the 
intervention improves patients’ QOL and reduces depression, anxiety, 
and perceived symptom burden.  Evidence for these mechanisms 
has been found in studies of patients in rural primary care,113 HF55 
and others.114,115 Resultant improved communication and advance 
care planning has also been associated with improved QOL, lower 
use of aggressive treatments at EOL, and increased hospice length of 
stay.116-122 Increased social support123-125 and coping style126-128 have 
been associated with improved cardiac patients’ well-being. To our knowledge no studies have prospectively 
addressed caregiver intervention mechanisms. Figure 1b illustrates hypothesized caregiver, patient, and 
reciprocal interactions.129 Examining these relationships may potentially identify mutable factors for future 
caregiver intervention targets. 130,131
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A8 This proposal addresses the knowledge gap related to longitudinal analysis of palliative care data. 
Miaskowski132,133 and others at the NINR-sponsored summit, “Science of Compassion: Future Directions in End-of-Life 
and Palliative Care” made a plea for the use of increasingly sophisticated statistical analysis methods for longitudinal 
palliative care patient data. Our group has implemented innovative analysis methods in our previous work63 and we 
will continue to develop these methods in the HF population (See Tosteson and Li consultant LOS/biosketches). 
B INNOVATION 
B1 Few concurrent palliative care interventions, using a pragmatic design, have been tested in underserved Deep 
South HF populations. Our investigative team (including consultant Dr. Christine Ritchie134-138-see LOS/biosketch) is 
unique as one of the few in the country with the necessary depth, scope, leadership, and experience to conduct a high 
impact pragmatic RCT of early integration of palliative care in underserved advanced-illness patients.68,73,139-141 As 
described in our Preliminary Work, we have a long history of conducting successful multi-site palliative care trials that 
reach rural, underserved patients. Whether or not our trial demonstrates positive outcomes, adopting a more 
pragmatic design by embedding palliative nurse coaches within the clinical cardiology departments and identifying 
data collection opportunities within the electronic health record will provide important insights about resource use, 
sustainability and future model dissemination / implementation.142,143
 
B2 Explicating palliative care mechanisms, especially in HF caregivers, is novel and necessary in developing effective 
palliative care models. The exact mechanisms whereby ENABLE improved QOL, depression, and survival50,63,64 
remains to be explored. Based on recent data,38,87,144 we have included health literacy, in addition to social support, 
and coping as theorized mutable intervention “active ingredients”. ENABLE specifically targets these factors which 
may in turn mediate patient and caregiver outcomes (including the often unmeasured caregiver-reported health).  
Understanding these mechanisms is essential to creating maximally efficient, effective palliative care models.  
B3 Developing innovative statistical approaches for longitudinal data analysis of palliative care outcomes 
A systematic review of 22 palliative care RCTs145 identified significant methodological shortcomings in longitudinal 
data analysis. Analyses of the dependence between quality and quantity of life are typically neglected in palliative care 
clinical trials but as we have proposed146 must be interpreted jointly to most accurately evaluate the primary scientific 
hypotheses. Specific properties of the joint distribution of the patient-reported QOL and survival data are: QOL 
conditional on survival, QOL in the months before death, overall survival and combined measures of survival and QOL 
such as quality-adjusted life years (when utilities are measured). Further, we propose to continue developing this 
innovative statistical methodology using “terminal decline” models146,147 that incorporate the unique HF pattern of 
decline which may ultimately suggest causal pathways thus improving our understanding of intervention effect.  
B4 Summary of Significance and Innovation  
This innovative RCT addresses the urgent need to integrate palliative care into the routine care of underserved, older 
adults with HF in the following ways: First, ENABLE: CHF-PC will be the first pragmatic RCT to study an extensively 
tested, evidence-based, tele-health palliative care coaching intervention, tailored to older underserved adults, that 
introduces novel problem-solving, decision support techniques/patient decision aids, and life review early in the 
advanced HF trajectory as recommended by the 2013 ACCF/AHA Guideline38. Second, ENABLE CHF-PC has a 
specific caregiver component, with a special focus on caregiver health literacy and self-reported health. Third, this 
proposal contributes to palliative care science by examining factors that may impact patient and caregiver intervention 
mechanisms (e.g. health literacy, coping, social support) and novel analytic methods that can inform future 
intervention development and testing. Finally, this multi-site study brings together an established inter-professional 
investigative team representing palliative care, HF, geriatrics, and behavioral psychology within an enthusiastic, 
outstanding research intensive infrastructure to address the special needs of underserved older adults with HF and 
their family caregivers. Therefore, as we have already demonstrated in palliative and EOL, multi-site, VA, rural, 
community-based and cancer studies this proposal can have a high impact by shifting the paradigm of HF care. 
C APPROACH 
PRELIMINARY WORK relevant to the proposed RCT.  
C1.1 ENABLE Trials in cancer. We have systematically developed the evidenced-based ENABLE palliative 
care intervention through two large clinical trials49-51,63 and a recently completed, multi-site RCT 
(R01NR011871-01) (See figure below). The ENABLE I RWJ-funded demonstration project (1999-2001)49,51 
provided the primary feasibility data that led to the ENABLE II efficacy RCT (NCI R01 CA101704, Ahles/Hegel 
(PI); Bakitas-(co-I)) published in the Journal of the American Medical Association63, ASCO Consensus 
Statement,74 Cochrane Review,148 and is now under review for the NCI Research-tested Intervention Program 
(RTIPs). Thus, this model has become a standard of high quality cancer care.36,149 We have just completed the 
ENABLE III RCT investigating the effect of immediate vs delayed introduction of palliative care. ENABLE III 
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Patient and Caregiver Outcome Measures 
Group 
Measure
Baseline Mean 
Score (SD) 
(N=11) 
Mean Standardized Effect Size 
(d) from Baseline 
Week 12 
(N=6) 
Week 24
(N=5) 
H F  
partie nts 
HADS Total 
25.11 (4.38) 
0.54 
0.01 
     Anxiety 
12.67 (3.66) 
0.36 
-0.16
     Depression 
12.44 (1.67) 
0.66 
0.41 
KCCQ Summary Score 
51.94 (18.95) 
0.31 
0.06 
MSAS Summary Score 
2.04 (0.46) 
-0.22 
0.33 
 
PACIC Summary Score 
3.49 (0.53)
0.47 
-0.08
F am ily caregivers 
HADS Total 
24.89 (7.2) 
0.05 
0.12 
     Anxiety 
10.67 (3.68) 
-0.06 
0.23 
     Depression 
14.22 (3.81) 
0.14 
-0.06
MBCB Total 
45.78 (6.3) 
0.25 
0.28 
     Objective Burden 
17.67 (5.27) 
0.04 
0.41 
     Subjective Burden 
15.89 (2.58) 
0.01 
-0.96
     Demand Burden 
12.22 (1.52) 
0.64 
0.96 
QOLC Total 
82.06 (22.2) 
-0.06 
0.33 
Preliminary Results: 
demonstrated a statistically 
significant survival advantage at 
1 year for immediate entry 
patients (Figure). Compared to 
delayed entry patients, the 
relative risk of death (hazard 
ratio [HR] (95%  CI)) was lower 
for immediate participants at 1 
year 0.72 (95% CI, 0.57-0.89) 
(P=0.003) despite small to 
moderate intervention effects at 
12 weeks ((mean [SD]: .13 
(21.39) for QOL (P=.34), -.21 (3.63) for symptom impact (P=.09), and .04 (3.91) 
for depressed mood (P=.33).150 Importantly, as shown in the Figures, there 
were statistically significant treatment effects of immediate entry from 
randomization to 12 weeks on caregiver depression: -4.1 [1.3] for depression 
(CESD) (P=.003), -1.0 [0.4] for subjective burden (SB) (P=.02), and a trend in QOL.151 Relevance to the 
current study: Provides a rigorous foundation for the intervention and methods  36,51,63,149,152-157 to be used in 
the proposed trial.  
C1.2 ENABLE CHF- PC: Needs assessment: Prior to our original submission we conducted a needs 
assessment to investigate HF patients (ICD-9 codes 428.0 – 428.99) potential palliative care needs and 
utilization.158 Results: Between 2006-2010 of 1763 HF admissions representing 1320 unique patients 132 had 
516 palliative care consultation visits (approximately 27 unique patient consults/year). Nearly half of the 
patients were male (n=70), married (n=70) with a mean age of 75 years at the time of consultation. Most 
consultations occurred during a hospital admission and were for a symptom management crisis, goals of care 
discussion, or to assist with transition to home hospice care. Relevance to the current study: Provides 
observational data validating that palliative care is routinely introduced late in the HF trajectory.    
C1.3 ENABLE CHF-PC Formative Evaluation Pilot.   
We completed a 2-phase formative evaluation pilot study159 in 
which we revised and tested ENABLE CHF-PC, study 
procedures and instruments in advanced HF patients and a 
family caregiver. In Phase I we tailored the study materials for a 
HF population based on expert consultation and literature 
review, and clinician feedback (N=11). In Phase II we evaluated 
the intervention, study procedures and instruments in two 
consecutive waves of 5 patient/caregiver dyads. Results: 
Phase I clinician interviews revealed the many challenges of 
providing PC to patients with HF such as knowing the right time 
and approach to address palliative care issues such as advance 
care planning given the unpredictable trajectory of their illness, the limited palliative services in rural areas, and 
the stigma of the “palliative care” label. Phase II: HF patients and caregivers expressed having a positive 
experience with the phone-based intervention but wished it had been available earlier in the illness trajectory. 
Small to moderate intervention effect sizes were noted (see Table). Relevance to the current study: Provides 
essential evidence demonstrating feasibility and acceptability of the intervention, recruitment/retention 
strategies, and study procedures. Identifies signals for small-moderate improvements in relevant outcomes.  
C1.4 The Alabama HF Project (Ahmed): C1.4 The Alabama HF Project (Ahmed): As a part of his NHLBI-
funded R01, Dr. Ahmed analyzed data from the Alabama HF Project that is based on 8049 Medicare 
beneficiaries discharged alive with a primary discharge HF diagnosis in 1998-2001 from 106 Alabama 
hospitals.177 We conducted a post hoc analysis of these data to examine the role of palliative care on hospital 
readmissions for hospitalized HF patients. We compared HF patients who received a discharge hospice 
referral with a propensity-matched cohort of HF patients who would have been hospice-eligible (that is, those 
who died within six months post-discharge). We noted hospice referral was associated with 88% lower risk of 
30-day all-cause readmissions when compared with hospice-eligible patients who died within 6 months post-
discharge and did not receive a hospice referral. In that study, about a quarter of the patients died within 6
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months of hospital discharge and yet only 8% of those patients (2% of all patients) received hospice referral.178 
Relevance to the current study: Provides evidence of potential for palliative care services to reduce 30-day 
readmissions; created an opportunity for the PI to establish new collaborations with UAB/BVAMC investigators. 
C1.5 Social Support, PAtients’ Needs, and Hospital Use for Heart Failure (SSPAN-HF) (AHA) and the 
DCH Social Support Study (NIA R03AG031995) (Durant) Based on prior work, 160-165 two on-going survey 
studies are examining the relationships among social support, HF self-care, and hospital use among racially- 
diverse HF patients at UAB Hospital and a rural referral center. In both projects, Dr. Durant cumulatively 
enrolled 586 African American (AA) and white HF patients. Of that total cohort, 210 AAs were recruited from 
UAB and 128 AA from the rural referral site over a 12-month period. UAB Hospital data from June 2012 to 
June 2013 reveals that 1009 unique AAs (most over age 65), were admitted for HF at least once during this 
12-month period.  To explore the quantitative survey findings about HF knowledge, self-efficacy and self-care,
40 semi-structured qualitative interviews with a subset of AA men with HF, we noted the variation and
inadequacy of HF information provided by health care professionals (“nobody ever explained”), difficulties
distinguishing HF symptoms from those likely caused by co-morbidities (e.g. “chest pain”, “heart fluttering”) and
insufficient self-care measures in response to symptoms (e.g. “relax”, “take a nitroglycerin”,”call 911”).
Relevance to the current study: Demonstrates availability and ability to recruit adequate numbers of minority
HF patients from the proposed sites and provides a HF cohort of 700 patients, mostly AAs, who have agreed to
be contacted for future HF studies and will be available to be contacted for the proposed study.
C1.6 Multisite BVAMC palliative care intervention studies Drs. Bailey and Burgio have conducted a series 
of VA-funded palliative care research studies for the last 10 years. BEACON (Best Practices for End-of-Life 
Care for our Nation’s Veterans), was a 7-site intervention trial to evaluate a multi-component education-based 
intervention to improve inpatient EOL care processes.166 Hundreds of hospital providers were trained to identify 
actively dying patients and to implement best practices from home-based hospice care, supported by an 
electronic order set and paper-based educational tools. Based on chart abstraction of 6,067 deceased 
veterans (20% with HF), the intervention resulted in significant improvements in several processes of care.140 
The next phase of this research (including Drs. Bakitas/Kvale-co-Is; proposal under review, HSRD) is a 
national, 48-VAMC site implementation project. The team has also pursued several studies of a hospice 
emergency kit (HEK) developed by Dr. Bailey and implemented as a BVAMC standard of care for veterans 
being discharged to home hospice. The most recent published study was a prospective cohort of 45 
patient/caregiver dyads (12% with HF) in home hospice (enrolled in less than 9 months)166provided promising 
evidence that HEKs are a feasible, well-tolerated method for achieving timely relief of emergent symptoms and 
possibly avoiding unwanted ED visits and hospitalizations. Finally, the BVAMC participated in a multi-site RCT 
of discontinuation of statins in home hospice patients conducted by the NINR-funded Palliative Care Research 
Consortium (Kvale/Goode-site-PIs). The BVAMC was one of the top recruiters, demonstrating our ability to 
screen and enroll eligible palliative care patients for clinical trials. 
Relevance to the proposed study: Demonstrates successful collaboration 
among the proposed study investigators and expertise in conducting multi-
site palliative care intervention studies within and outside the VA system. 
Summary of Preliminary Work: ENABLE, one of the first community-
based concurrent palliative care models to demonstrate effectiveness in 
reducing the burden of serious illness for patients and caregivers, has 
undergone more than a decade of systematic intervention development and 
effectiveness research in cancer and formative evaluation in advanced HF. 
The UAB/BVAMC teams have conducted important HF/palliative care 
studies using population-based methods, demonstrated the ability to recruit 
and deliver interventions to minority HF populations, and to conduct multi-
site palliative care research. We are poised to undertake a full scale 
pragmatic RCT in underserved HF patients and caregivers. 
C2 STUDY DESIGN   
The figure illustrates the study schema for this prospective pragmatic RCT 
of ENABLE CHF-PC, a theoretically-based early palliative care model that is 
integrated with advanced HF care compared to usual care. Our goal is to 
determine intervention effects on patient QOL, symptom burden, anxiety, 
depression and resource use (primary) outcomes and caregiver QOL, 
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burden, anxiety/depression, and self-reported health. Based on our prior work51,63 the CIC model111,112, and 
recently completed formative evaluation pilot study68 ENABLE CHF-PC comprises: 1) an in-person Palliative 
Care Team (PCT) assessment and 2) an Advanced Practice Palliative Care Nurse Coach (PNC) embedded in 
the UAB and BVAMC HF clinical teams instituting a phone-based, 6-session patient curriculum and 4-session 
caregiver curriculum; both followed by monthly follow up calls that will reinforce prior content. ENABLE CHF-
PC is not focused on terminal illness; but rather it addresses patient and family-centered care issues of living well with 
chronic, progressive illness, empowerment, problem-solving, symptom management and self-care, defining personal 
goals, and decision-making.  
C2.1 Justification of a pragmatic RCT design 
We63 and others148 have carried out rigorous early palliative care trials using an experimental approach yielding 
statistically significant results. However the true test of benefit is to determine if these care models are able to 
be applied and show benefit in real-life clinical practice.142 To our knowledge we will be among the first to use a 
pragmatic design in an early palliative care HF RCT. As we illustrate in Appendix A, the proposed trial 
maintains some elements of an explanatory trial (e.g. structured intervention, PNC specialized training, fidelity 
monitoring), as defined by the 10 domains of the PRECIS (pragmatic-explanatory continuum indicator 
summary).143 However other elements will maintain characteristics typical of real-world current U.S. HF care 
(e.g. no attempt to control HF practitioner care, participant compliance, or primary outcomes (intent to treat) 
analysis). We hope that the knowledge to be gained by this design will contribute to the current sparse data on 
palliative care integration into HF and accelerate the practical applicability of palliative care in routine practice. 
C2.2 Specific Aim 1 Patient Sample and Justification 
Patients ≥65 years will be recruited from the UAB and BVAMC cardiology, advanced HF, geriatric, and primary 
care clinics and from Dr. Durant’s (co-I)160,163existing UAB HF study cohorts. HF occurs most commonly in 
older adults and the Seattle Heart Failure model167 has demonstrated some ability to identify patients who 
might benefit from palliative care.41 These broad criteria, consistent with a pragmatic design, balance the 
competing issues of sample homogeneity and external validity/generalizability. 
Patient Inclusion Criteria: 1) English-speaking; 2) able to complete baseline interview (see Instruments-
Appendix E); 3) Age ≥65; 4) NYHF III/IV or ACC Class D HF (physician-determined); 5) Seattle Heart Failure 
Model ≥ 50% 2 year mortality (http://depts.washington.edu/shfm/)41,167  
Patient Exclusion Criteria: 1) Dementia or significant confusion (measured by ≤3 Callahan score 168   
2) DSM-IV Axis I diagnosis (e.g. schizophrenia, bipolar disorder, or active substance use disorder); 3) Patients
will not be excluded if they do not identify a caregiver.*
* We have consciously chosen to make allowances (in this and our prior intervention studies) in favor of a pragmatic approach recognizing that many
chronically-ill patients have little or no caregiver support. We recognize that caregiver support can positively influence some HF outcomes and if
imbalance.
39,110,169 .
Specific Aim 2 Caregiver Sample and Justification 
Consistent with our prior studies50,51,63 102 and a pragmatic design we will use a broad definition of “caregiver”. 
Caregiver Inclusion Criteria: 1) Identified by the patient as “a person who knows you well & is involved 
in your medical care”. May live in the same household and/or be considered to be primary caregiver willing to 
participate;”102 2) English-speaking; 3) able to complete baseline interview (see Instruments-Appendix E)  
C2.3 Total Enrollment 
We anticipate a total enrollment of 380 patient participants and 228 caregivers over 42 months (from our 
previous studies, ~60% caregivers participated). Approximately half of the patient participants (n=190) will be 
randomized to the intervention and half (n=190) will be randomized to receive usual HF care. Likewise, due to 
stratified randomization by indication of caregiver, approximately half of caregivers (n=114) will be randomly 
assigned to intervention and the other half to usual care (control) (n=114).    
Justification of Enrollment Estimates  
We have carefully examined our three sources of recruitment for volumes and racial diversity to assure that we 
can meet our enrollment of 380. This sample size will also allow us to estimate and test intervention effects 
and to conduct subgroup analyses (e.g. by race) with sufficient power to detect meaningful differences.  
UAB: Primary HF diagnosis (age ≥65) is among the top five UAB hospital discharges accounting for 943 
patients per year of which 38% are African American (AA). The UAB HF program follows over 1000 ambulatory 
HF patients. Conservatively these overlapping cohorts comprise an estimated 1400 patients per year; 
approximately 80% (n=1120) will meet eligibility criteria (stage III/IV or Class D). Assuming a steady rate of 
presentation of 93 patients per month over 42 months of recruitment =3920 total eligible UAB HF patients. 
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BVAMC: Of 300 active HF patients approximately 80% will meet eligibility criteria or 240 total HF patients over 
42 months. Existing UAB HF Cohort: Co-investigator Dr. Raegan Durant has an established cohort from prior 
studies of approximately 700 HF patients (40% AA) that are willing to be contacted for future studies.  
Hence, approximately 4920 HF patients will be eligible over 42 months from the combined sources. We have 
consistently enrolled just under 50% (in this case 2460) of eligible patients over the last 10 years of palliative 
care trials. 50,51,63 Conservatively, if only 30% of the 2460 eligible patients consent, that would provide a 
possible pool of 738 patients to achieve the enrollment target of 380. 
Attrition In prior palliative care studies we have experienced 10% attrition due to withdrawal or loss to follow up 
over 2 years.50,51,63 We will oversample if needed to achieve a final sample of 380 to evaluate primary patient 
outcomes and vital status. 
C2.3 Recruitment and retention 
Prior successful methods will be employed to maximize recruitment and retention and minimize missing data. 
UAB and VA clinicians are co-I’s and cardiology leadership is enthusiastic and supportive of this study which is 
the key to patient access and successful recruitment (See LOS). Recruitment will be facilitated by experienced 
research coordinators on-site and/or available by pager during clinic hours. The research coordinators will 
screen provider schedules to identify patients meeting eligibility criteria. Flyers and Clinician Information 
Sheets describing eligibility and study information will be posted in all exam and work rooms, and waiting 
areas. Eligible patients in the existing HF cohort will be contacted via letter or phone to determine interest. To 
enhance retention, research coordinators will be maintaining contact via data-collection, monitoring patients’ 
status through the electronic medical record, and their clinician.  
C3 Intervention Protocol and Procedures 
ENABLE CHF PC includes two major components: 
1) In-person comprehensive Palliative Care Team (PCT) Consultation- as soon as feasible after enrollment;
performed at the UAB or BVAMC Supportive Care Clinics (See Facilities and Resources).
2) A Palliative Care Nurse Coach (PNC) embedded within the advanced UAB and BVAMC HF teams,
instituting a phone-based 6-session patient curriculum and a 4-session caregiver curriculum followed by
monthly phone-based supportive care through the end of data collection (48 weeks) or patient death.
The PNC will interact with the patient and caregiver over time and across settings (home, clinic, hospital, and 
hospice) via telephone using the manualized curriculum: “Charting Your Course (CYC): An Intervention for Patients 
with Heart Failure and their Families”. (Table 2 and Appendix B). The CYC materials will be mailed prior to the first 
session. Participants will be asked to review each chapter prior to the session, but this is not required. Based on our 
prior work and recent pilot study,68 sessions last approximately 30-40 minutes.50 The PNC conducts the scheduled 
weekly sessions and then continues to follow participants monthly to check on patient/caregiver needs and to 
reinforce prior content. PCT and PNC involvement is complementary; the in-person PCT consultation provides 
expert symptom assessment and builds a foundation for future consultation if needed and the PNC sessions 
provide comprehensive information in an unhurried, convenient home setting. The primary goal of the 
intervention is to encourage patient empowerment; however occasionally the PNC may provide feedback 
directly to the HF (or PCT) teams about specific issues (e.g., unrelieved pain) or make referrals to other 
resources. The HF and PCT teams are responsible for direct medical care. If an intervention patient is 
hospitalized they will be followed by the attending service and PCT consultation will be offered. 
Table 2.  Charting Your Course (CYC) Patient (PT) and Caregiver (CG) Chapter/Session Topics by Specific Aim
Specific Aim 1 
In-person Palliative Care Team (PCT) Consultation following National Consensus Guidelines: 
Understanding of illness, tx plan, prognosis  Decision style and preferences  Goals of care  Physical symptoms  Social hx
Support system and challenges  Psycho-emotional well-being  Spirituality  Advance care planning  Pharmacological
assessment and recommendations  Referrals  Communicate with PCP  Follow-up
PT CYC Chapter/Session 1: Problem Solving and the “COPE” Attitude  
Distress Thermometer  What is problem solving coping?  COPE: A Positive Problem-Solving Attitude  ”C”-Creativity  ”O”-
Optimism ”P”-Planning  ”E”-Expert Information  The Seven Steps of Problem-Solving  Identifying the Problem  Establishing
a Goal  Brainstorming Solutions  Pros and Cons  Picking and Implementing a Solution  Reviewing how Your Plan Worked
ACTIVITY-Giving the 7 Steps a Shot
PT CYC Chapter/Session 2: Self-Care  
Distress Thermometer  What is Self-Care?  Healthy Eating and Nutrition  Exercise  Smoking  Relaxation Techniques
ACTIVITY-Identifying a Support Team  ACTIVITY-Building a Support Team  What’s the Latest?
PT CYC Chapter/Session 3: Symptom Management  
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Distress Thermometer  Prioritizing and Tracking Symptoms  Physical Symptoms of HF  ”Advanced Therapies” in HF
Emotional Effects of HF (Depression, Anxiety, Grief & Loss)  ACTIVITY-Identifying Strengths and Resources  Spirituality
PT CYC Chapter/Session 4: Core Values, Talking about what Matters Most, & Making Decisions for the Future  
Distress Thermometer  Core Values and Decision-Making  ACTIVITY-Thinking About My Own Core Values  How to Talk to
Your Family and Health Care Team about What Matters Most to You  Decision Aids  ACTIVITY-Watching the Looking Ahead
DVD  ACTIVITY-The Ottawa Personal Decision Guide  Advance Directives
PT CYC Chapter/Session 5: My Life Story  
My Life Story and Why Thinking about it is Important (even if I’m not dying)  Where I was born and early childhood  Influential
people  Important events  Cherished times  Important goals  Favorite accomplishments/proudest moments  Important
elements if there was a movie about your life
PT CYC Chapter/Session 6: Looking at Today, Looking at Tomorrow 
Distress Thermometer  What is Forgiveness  Regrets  People they want to forgive  Seeking forgiveness from others
Things left undone  Feeling at peace  Family and personal values  Hopes and fears  Sources of strength  Wisdom gained
& lessons learned  Advice for future generations  Future things to accomplish
Monthly Follow-up:  
On-going psychosocial support Reinforce/clarify previous material as it impacts real time decision making, symptom
management and QOL.
Specific Aim 2 
CG CYC Chapter/Session 1: Mirrors PT Session 1 with special attention to CG role 
CG CYC Chapter/Session 2: Mirrors PT Session 2  
CG CYC Chapter/Session 3: Mirrors PT Session 3 with special attention to surrogate decision-making role 
CG CYC Chapter/Session 4: Mirrors PT Session 4  
Monthly Follow-up: Mirrors PT.  
Bereavement Follow-up: If PT dies during study period, the PNC contacts the CG for bereavement follow-up 
Usual Care 
UAB: HF patients randomized to the usual care group will receive their outpatient care through the Advanced HF or 
Cardiology Clinics (both located at the Kirklin Clinic), or Geriatric HF Clinic (located at UAB Highlands). Primary 
care practices are located in Birmingham and patients’ local communities. Typical HF patient medical management 
is based on national HF guidelines.38 Though advanced HF patients may also receive chronic inotropes or 
mechanical circulatory support devices.  Hospitalized patients are managed by the admitting service (Cardiology or 
Hospitalist). PCT consultation is rare, but may be offered at the discretion of the clinician. In FY 2012-13, UAB PCT 
consults in HF were: 24 outpatient; 298 inpatient, and 264 PCCU admissions. While most patients receiving 
advanced therapies (ventricular assist devices [VAD] or transplant) receive a PCT consult as part of their 
evaluation; these candidates are rarely age 65 and older.  
BVAMC: HF patients are followed by primary care, general cardiology and geriatrics with care similar to that 
described above. In FY 2012-13 HF comprised 20% of outpatient and inpatient consults, Safe Harbor Palliative 
Care Unit admissions, and 39 HF home hospice admissions.  
C3.1 General Study Procedures  
Following eligibility screening, signed informed consent, baseline data collection, and randomization, the PNC will 
contact intervention patients and (enrolled caregivers) to schedule the first CYC phone session (described above). 
Patient and caregiver CYC Session 1 will occur during the week following enrollment. The remaining sessions will 
be scheduled for subsequent consecutive weeks. After completing the structured sessions, the PNC will continue 
phone contact at least monthly. If the patient dies during the study a bereavement call will be made to a (study or 
non-study) caregiver. After completing the baseline questionnaires upon enrollment, intervention and usual care 
participants will be contacted by research coordinators (who are blinded to study group) for scheduled, phone-
based data collection at 8 weeks after enrollment and every 8 weeks thereafter for 48 weeks.  
C3.2 Training and Treatment Fidelity Monitoring 
We anticipate hiring PNCs with palliative care, cardiac, and/or psychiatric nursing experience and have 
commitments from three PNCs who have been providing this intervention during our pilot. These PNCs have 
received (or additional new PNCs will receive) training provided by study staff (Bakitas/Dionne-Odom/Burgio) which 
includes 28 hours of didactic and interactive role-play guided by an established training manual/protocol including 
specific intervention skills (e.g. problem solving, decision support, health coaching). Bakitas/Dionne-Odom/Burgio 
will review digitally-recorded mock training sessions and provide feedback until PNCs are confident in their skills. 
(See Nurse Coach Training scripts-Appendix C and Fidelity checklists - Appendix D).  
Fidelity Monitoring: Treatment Integrity: PCT Consultation: Co-Is Drs. Kvale and Bailey will review PCT notes which 
are recorded in the electronic medical record using a template comprised of PCT elements based on NCP 
Guidelines.36 If elements are consistently missing, the PCT member will receive additional training.  
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PNC coaching sessions: The PI and Drs. Burgio and Dionne-Odom will review a random sample of all digitally-
recorded coaching sessions. The sessions will be scored using previously developed fidelity checklists that have been 
adapted to this study (see Fidelity Checklists-Appendix D.). The goal of the fidelity monitoring is to insure that the 
intervention is being administered reliably over time and across PNCs. PNCs who exhibit a pattern of non-adherence 
on three consecutive ratings will receive additional training and supervision. 
Participant receipt / enactment of intervention: Following the collection of outcome measures at week 48, all 
intervention participants will be interviewed by phone for the primary purpose of determining if the patient received and 
enacted the components of the intervention as described in Table 2. We will use procedures and interview guides that 
have been adapted from our previous RCTs.67 Briefly we will digitally-record, transcribe all interviews verbatim, and 
code transcripts using ATLAS.ti software to determine the extent of patient receipt and enactment of the skills taught 
by the nurse coaches. The PI is an experienced qualitative researcher,170-174 with expertise in the qualitative 
techniques that are recommended for intervention evaluation.175,176 Though not the purpose in this proposal, these 
interviews may also provide rich data for a secondary analysis of the patient and caregiver experience.   
C4 INSTRUMENTS (All instruments are contained in Appendix E.) 
The instruments were carefully chosen to measure distinct constructs within the theoretical models (Figures 1a and 
1b) with little to no overlap. The proposed instrument battery and schedule are similar to what we have used in our 
prior studies50,51,177 and in our recent HF pilot study.68 Per pilot participants’ report68 these presented minimal burden.  
Table 3.  Outcome measures
Specific Aim 1 
Construct
Instrument
Description
Reliability 
Schedule
HF Patients 
QOL 
Kansas City Cardiomyopathy 
Questionnaire (KCCQ)
178 
5 domains: physical limitations, symptoms, self-efficacy, 
social interference, and QOL; 23 items 
Subscales ߙ=.62 
to .90 
Baseline, 
week 8 and 
every 8 
weeks until 
week 48 
Mood 
Hospital Anxiety and 
Depression Scale (HADS)
179 
2 domains measuring depression and anxiety; 14 items 
Subscales α=.82 
to .83 
Symptom 
Burden 
Memorial Symptom Assessment 
Scale-HF (MSAS-HF)
25 
Targets 32 HF-relevant symptoms (e.g. chest pain, 
difficulty breathing while lying flat, etc.) 
Subscales ߙ=.73 
to .92 
Resource 
use 
Resource Use 
Inpatient days, ICU days, ED visits, hospice use, palliative 
care provider visits, AD completion, DNR orders 
NA 
Specific Aim 2 
Caregivers*
QOL 
Quality of Life – Caregiver 
(QOLC)
180 
3 domains: emotional and spiritual well-being; relationship 
with patient; & sleep, daily routine, and family life, 35 items 
ߙ = 0.91 
Baseline, 
week 8 and 
every 8 
weeks until 
week 48 
Mood  
Hospital Anxiety and 
Depression Scale (HADS) 
Same as above 
Same as above 
Caregiver 
burden 
Montgomery Borgatta Caregiver 
Burden Scale (MBCB)
181 
Measure of caregiver burden with 3 domains: objective 
burden, stress burden, and demand burden; 14 items 
Subscales ߙ = 
.75 to .88 
Self-reported 
health
PROMIS SF Global Health
10 
2 domains: physical and mental health, 10 items
Subscales ߙ= 
.81 to .86 
Exploratory Aims 
HF Patients 
Patient 
Activation 
Patient Assessment of 
Chronic Illness Care 
(PACIC)
182 
5 dimensions: activation, delivery system/decision support, 
goal setting, problem solving, and coordination; 20 items  
Subscales ߙ=.62 
to .90 
Baseline, week 8 
and every 8 weeks 
until week 48
Coping 
style 
Brief Cope 
2 subscales: active and avoidant coping; 28 items
183 
ߙ = .68 to .79 
Baseline 
only
Social 
support 
Multidimensional Scale of Perceived 
Social Support (MSPSS) 
Perceived adequacy of support from family and friends, 12 
items
184 
ߙ =.81 
All 
Health 
literacy 
Newest Vital Sign
9 
Measure of health literacy and numeracy based on 
interpretations of a nutrition label, 6 items 
ߙ = .76 
Demo-
graphics 
Demographic questionnaire 
Age, gender, race, marital status, religion, employment,
education, occupation, health insurance, smoking, etc. 
NA 
Additional measures and data 
If patients die on study we will conduct a standardized interview with a study or non-study (if agreeable) caregiver 2 
months after death using the instruments and similar techniques from prior studies129,185 to evaluate the caregivers’ 
perception of the EOL care provided and to assess their grief experience  and mood. The questionnaires are: 1) 
proxy-reported Quality of Death and Dying (QODD) (31-items) which rates the quality of the descendant’s last 7 days; 
it has acceptable internal consistency (Cronbach alphas 0.89) and construct validity; 186,187 2) Inventory of Complicated 
Grief-Short form (ICG-SF) a reliable, validated 13-item survey of complicated grief188 and the HADs (described above).  
C4.1 Data Collection, Management, and Quality Control.  
Participant recruitment/ tracking: A Microsoft Access database will be used to track the participant progress 
through recruitment, enrollment, and all study procedures. The database will consist of 3 sections: a form with 
contact information about interested participants (e.g., name, current address, cell and telephone numbers, 
and the best time to call); a section allowing for tracking contact attempts for potential participants; a dates 
form to document the number and outcomes of participant contacts (i.e., scheduled or enrolled), and all 
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subsequent contact times and types, specific mailed contacts, dates and times of pertinent communication, and 
information about the length of time between scheduled visits and dates of missed appointments.  
Data collection of outcome measures: Several instruments are available for completion within the electronic health 
record. We are exploring the ability to collect most of the study data via this mechanism. In the event this is not 
feasible we will use our trained research coordinators to collect patient- and caregiver-reported data by phone and it 
will be directly-entered into our existing REDCap (Research Electronic Data Capture) database. REDCap is 
software for building and managing questionnaires and facilitating electronic data collection and storage. It supports 
a HIPAA best practice, secure web-based application enabling multiple sites to seamlessly access, analyze and 
share data while maintaining the security and integrity of the database and provides automated export procedures 
for seamless data downloads to common statistical packages (SPSS, SAS), built-in project calendars, scheduling 
and randomization modules. Hard stops prevent missing data due to inadvertent skipping of items.  
eHR and administrative data collection: Resource use, advance directives, use of palliative, hospice, and home 
care services, disease stage, and other clinical data will be collected using established data collection forms and 
chart abstraction techniques/protocols that we have used previously.63,68,158 (See Appendix E for forms).  
Data quality control (interviewing and chart abstraction): We will hire experienced research coordinators who have 
received intensive training (typically 10 hours including role play and inter-rater reliability checks) in order to assure 
high quality data collection from participants and electronic medical records.  
Data Security: All databases are secure, HIPPA-compliant and password protected in both the front end and back 
end. Back end data will be housed on a secure drive with access limited to only authorized research personnel.  
C5 STATISTICAL CONSIDERATIONS 
C5.1 Randomization. After consent and baseline assessment, patients will be randomized using computer-
generated treatment assignments, stratified by center (UAB or BVAMC), referring service (HF clinic, 
cardiology, primary care), and race (Caucasian/non-Caucasian). 
C5.2 Statistical Analyses 
Specific Aim 1 Patient-reported QOL, mood, symptom burden, and resource use 
The intention to treat (ITT) analysis will be used for all treatment comparisons. That is, all randomized patients will 
be included in primary comparisons, regardless of whether the patient actually received the randomly-assigned 
intervention. Primary data analysis will begin with descriptive statistics for baseline patient characteristics and 
outcomes by treatment group. Distributional assumptions will be examined; when appropriate we will employ testing 
and modeling procedures that do not assume normality. We will compare groups with respect to baseline 
covariates. We will analyze and compare missing data and compliance patterns according to baseline covariates 
and we will adjust analyses for baseline factors showing either imbalances or predictive of missing data (not due to 
patient death) or compliance. Mixed modeling techniques and covariate adjustment will reduce the impact of 
missing data, provided that the data are missing at random. If necessary, multiple imputation techniques and 
sensitivity analyses will be used to deal with data not missing at random and not caused by patient death.  
We will conduct 2 sets of longitudinal ITT analyses of the primary study endpoints for participants with baseline and 
one or more follow up assessments using mixed effects modeling for repeated measures to examine the relative 
impact of ENABLE: CHF-PC in the 48 weeks after enrollment (forward in time from baseline), and its effects 
proximal to the time to death (retrospective starting from death). In the first set of analyses, we will examine 
differences between all patients in each group surviving until the scheduled 48 week follow-up surveys. Kurland et 
al.147 have described this approach as a partially conditional analysis for joint longitudinal and survival data, 
because it assumes that patients are alive at the comparison times.147 Initial ITT analyses will be conducted on 
patient-reported outcomes using mixed effects models to test the effect of the intervention, first by comparing all 
group differences simultaneously for both time periods in multiple degree of freedom global tests, and then 
individually if overall differences are significant.  
The second analysis, retrospective from death, also conducted with mixed effects models, has been described by 
Kurland et al.147 as fully conditional; because it examines patient outcomes conditional on the patients having died 
(the participants who are alive by the end of follow-up are excluded because their outcome measures proximal to 
death will be unknown). Alternative more complex analyses involving “terminal decline” models that jointly model a 
longitudinal outcome and survival will be considered as described under Exploratory Aim 2 below. All calculations 
will be performed using the latest versions of SAS and R. Standardized intervention effect sizes will be estimated 
for each outcome, and the False Discovery Rate criterion will be used to correct for multiple significance testing.  
We will conduct a decedent-only ITT analysis for the proxy-report QODD. Since only one QODD observation will be 
available for each decedent, no longitudinal modeling is required. Secondary analyses will consider any deviations 
from the intended intervention, and intervention dose effects. Subgroup analyses will be conducted with interest on 
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determining the profile characteristics (e.g. race, SES, gender, military vs. civilian background, absence of caregiver, 
etc.) of the participants who benefited the most and the least from the intervention using flexible modeling techniques, 
such as latent class analysis and recursive partitioning. 
Specific Aim 2 Caregiver QOL, mood, self-reported health, burden 
Caregiver outcomes will be analyzed using the same longitudinal methods as outlined for Specific Aim 1. For the 
analyses going forward in time from baseline, the effects of patient death on caregiver outcomes will be examined 
using models with indicators for patient death at its respective time-point. Only decedents’ caregivers will have grief 
outcomes analyzed which will not involve longitudinal modeling. Caregivers of patients who die will contribute the 
additional outcome of a rating of quality of care at the end of life (QODD). Since only one QODD observation will be 
available for each decedent, no longitudinal modeling is required. However, analysis of these measures will be 
conducted with mixed effect methods to account for nesting, with the parameter of interest being the association 
between group assignment and the caregiver-rated outcome   
Exploratory Aim 1. Explore mediators/moderators of patient/caregiver outcomes and reciprocal relationships.  
As depicted earlier in Figure 1a, intervention effect on patient QOL, mood, and symptom burden is proposed to be 
mediated by the quality of chronic illness care (PACIC), active and avoidant coping styles (COPE), social support 
(MSPSS) and health literacy (NVS). This conceptual logic will be tested using structural equation modeling (SEM) 
applied to matrices residualized for demographic and disease factors.189 Each patient model will involve 13 observed 
variables: the intervention as a dichotomous variable, five mediational variables (8 week: PACIC, active COPE, 
avoidant COPE, MSPSS, NVS) lagged against their five baseline values, and the 8 week outcome of interest lagged 
against its baseline. With 22 degrees of freedom, a sample size of 359 (expected to be alive/available at week 8), and 
a significance level of p= .05, power is .86 to distinguish a model with close fit (root mean square error of 
approximation [RMSEA] = .05) from a model with mediocre to poor fit (RMSEA = .09).190 Jointly significant effects 
involving the theorized mediators (intervention  mediator, mediator  outcome as depicted in Figure 1a) will 
constitute evidence of mediation. Assuming a medium effect size (d=0.5) on mediator and outcome, a sample size of 
359 provides.80 power to detect a small indirect effect of at least 34% of the total intervention effect size (dM=0.17) 
based on computer simulations of joint tests with a significance level of 0.05.191  
As depicted earlier in Figure 1b, the effect of the intervention on caregiver QOL, mood, and burden is proposed to be 
mediated by patient well-being. Tests of mediation of caregiver outcomes will involve jointly significant (p = .05) effects 
(intervention  8 week patient outcome  24 week caregiver outcome) for caregiver outcomes mediated by patient 
outcome. Assuming a medium effect size (d=0.5) on both mediator and outcome, a sample size of 188 (expected 
CGs with 24 week outcomes) provides .80 power to detect an indirect effect size of at least 48% of the total 
intervention effect size (dM=0.24) based on computer simulations of joint tests with a significance level of 0.05.191 As 
depicted earlier in Figure 1b, the effect of the intervention on caregiver QOL, mood, and burden is proposed to be 
mediated by patient well-being. Tests of mediation of caregiver outcomes will involve jointly significant (p = .05) effects 
(intervention  8 week patient outcome  24 week caregiver outcome) for caregiver outcomes mediated by patient 
outcome. Assuming a medium effect size (d=0.5) on both mediator and outcome, a sample size of 188 (expected 
CGs with 24 week outcomes) provides .80 power to detect an indirect effect size of at least 48% of the total 
intervention effect size (dM=0.24) based on computer simulations of joint tests with a significance level of 0.05.191 
Exploratory Aim 2. Examine intervention effects using joint modeling approaches. 
Previously cited palliative care studies have shown alterations in both QOL and survival.63,153 Although the 
interventions are not directly intended to impact survival, evaluation of this effect is important. We will compare survival 
between groups using Kaplan-Meier plots and log-rank tests. Relative risks and differences in median survival times 
will be estimated and confidence intervals will be constructed. For a second set (assessment prior to death) of 
analyses, we will implement a joint analysis of the survival time and the longitudinal data. The likelihood for this model 
is constructed by specifying the survival distribution as a piecewise exponential distribution depending on the group 
assignment, and the outcomes before death as longitudinal outcomes from mixed models depending on time 
measuring backwards from death. Kurland et al.147 describe this as the fully conditional terminal decline approach to 
joint modeling. 63,153. To accommodate the intermittent decline, flexible spline-based time trends will be introduced in 
the terminal decline model.146 With this model, we will be able to construct estimates of mean survival time in each 
intervention group weighted by longitudinal QOL measures. These estimates will allow comparison between the 
groups in terms of cumulative QOL factoring in any 
differences in survival time.  
C5.3 Sample Size Considerations Assuming a 
projected uniform patient accrual rate over 42 months 
we anticipate an initial enrollment of 380 patients and 
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228 caregivers. We assume an exponential survival distribution with a median of 2 years and independent 2-year 10% 
attrition. Under these assumptions, we estimate the minimum detectable difference (MDD) between the intervention 
and control patient means at every 8 weeks post randomization for 48 weeks as described in Table 4. We apply this 
same method to caregivers (Table 5) who will have their follow-ups truncated at patient death. We use ENABLE II 
data to provide estimates for the caregiver MBCB-OB standard deviation (sd).129 Based on the meta-analysis by Garin 
et al.192 Literature-based estimates are used for the KCCQ,193 HADS,179,194 MSAS-HF,25 and QOL-C.104 Patient and 
caregiver MDDs shown in Table 4 and 5 are based on partially-conditional (on being alive) time-averaged tests of 
mean differences comparing the treatment groups at the specified follow-up times, intra-subject correlation of 0.5, with 
a corrected two-sided .01 significance level, and a power of 0.80. Under these conservative assumptions we have 
sufficient sample size for the primary aims of this study. For subgroup analyses (e.g. Caucasian race vs. other) the 
detectable time-averaged standardized difference in intervention effect by 48 weeks post randomization is 0.53, 
assuming equally sized subgroups, and prior to other covariate adjustment.   
It is estimated that 120 patients (60 per group) will die by 48 weeks post-randomization and will be available for the 
analysis of patient outcomes nearest death. Based on the sds in Table 4, we find MDDs of 10.8 for KCCQ, 1.04 for 
MSAS-HF, 2.06 for HADS-A, and 2.01 for HADS-D. We project that the grief index (ICG) will be available for 37 
caregivers in each group. With a sd of 11.7,63 a 5% two-sided significance level and 80% power, the MDD of the ICG 
between two groups is 7.7 using a two-sample t-test.  
For secondary comparison of survival outcomes, we make the same assumptions about median survival, attrition, 
accrual, and observation time as for the longitudinal outcomes. Based on a log rank test, .05 significance level and a 
power of .80, a 1-yr reference survival fraction of 0.68, the detectable HR is 1.6. 
C6 Potential problems, alternative strategies, and benchmarks for success and future directions. 
We have anticipated potential problems and solutions related to sample recruitment and retention, usual care group 
contamination, feasibility, non-participation and respondent bias. Recruitment and retention is expected to be robust 
based on the strong collaborative relationships between the HF and palliative care clinical and research teams and the 
availability of a large existing HF cohort. Research coordinators will be present in all HF clinical areas. The PI and co-
PIs will meet regularly to track recruitment and review issues and jointly problem solve. While usual care group 
contamination is possible because HF clinicians are seeing intervention and usual care participants; early palliative 
care referral of HF patients at the UAB/BVAMC a very new concept22,39 as evidenced by the current negligible HF 
patients being seen in consultation. Our intervention is not specifically directed at changing physician behavior. Prior 
studies have shown that simply exposing physicians to new practices and providing education are not sufficient to 
change physician behavior69 so while control group contamination due to physician behavior change is possible, it is 
extremely unlikely.23 Feasibility is most directly addressed based on our prior successful completion of similar studies. 
Our team collectively has conducted numerous large, complex, multi-site RCTs in a rigorous fashion over the past 
decade. UAB/BVAMC is a research intensive environment (See Facilities/Resources) providing an exceptional 
infrastructure within which to conduct this study successfully. Non-participation bias will be monitored by collecting 
demographic data on person’s who decline and comparing that to patients who participate. We have established 
tracking and data collection mechanisms to capture this data carefully. Respondent bias in a non-blinded study is an 
important concern that we will address by providing similar information about the study purpose generally to both arms 
but not the specific outcomes we wish to influence and also by blinding data collectors to study group.  
C7 Study Timeline and Milestones  
As a result of our 10 years of experience conducting similar palliative care clinical trials our established investigators 
recruitment, retention, and data collection methods, we anticipate prompt regulatory approval (within 3 months of 
funding) and study start-up. This will ensure a 42-month recruitment period and an additional 6 months of follow up on 
patient and caregiver (bereavement) outcomes. We will present yearly progress reports to the Data Safety Monitoring 
Committee for feedback on study progress and to identify solutions to any unforeseen challenges or adverse events.  
Year 1 
Year 2 
Year 3 
Year 4 
Year 5 
Activity 
Q 1 
Q2  
Q3  
Q4 
Q 1 
Q2  
Q3  
Q4 
Q 1 
Q2  
Q3  
Q4 
Q 1 
Q2  
Q3  
Q4 
Q 1 
Q2  
Q3  
Q4 
Aim 1 & 2  
Hire, train staff, IRB 
approval 
Enrollment 
Collect Data 
Data Analysis 
(exploratory aims (1&2) 
Progress/Final Reports 
Grant submission 
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REFERENCES 
1.
Go AS, Mozaffarian D, Roger VL, et al. Heart disease and stroke statistics--2014 update: a report from
the american heart association. Circulation. Jan 2014;129(3):e28-e292.
2.
Liu L, Eisen HJ. Epidemiology of Heart Failure and Scope of the Problem. Cardiology Clinics. 2//
2014;32(1):1-8.
3.
Stein GY, Kremer A, Shochat T, et al. The diversity of heart failure in a hospitalized population: the role
of age. J Card Fail. Aug 2012;18(8):645-653.
4.
Will JC, Valderrama AL, Yoon PW. Preventable hospitalizations for congestive heart failure:
establishing a baseline to monitor trends and disparities. Preventing chronic disease. 2012;9:E85.
5.
Robinson CA, Pesut B, Bottorff JL, Mowry A, Broughton S, Fyles G. Rural Palliative Care: A
Comprehensive Review. J Palliat Med. Feb 13 2009.
6.
Bekelman DB, Hutt E, Masoudi FA, Kutner JS, Rumsfeld JS. Defining the role of palliative care in older
adults with heart failure. International journal of cardiology. Apr 10 2008;125(2):183-190.
7.
Buck HG, Riegel B. The impact of frailty on health related quality of life in heart failure. European
journal of cardiovascular nursing : journal of the Working Group on Cardiovascular Nursing of the
European Society of Cardiology. Jun 28 2010.
8.
Waterworth S, Jorgensen D. It's not just about heart failure--voices of older people in transition to
dependence and death. Health Soc Care Community. Mar 2010;18(2):199-207.
9.
Shah KB, Rahim S, Boxer RS. Heart Failure Readmissions. Current treatment options in cardiovascular
medicine. Jul 2 2013.
10.
Unroe KT, Greiner MA, Hernandez AF, et al. Resource use in the last 6 months of life among medicare
beneficiaries with heart failure, 2000-2007. Arch Intern Med. Feb 14 2011;171(3):196-203.
11.
Bekelman DB, Rumsfeld JS, Havranek EP, et al. Symptom burden, depression, and spiritual well-
being: a comparison of heart failure and advanced cancer patients. Journal of general internal
medicine. May 2009;24(5):592-598.
12.
Currow DC, Smith J, Davidson PM, Newton PJ, Agar MR, Abernethy AP. Do the trajectories of dyspnea
differ in prevalence and intensity by diagnosis at the end of life? A consecutive cohort study. J Pain
Symptom Manage. Apr 2010;39(4):680-690.
13.
Goebel JR, Doering LV, Lorenz KA, Maliski SL, Nyamathi AM, Evangelista LS. Caring for special
populations: total pain theory in advanced heart failure: applications to research and practice. Nursing
forum. Jul-Sep 2009;44(3):175-185.
14.
Goebel JR, Doering LV, Shugarman LR, et al. Heart failure: the hidden problem of pain. J Pain
Symptom Manage. Nov 2009;38(5):698-707.
15.
Goodlin SJ. Palliative care in congestive heart failure. Journal of the American College of Cardiology.
Jul 28 2009;54(5):386-396.
16.
O'Leary N, Murphy NF, O'Loughlin C, Tiernan E, McDonald K. A comparative study of the palliative
care needs of heart failure and cancer patients. Eur J Heart Fail. Apr 2009;11(4):406-412.
17.
Fang J, Mensah GA, Croft JB, Keenan NL. Heart failure-related hospitalization in the U.S., 1979 to
2004. Journal of the American College of Cardiology. Aug 5 2008;52(6):428-434.
18.
Evangelista LS, Liao S, Motie M, De Michelis N, Lombardo D. On-going palliative care enhances
perceived control and patient activation and reduces symptom distress in patients with symptomatic
heart failure: A pilot study. European journal of cardiovascular nursing : journal of the Working Group
on Cardiovascular Nursing of the European Society of Cardiology. Jan 17 2014.
19.
Evangelista LS, Liao S, Motie M, De Michelis N, Ballard-Hernandez J, Lombardo D. Does the type and
frequency of palliative care services received by patients with advanced heart failure impact symptom
burden? J Palliat Med. Jan 2014;17(1):75-79.
20.
Evangelista LS, Lombardo D, Malik S, Ballard-Hernandez J, Motie M, Liao S. Examining the effects of
an outpatient palliative care consultation on symptom burden, depression, and quality of life in patients
with symptomatic heart failure. J Card Fail. Dec 2012;18(12):894-899.
21.
Bekelman DB, Nowels CT, Allen LA, Shakar S, Kutner JS, Matlock DD. Outpatient palliative care for
chronic heart failure: a case series. J Palliat Med. Jul 2011;14(7):815-821.
22.
Yancy CW, Jessup M, Bozkurt B, et al. 2013 ACCF/AHA Guideline for the Management of
Heart Failure: A Report of the American College of Cardiology Foundation/American Heart Association
Task Force on Practice Guidelines. Journal of the American College of Cardiology. 10/15/
2013;62(16):e147-e239.
References Cited
Page 118
Contact PD/PI: Bakitas, Marie

23.
Evangelista LS, Motie M, Lombardo D, Ballard-Hernandez J, Malik S, Liao S. Does preparedness
planning improve attitudes and completion of advance directives in patients with symptomatic heart
failure? J Palliat Med. Dec 2012;15(12):1316-1320.
24.
Fitzsimons D, Strachan PH. Overcoming the challenges of conducting research with people who have
advanced heart failure and palliative care needs. European journal of cardiovascular nursing : journal of
the Working Group on Cardiovascular Nursing of the European Society of Cardiology. Feb 15 2011.
25.
Bekelman DB, Nowels CT, Retrum JH, et al. Giving voice to patients' and family caregivers' needs in
chronic heart failure: implications for palliative care programs. J Palliat Med. Dec 2011;14(12):1317-
1324.
26.
Thai V, Cujec B. Transitioning to end-of-life care for patients with advanced heart failure. J Palliat Med.
Jul 2010;13(7):796.
27.
Janssen DJ, Spruit MA, Schols JM, Wouters EF. A call for high-quality advance care planning in
outpatients with severe COPD or chronic heart failure. Chest. Sep 9 2010.
28.
Davidson PM, Macdonald PS, Newton PJ, Currow DC. End stage heart failure patients - palliative care
in general practice. Aust Fam Physician. Dec 2010;39(12):916-920.
29.
Berry JI. Hospice and heart disease: missed opportunities. J Pain Palliat Care Pharmacother. Mar
2010;24(1):23-26.
30.
Widera E, Pantilat SZ. Hospitalization as an opportunity to integrate palliative care in heart failure
management. Curr Opin Support Palliat Care. Dec 2009;3(4):247-251.
31.
Chattoo S, Atkin KM. Extending specialist palliative care to people with heart failure: semantic,
historical and practical limitations to policy guidelines. Soc Sci Med. Jul 2009;69(2):147-153.
32.
Howlett JG. Palliative care in heart failure: addressing the largest care gap. Curr Opin Cardiol. Mar
2011;26(2):144-148.
33.
Hupcey JE, Penrod J, Fogg J. Heart failure and palliative care: implications in practice. J Palliat Med.
Jun 2009;12(6):531-536.
34.
Bakitas M, Bishop MF, Caron P, Stephens L. Developing successful models of cancer palliative care
services. Semin Oncol Nurs. Nov 2010;26(4):266-284. PMID: 20971407: PMCID PMC2976669
35.
Bakitas M, Lyons K, Hegel M, et al. Effects of a palliative care intervention on clinical outcomes in
patients with advanced cancer: The Project ENABLE II Randomized Controlled Trial. JAMA.
2009;302(7):741-749. PMID: 19690306; PMCID: PMC3657724
36.
El-jawahri A, Greer JA, Temel JS. Does Palliative Care Improve Outcomes for Patients with Incurable
Illness? A Review of the Evidence. The Journal of Supportive Oncology. 2011;9(3):87-94.
37.
Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non-small-cell
lung cancer. The New England journal of medicine. Aug 19 2010;363(8):733-742.
38.
Bakitas M, Ahles TA, Skalla K, et al. Proxy perspectives regarding end-of-life care for persons with
cancer. Cancer. Apr 15 2008;112(8):1854-1861. PMID: 18306393; PMCID: 3638939
39.
Bakitas M, Lyons K, Hegel M, et al. Project ENABLE II randomized controlled trial to improve palliative
care for rural patients with advanced cancer: Baseline findings, methodological challenges, and
solutions. Palliat Support Care. 2009;7:75-86. PMID: 19619377; PMCID: PMC3685415
40.
Bakitas M, Stevens M, Ahles T, et al. Project ENABLE: A palliative care demonstration project for
advanced cancer patients in three settings. J Palliat Med. 2004;7(2):363-372.
41.
Smith TJ, Temin S, Alesi ER, et al. American Society of Clinical Oncology Provisional Clinical Opinion:
The Integration of Palliative Care into Standard Oncology Care. J Clin Oncol. Feb 6 2012.
42.
Gomes B, Calanzani N, Curiale V, McCrone P, Higginson IJ. Effectiveness and cost-effectiveness of
home palliative care services for adults with advanced illness and their caregivers. London2013. Issue
6. Art.No.:CD007760.
43.
World Health Organization. WHO Definition of Palliative Care 2010;
http://www.who.int/cancer/palliative/definition/en/. Accessed November, 2010.
44.
Dionne-Odom JN, Kono; A., Ahmed A, et al. Translating and Testing a Concurrent Palliative Care
Model for Rural-Dwelling Adults with Heart Failure and their Family Caregivers: ENABLE: CHF-PC. J
Palliat Med. 2014, in press.
45.
Weiss BD, Mays MZ, Martz W, et al. Quick assessment of literacy in primary care: the newest vital sign.
Ann Fam Med. 2005 Nov-Dec 2005;3(6):514-522.
46.
Durant RW, Brown QL, Cherrington AL, Andreae LJ, Hardy CM, Scarinci IC. Social support among
African Americans with heart failure: is there a role for community health advisors? Heart Lung. Jan-
Feb 2013;42(1):19-25.
References Cited
Page 119
Contact PD/PI: Bakitas, Marie

47.
Li Z, Tosteson TD, Bakitas MA. Joint modeling quality of life and survival using a terminal decline model
in palliative care studies. Statistics in medicine. Apr 15 2013;32(8):1394-1406 PMID: 23001893;
PMCID: PMC3623280
48.
Williams BR, Woodby LL, Bailey FA, Burgio KL. Formative Evaluation of a Multi-Component,
Education-Based Intervention to Improve Processes of End-of-Life Care. Gerontology & geriatrics
education. 2014;35(1):4-22.
49.
Bailey FA, Williams BR, Woodby LL, et al. Intervention to Improve Care at Life's End in Inpatient
Settings: The BEACON Trial. Journal of general internal medicine. Jan 22 2014.
50.
Leigh AE, Burgio KL, Williams BR, Kvale E, Bailey FA. Hospice emergency kit for veterans: a pilot
study. J Palliat Med. Apr 2013;16(4):356-361.
51.
Casarett D, Pickard A, Bailey FA, et al. Do palliative consultations improve patient outcomes? J Am
Geriatr Soc. Apr 2008;56(4):593-599.
52.
Bailey FA, Ferguson L, Williams BR, et al. Palliative care intervention for choice and use of opioids in
the last hours of life. J Gerontol A Biol Sci Med Sci. Sep 2008;63(9):974-978.
53.
Bailey FA, Burgio KL, Woodby LL, et al. Improving processes of hospital care during the last hours of
life. Arch Intern Med. Aug 8-22 2005;165(15):1722-1727.
54.
Cheng JW, Nayar M. A review of heart failure management in the elderly population. Am J Geriatr
Pharmacother. Oct 2009;7(5):233-249.
55.
Havranek EP, Masoudi FA, Westfall KA, Wolfe P, Ordin DL, Krumholz HM. Spectrum of heart failure in
older patients: results from the National Heart Failure project. American heart journal. Mar
2002;143(3):412-417.
56.
Martinez-Selles M, Vidan MT, Lopez-Palop R, et al. End-stage heart disease in the elderly. Rev Esp
Cardiol. Apr 2009;62(4):409-421.
57.
Lorenz KA, Lynn J, Dy SM, et al. Evidence for improving palliative care at the end of life: a systematic
review. Ann Intern Med. Jan 15 2008;148(2):147-159.
58.
Zambroski C. Self-care at the end of life in patients with heart failure. Journal of Cardiovascular
Nursing. May-Jun 2008;23(3):266-276.
59.
Zambroski CH, Moser DK, Bhat G, Ziegler C. Impact of symptom prevalence and symptom burden on
quality of life in patients with heart failure. European journal of cardiovascular nursing : journal of the
Working Group on Cardiovascular Nursing of the European Society of Cardiology. Sep 2005;4(3):198-
206. 
60.
Zambroski CH, Moser DK, Roser LP, Heo S, Chung ML. Patients with heart failure who die in hospice.
American heart journal. Mar 2005;149(3):558-564.
61.
Hunt SA, Abraham WT, Chin MH, et al. 2009 focused update incorporated into the ACC/AHA 2005
Guidelines for the Diagnosis and Management of Heart Failure in Adults: a report of the American
College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines:
developed in collaboration with the International Society for Heart and Lung Transplantation.
Circulation. Apr 14 2009;119(14):e391-479.
62.
Johnson MJ, Booth S. Palliative and end-of-life care for patients with chronic heart failure and chronic
lung disease. Clin Med. Jun 2010;10(3):286-289.
63.
Steinhauser KE, Arnold RM, Olsen MK, et al. Comparing Three Life-Limiting Diseases: Does Diagnosis
Matter or is Sick, Sick? J Pain Symptom Manage. Jan 27 2011.
64.
Maessen M, Veldink JH, van den Berg LH, Schouten HJ, van der Wal G, Onwuteaka-Philipsen BD.
Requests for euthanasia: origin of suffering in ALS, heart failure, and cancer patients. J Neurol. Jul
2010;257(7):1192-1198.
65.
Goebel JR, Doering LV, Evangelista LS, et al. A comparative study of pain in heart failure and non-
heart failure veterans. J Card Fail. Feb 2009;15(1):24-30.
66.
De Jong MJ, Hall LA. Measurement of anxiety for patients with cardiac disease - A critical review and
analysis. Journal of Cardiovascular Nursing. Sep-Oct 2006;21(5):412-419.
67.
De Jong MJ, Moser DK, Chung ML. Anxiety, depression, and functional status are the best predictors
of health status for patients with heart failure. Journal of Cardiac Failure. Aug 2004;10(4):S21-S21.
68.
De Jong MJ, Chung ML, Wu J-R, Riegel B, Rayens MK, Moser DK. Linkages between anxiety and
outcomes in heart failure. Heart & Lung: The Journal of Acute and Critical Care. 2011;40(5):393-404.
69.
Faller H, Stork S, Schuler M, et al. Depression and disease severity as predictors of health-related
quality of life in patients with chronic heart failure--a structural equation modeling approach. J Card Fail.
May 2009;15(4):286-292 e282.
References Cited
Page 120
Contact PD/PI: Bakitas, Marie

70.
National Consensus Project. Clinical Practice Guidelines for Quality Palliative Care; Second Edition.
Brooklyn, NY: National Consensus Project for Quality Palliative Care;2009.
71.
Lewis EF. End of life care in advanced heart failure. Current treatment options in cardiovascular
medicine. Feb 2011;13(1):79-89.
72.
James T, Offer M, Wilson M, Delyea A, Johnson D. Increasing Palliative Consults for Heart Failure
Inpatients Using the Seattle Heart Failure Model. Journal of Hospice & Palliative Nursing. Sep-Oct
2010;12(5):273-281.
73.
Jaarsma T, Beattie JM, Ryder M, et al. Palliative care in heart failure: a position statement from the
palliative care workshop of the Heart Failure Association of the European Society of Cardiology. Eur J
Heart Fail. May 2009;11(5):433-443.
74.
Garin O, Ferrer M, Pont A, et al. Disease-specific health-related quality of life questionnaires for heart
failure: a systematic review with meta-analyses. Qual Life Res. Feb 2009;18(1):71-85.
75.
Kheirbek RE, Alemi F, Citron BA, Afaq MA, Wu H, Fletcher RD. Trajectory of illness for patients with
congestive heart failure. J Palliat Med. May 2013;16(5):478-484.
76.
Hupcey JE, Penrod J, Fenstermacher K. Review article: a model of palliative care for heart failure. Am
J Hosp Palliat Care. Oct-Nov 2009;26(5):399-404.
77.
Konstam MA, Greenberg B. Transforming health care through the medical home: the example of heart
failure. J Card Fail. Nov 2009;15(9):736-738.
78.
Waterworth S, Gott M. Decision making among older people with advanced heart failure as they
transition to dependency and death. Curr Opin Support Palliat Care. Dec 2010;4(4):238-242.
79.
Asch SM, Baker DW, Keesey JW, et al. Does the collaborative model improve care for chronic heart
failure? Med Care. Jul 2005;43(7):667-675.
80.
Rich MW, Beckham V, Wittenberg C, Leven CL, Freedland KE, Carney RM. A multidisciplinary
intervention to prevent the readmission of elderly patients with congestive heart failure. The New
England journal of medicine. Nov 2 1995;333(18):1190-1195.
81.
Blue L, Lang E, McMurray JJV, et al. Randomised controlled trial of specialist nurse intervention in
heart failure. BMJ: British Medical Journal. 2001;323(7315):715.
82.
Gonseth J, Guallar-Castillón P, Banegas JR, Rodríguez-Artalejo F. The effectiveness of disease
management programmes in reducing hospital re-admission in older patients with heart failure: a
systematic review and meta-analysis of published reports. European Heart Journal. September 1, 2004
2004;25(18):1570-1595.
83.
McAlister FA, Stewart S, Ferrua S, McMurray JJJV. Multidisciplinary strategies for the management of
heart failure patients at high risk for admission: A systematic review of randomized trials. Journal of the
American College of Cardiology. 2004;44(4):810-819.
84.
Stewart S, Horowitz JD. Home-Based Intervention in Congestive Heart Failure: Long-Term Implications
on Readmission and Survival. Circulation. June 18, 2002 2002;105(24):2861-2866.
85.
Strömberg A, Mårtensson J, Fridlund B, Levin LÅ, Karlsson J-E, Dahlström U. Nurse-led heart failure
clinics improve survival and self-care behaviour in patients with heart failure. European Heart Journal.
2003;24(11 %U http://eurheartj.oxfordjournals.org/content/24/11/1014.abstract):1014-1023.
86.
Krumholz HM, Amatruda J, Smith GL, et al. Randomized trial of an education and support intervention
to prevent readmission of patients with heart failure. Journal of the American College of Cardiology. Jan
2 2002;39(1):83-89.
87.
Bakitas M, Lyons K, Hegel M, et al. The Project ENABLE II Randomized Controlled Trial to Improve
Palliative Care for Patients with Advanced Cancer. Paper presented at: 10th National Conference on
Cancer Nursing Research2009; Orlando,FL.
88.
Bakitas M, Lyons KD, Hegel MT, et al. The project ENABLE II randomized controlled trial to improve
palliative care for rural patients with advanced cancer: Baseline findings, methodological challenges,
and solutions. Palliative and Supportive Care. 2009;7(01):75-86.
89.
McCorkle R, Ercolano E, Lazenby M, et al. Self-Management: Enabling and Empowering Patients
Living With Cancer as a Chronic Illness. Ca-a Cancer Journal for Clinicians. Jan-Feb 2011;61(1):50-62.
90.
Jacobsen J, Jackson V, Dahlin C, et al. Components of Early Outpatient Palliative Care Consultation in
Patients with Metastatic Nonsmall Cell Lung Cancer. J Palliat Med. Apr 2011;14(4):459-464.
91.
Bakitas M, Lyons KD, Hegel MT, Ahles T. Oncologists' perspectives on concurrent palliative care in a
National Cancer Institute-designated comprehensive cancer center. Palliative & supportive care. Oct 8
2012:1-9.
References Cited
Page 121
Contact PD/PI: Bakitas, Marie

92.
Maloney C, Lyons KD, Li Z, Hegel M, Ahles TA, Bakitas M. Patient perspectives on participation in the
ENABLE II randomized controlled trial of a concurrent oncology palliative care intervention: benefits
and burdens. Palliative medicine. Apr 2013;27(4):375-383 PMID: 22573470; PMCID: PMC3657725.
93.
Goldstein N, Bradley E, Zeidman J, Mehta D, Morrison RS. Barriers to conversations about deactivation
of implantable defibrillators in seriously ill patients: results of a nationwide survey comparing cardiology
specialists to primary care physicians. Journal of the American College of Cardiology. Jul 21
2009;54(4):371-373.
94.
Goldstein N, Carlson M, Livote E, Kutner JS. Brief communication: Management of implantable
cardioverter-defibrillators in hospice: A nationwide survey. Ann Intern Med. Mar 2 2010;152(5):296-299.
95.
Goldstein NE, Lynn J. Trajectory of end-stage heart failure: the influence of technology and implications
for policy change. Perspect Biol Med. Winter 2006;49(1):10-18.
96.
Morrison R. S. MDE. America's Care of Serious Illness: A state-by-state report card on access to
palliative care in our nation's hospitals. New York: Center to Advance Palliative Care;2011.
97.
Bakitas M, Clifford K, Kvale E. Chapter 43: Rural Palliative Care. In: Ferrell BR, Coyle N, eds. Oxford
Textbook of Palliative Nursing, 4rd Edition. Oxford: Oxford University Press.; 2014 (in press).
98.
Zuniga M, Anderson D, Alexander K. Heart Disease and Stroke in Rural America. In: Gamm L,
Hutchison L, Dabney B, Dorsey A, eds. Rural Healthy People 2010: A Companion Document to Healthy
People 2010. Vol 2. College Station, Texas2010:73-84.
99.
United States Department of Agriculture-Economic Research Service. The Economics of Food,
Farming, Natural Resources, and Rural America: Measuring Rurality: What is Rural? 2007;
http://www.ers.usda.gov/Briefing/Rurality/WhatisRural/. Accessed March 26, 2009.
100. 
Institute of Medicine. Crossing the Quality Chasm: A new health system for the 21st century. 
Washington, DC: National Academy Press;2001. 
101. 
Center to Advance Palliative Care, National Palliative Care Research Center. America's Care of 
Serious Illness: A State-by-State Report Card on Access to Palliative Care in Our Nation's Hospitals. 
New York: Center to Advance Palliative Care;2008. 
102. 
McCarthy EP, Burns RB, Davis RB, Phillips RS. Barriers to hospice care among older patients dying 
with lung and colorectal cancer. Journal of Clinical Oncology. 2003;21:728-735. 
103. 
Haller IV, Gessert CE. Utilization of medical services at the end of life in older adults with cognitive 
impairment: focus on outliers. Journal of palliative medicine. Apr 2007;10(2):400-407. 
104. 
Heart Failure Society of America. Health Literacy and Care of the Patient with Heart Failure: A Fact 
Sheet. St. Paul, MN: Heart Failure Society of America; 2009. 
105. 
Wu JR, Holmes GM, DeWalt DA, et al. Low literacy is associated with increased risk of hospitalization 
and death among individuals with heart failure. J Gen Intern Med. Sep 2013;28(9):1174-1180. 
106. 
McNaughton CD, Collins SP, Kripalani S, et al. Low numeracy is associated with increased odds of 30-
day emergency department or hospital recidivism for patients with acute heart failure. Circ Heart Fail. 
Jan 2013;6(1):40-46. 
107. 
Murray MD, Tu W, Wu J, Morrow D, Smith F, Brater DC. Factors associated with exacerbation of heart 
failure include treatment adherence and health literacy skills. Clin Pharmacol Ther. Jun 2009;85(6):651-
658. 
108. 
Noureldin M, Plake KS, Morrow DG, Tu W, Wu J, Murray MD. Effect of health literacy on drug 
adherence in patients with heart failure. Pharmacotherapy. Sep 2012;32(9):819-826. 
109. 
Macabasco-O'Connell A, DeWalt DA, Broucksou KA, et al. Relationship between literacy, knowledge, 
self-care behaviors, and heart failure-related quality of life among patients with heart failure. J Gen 
Intern Med. Sep 2011;26(9):979-986. 
110. 
Peterson PN, Shetterly SM, Clarke CL, et al. Health literacy and outcomes among patients with heart 
failure. JAMA. Apr 27 2011;305(16):1695-1701. 
111. 
Evangelista LS, Rasmusson KD, Laramee AS, et al. Health literacy and the patient with heart failure--
implications for patient care and research: a consensus statement of the Heart Failure Society of 
America. J Card Fail. Jan 2010;16(1):9-16. 
112. 
DeWalt DA, Schillinger D, Ruo B, et al. Multisite randomized trial of a single-session versus 
multisession literacy-sensitive self-care intervention for patients with heart failure. Circulation. Jun 
2012;125(23):2854-2862. 
113. 
Baker DW, Dewalt DA, Schillinger D, et al. The effect of progressive, reinforcing telephone education 
and counseling versus brief educational intervention on knowledge, self-care behaviors and heart 
failure symptoms. J Card Fail. Oct 2011;17(10):789-796. 
References Cited
Page 122
Contact PD/PI: Bakitas, Marie

114. 
Wu JR, Moser DK, Lennie TA, Peden AR, Chen YC, Heo S. Factors influencing medication adherence 
in patients with heart failure. Heart Lung. Jan-Feb 2008;37(1):8-16, 16 e11. 
115. 
Jaarsma T, Beattie JM, Ryder M, et al. Palliative care in heart failure: a position statement from the 
palliative care workshop of the Heart Failure Association of the European Society of Cardiology. Eur J 
Heart Fail. May 2009;11(5):433-443. 
116. 
Agren S, Evangelista L, Stromberg A. Do partners of patients with chronic heart failure experience 
caregiver burden? European journal of cardiovascular nursing : journal of the Working Group on 
Cardiovascular Nursing of the European Society of Cardiology. Dec 2010;9(4):254-262. 
117. 
Pinquart M, Sörensen S. Correlates of physical health of informal caregivers: a meta-analysis. J 
Gerontol B Psychol Sci Soc Sci. Mar 2007;62(2):P126-137. 
118. 
Perkins M, Howard VJ, Wadley VG, et al. Caregiving strain and all-cause mortality: evidence from the 
REGARDS study. J Gerontol B Psychol Sci Soc Sci. Jul 2013;68(4):504-512. 
119. 
Ji J, Zöller B, Sundquist K, Sundquist J. Increased risks of coronary heart disease and stroke among 
spousal caregivers of cancer patients. Circulation. Apr 2012;125(14):1742-1747. 
120. 
Candy B, Jones L, Drake R, Leurent B, King M. Interventions for supporting informal caregivers of 
patients in the terminal phase of a disease. Cochrane Database Syst Rev. 2011(6):CD007617. 
121. 
Hodges LJ, Humphris GM, Macfarlane G. A meta-analytic investigation of the relationship between the 
psychological distress of cancer patients and their carers. Soc Sci Med. Jan 2005;60(1):1-12. 
122. 
Stamataki Z, Ellis JE, Costello J, Fielding J, Burns M, Molassiotis A. Chronicles of informal caregiving in 
cancer: using 'The Cancer Family Caregiving Experience' model as an explanatory framework. Support 
Care Cancer. Feb 2014;22(2):435-444. 
123. 
Wadhwa D, Burman D, Swami N, Rodin G, Lo C, Zimmermann C. Quality of life and mental health in 
caregivers of outpatients with advanced cancer. Psychooncology. Feb 2013;22(2):403-410. 
124. 
Schulz R. Research priorities in geriatric palliative care: informal caregiving. J Palliat Med. Sep 
2013;16(9):1008-1012. 
125. 
Dunbar SB, Clark PC, Deaton C, Smith AL, De AK, O'Brien MC. Family education and support 
interventions in heart failure: a pilot study. Nurs Res. May-Jun 2005;54(3):158-166. 
126. 
McMillan SC, Small BJ. Using the COPE intervention for family caregivers to improve symptoms of 
hospice homecare patients: a clinical trial. Oncol Nurs Forum. Mar 2007;34(2):313-321. 
127. 
McMillan SC, Small BJ, Weitzner M, et al. Impact of coping skills intervention with family caregivers of 
hospice patients with cancer. Cancer 2005;106(1):214-222. 
128. 
Susan C. McMillan BJSMWRSMTLMWEH. Impact of coping skills intervention with family caregivers of 
hospice patients with cancer. Vol 1062006:214-222. 
129. 
McMillan SC, Small BJ, Haley WE, Zambroski C, Buck HG. The COPE Intervention for Caregivers of 
Patients with Heart Failure: An Adapted Intervention. Journal of hospice and palliative nursing : JHPN : 
the official journal of the Hospice and Palliative Nurses Association. Jun 1 2013;15(4). 
130. 
Buck HG, Zambroski CH, Garrison C, McMillan SC. "Everything They Were Discussing, We Were 
Already Doing": Hospice Heart Failure Caregivers Reflect on a Palliative Caregiving Intervention. 
Journal of hospice and palliative nursing : JHPN : the official journal of the Hospice and Palliative 
Nurses Association. Jun 1 2013;15(4):218-224. 
131. 
Riegel B, Lee CS, Dickson VV, Carlson B. An update on the self-care of heart failure index. J 
Cardiovasc Nurs. Nov-Dec 2009;24(6):485-497. 
132. 
Riegel B, Lee CS, Sochalski J. Developing an instrument to measure heart failure disease 
management program intensity and complexity. Circ Cardiovasc Qual Outcomes. May 2010;3(3):324-
330. 
133. 
Riegel B, Moser DK, Anker SD, et al. State of the science: promoting self-care in persons with heart 
failure: a scientific statement from the American Heart Association. Circulation. Sep 22 
2009;120(12):1141-1163. 
134. 
Wagner E. Chronic disease management: what will it take to improve care for chronic illness? . 
Effective Clinical Practice. 1998;1:2-4. 
135. 
Wagner EH, Austin BT, C. D, Hindmarsh M, Schaefer J, Bonomi A. Improving chronic illness care: 
translating evidence into action. Health Aff. 2001;20(6):64-78. 
136. 
Wasson J, Splaine M, Bazos D, Fisher E. Working inside, outside, and side by side to improve the 
quality of health care. Jt Comm J Qual Improv. 1998;24:513-517. 
References Cited
Page 123
Contact PD/PI: Bakitas, Marie

137. 
Peikes D, Chen A, Schore J, Brown R. Effects of Care Coordination on Hospitalization, Quality of Care, 
and Health Care Expenditures Among Medicare Beneficiaries: 15 Randomized Trials. JAMA : the 
journal of the American Medical Association. February 11, 2009 2009;301(6):603-618. 
138. 
Glasgow R, Whitesides H, Nelson C, King D. Use of the Patient Assessment of Chronic Illness Care 
(PACIC) with diabetic patients. Diabetes Care. 2005;28(11):2655-2661. 
139. 
Wright A, Zhang B, Ray A, et al. Associations between end-of-life discussions, patient mental health, 
medical care near death, and caregiver bereavement adjustment. JAMA : the journal of the American 
Medical Association. 2008;300(14):1665-1673. 
140. 
Danis M, Southerland LI, Garrett JM, et al. A prospective study of advance directives for life-sustaining 
care. N Engl J Med. Mar 28 1991;324(13):882-888. 
141. 
Temel JS, McCannon J, Greer JA, et al. Aggressiveness of care in a prospective cohort of patients with 
advanced NSCLC. Cancer. 2008;113:826-833. 
142. 
Teno J, Gruneir A, Schwartz Z, Nanda A, Welte T. Association between advance directives and quality 
of end-of-life care: A national study. Journal of the American Geriatrics Society. 2007;55:189-194. 
143. 
Teno JM, Shu JE, Casarett D, Spence C, Rhodes R, Connor S. Timing of Referral to Hospice and 
Quality of Care: Length of Stay and Bereaved Family Members' Perceptions of the Timing of Hospice 
Referral. Journal of pain and symptom management. 2007/8 2007;34(2):120-125. 
144. 
Meyers F, Linder J. Simultaneous care: Disease treatment and palliative care throughout illness. 
Journal of Clinical Oncology. 2003;21(7):1412-1415. 
145. 
Earle CC, Landrum MB, Souza JM, Neville BA, Weeks JC, Ayanian JZ. Aggressiveness of cancer care 
near the end of life: is it a quality-of-care issue? Journal of clinical oncology : official journal of the 
American Society of Clinical Oncology. Aug 10 2008;26(23):3860-3866. 
146. 
Berkman LF, Blumenthal J, Burg M, et al. Effects of treating depression and low perceived social 
support on clinical events after myocardial infarction: the Enhancing Recovery in Coronary Heart 
Disease Patients (ENRICHD) Randomized Trial. JAMA. Jun 18 2003;289(23):3106-3116. 
147. 
Czajkowski S, Arteaga S, Burg M, R A, Fisher J. Social support and coronary artery disease. In: Allan 
R, Fisher J, eds. Heart and mind: The practice of cardiac psychology. 2nded. Washington, DC: 
American Psychological Association; 2011:169-195. 
148. 
Lett HS, Blumenthal JA, Babyak MA, Strauman TJ, Robins C, Sherwood A. Social support and 
coronary heart disease: epidemiologic evidence and implications for treatment. Psychosom Med. Nov-
Dec 2005;67(6):869-878. 
149. 
Brink E, Karlson BW, Hallberg LRM. Health experiences of first-time myocardial infarction: factors 
influencing women's and men's health-related quality of life after five months. Psychology, Health & 
Medicine. 2002;7(1):5-16. 
150. 
Brown JR, Gillinder B. The relationship between coping style and affect in recovering cardiac patients. 
Current Research in Social Psychology. 2001;6(11):151-165 
151. 
van Elderen T, Maes S, Dusseldorp E. Coping with coronary heart disease: a longitudinal study. J 
Psychosom Res. Aug 1999;47(2):175-183. 
152. 
O'Hara RE, Hull JG, Lyons KD, et al. Impact on caregiver burden of a patient-focused palliative care 
intervention for patients with advanced cancer. Palliat Support Care. Dec 2010;8(4):395-404. 
153. 
Williams AW, Bakitas M. Cancer Family Caregivers:  A New Direction for Interventions. J Palliative 
Med. 15(7): 775-783. PMID:  22612407; PMCID: PMC3387766  
154. 
Williams AW, Bakitas M, Prigerson H. Determinants of Prolonged Grief in Cancer Family Caregivers. 
National Palliative Care Research Center Junior Career Development Award; 2011-2013. 
155. 
Miaskowski C. Symptom Trajectories, Palliative Care, and Quality of Life. Paper presented at: The 
Science of Compassion: Future Directions in End-of-Life and Palliative Care2011; Bethesda, MD. 
156. 
Miaskowski C, Dhruva A, Dodd M, et al. Trajectories of Fatigue in Patients With Breast Cancer Before, 
During, and After Radiation Therapy. Cancer nursing. May-Jun 2010;33(3):201-212. 
157. 
Ritchie CS, Currow DC, Abernethy AP, Kutner JS. Multisite studies offer a solution to recruitment 
challenges in palliative care studies. J Palliat Med. Mar 2013;16(3):225. 
158. 
Lu H, Trancik E, Bailey FA, et al. Families' perceptions of end-of-life care in Veterans Affairs versus 
non-Veterans Affairs facilities. J Palliat Med. Aug 2010;13(8):991-996. 
159. 
Kvale E, Ritchie C, Sudenga S, Jackson M, Kno H, Meleth S. Comorbidity Does Not Predict Symptom 
Burden in Palliative Care Outpatient (730). J Pain Symptom Manag. Feb 2010;39(2):438-438. 
References Cited
Page 124
Contact PD/PI: Bakitas, Marie

160. 
Kvale E, Ekundayo O, Ritchie C, Ahmed A. Predictors of Mortality among Community-Dwelling Older 
Adults with a History of Cancer in a Prospective Population-Based Study. Gerontologist. Oct 
2008;48:414-414. 
161. 
Casarett D, Pickard A, Bailey FA, et al. A nationwide VA palliative care quality measure: the family 
assessment of treatment at the end of life. J Palliat Med. Jan-Feb 2008;11(1):68-75. 
162. 
Patsopoulos NA. A pragmatic view on pragmatic trials. Dialogues in clinical neuroscience. 
2011;13(2):217-224. 
163. 
Thorpe KE, Zwarenstein M, Oxman AD, et al. A pragmatic-explanatory continuum indicator summary 
(PRECIS): a tool to help trial designers. J Clin Epidemiol. May 2009;62(5):464-475. 
164. 
Falk H, Ekman I, Anderson R, Fu M, Granger B. Older Patients’ Experiences of Heart Failure—An 
Integrative Literature Review. Journal of Nursing Scholarship. 2013;45(3):247-255. 
165. 
Kurland BF, Johnson LL, Egleston BL, Diehr PH. Longitudinal Data with Follow-up Truncated by Death: 
Match the Analysis Method to Research Aims. Stat Sci. 2009;24(2):211. 
166. 
Byock I. Palliative Care and Oncology: Growing Better Together. J Clin Oncol. January 10, 2009 
2009;27(2):170-171. 
167. 
Bakitas M, Tosteson TD, Li Z, et al. The ENABLE III Randomized Controlled Trial of Concurrent 
Palliative Oncology Care: Does Timing Matter? JAMA : the journal of the American Medical 
Association. 2014, under review. 
168. 
Dionne-Odom JN, Tosteson TD, Li Z, et al. The ENABLE III Randomized Controlled Trial of Concurrent 
Palliative Oncology Care: Caregiver Benefits. JAMA : the journal of the American Medical Association. 
2014, under review. 
169. 
Temel J, Jackson V, Billings A, et al. Phase II Study: Integrated palliative care in newly diagnosed 
advanced non-small cell lung cancer patients. J Clin Oncol. 2007;25(17):2377-2382. 
170. 
Follwell M, Burman D, Le LW, et al. Phase II Study of an Outpatient Palliative Care Intervention in 
Patients With Metastatic Cancer. Journal of clinical oncology : official journal of the American Society of 
Clinical Oncology. January 10, 2009 2009;27(2):206-213. 
171. 
McNiff KK, Neuss MN, Jacobson JO, Eisenberg PD, Kadlubek P, Simone JV. Measuring supportive 
care in medical oncology practice: lessons learned from the quality oncology practice initiative. J Clin 
Oncol. Aug 10 2008;26(23):3832-3837. 
172. 
National Comprehensive Cancer Network. Palliative Care V.I.2006, NCCN Clinical Practice Guidelines 
in Oncology. New York: National Comprehensive Cancer Network;2006. 
173. 
National Quality Forum. A National Framework and Preferred Practices for Palliative and Hospice Care 
Quality: A Consensus Report. Washington, DC: National Quality Forum;2006. 
174. 
Bakitas M, Macmartin M, Trzepkowski K, et al. Palliative care consultations for heart failure patients: 
how many, when, and why? J Card Fail. Mar 2013;19(3):193-201. 
175. 
Dionne-Odom JN, Kono A, Frost J, et al. Translating and Testing the ENABLE CHF PC Concurrent 
Palliative Care Model for Older Adults with Heart Failure and Their Family Caregivers. Journal of 
palliative medicine. 2014, in REVISION/RESUBMISSION. 
176. 
Shuaib FM, Durant RW, Parmar G, et al. Awareness, treatment and control of hypertension, diabetes 
and hyperlipidemia and area-level mortality regions in the Reasons for Geographic and Racial 
Differences in Stroke (REGARDS) study. Journal of health care for the poor and underserved. May 
2012;23(2):903-921. 
177. 
Safford MM, Brown TM, Muntner PM, et al. Association of race and sex with risk of incident acute 
coronary heart disease events. JAMA. Nov 7 2012;308(17):1768-1774. 
178. 
Durant RW, Parmar G, Shuaib F, et al. Awareness and management of chronic disease, insurance 
status, and health professional shortage areas in the REasons for Geographic And Racial Differences 
in Stroke (REGARDS): a cross-sectional study. BMC health services research. 2012;12:208. 
179. 
Durant RW, Legedza AT, Marcantonio ER, Freeman MB, Landon BE. Different types of distrust in 
clinical research among whites and African Americans. Journal of the National Medical Association. 
Feb 2011;103(2):123-130. 
180. 
Durant RW, Legedza AT, Marcantonio ER, Freeman MB, Landon BE. Willingness to participate in 
clinical trials among African Americans and whites previously exposed to clinical research. Journal of 
cultural diversity. Spring 2011;18(1):8-19. 
181. 
Bailey FA, Williams BR, Goode PS, et al. Impact of a hospice emergency kit for veterans and their 
caregivers: A prospective cohort study. journal of Hospice and Palliative Medicine. 2014, in press. 
182. 
WC. L. Seattle Heart Failure Model. The American Journal of Cardiology. 2013;111(8):1235. 
References Cited
Page 125
Contact PD/PI: Bakitas, Marie

183. 
Callahan C, Unverzagt F, Hui S, Perkins A, Hendrie H. Six-item screener to identify cognitive 
impairment among potential research subjects. Medical Care. 2002;40(9):771-781. 
184. 
Dunbar SB, Clark PC, Quinn C, Gary RA, Kaslow NJ. Family influences on heart failure self-care and 
outcomes. J Cardiovasc Nurs. May-Jun 2008;23(3):258-265. 
185. 
Bakitas M. Insights from a Family Focus Group on Hospital End-of-Life Care1999. Located at: 
Unpublished data, Dartmouth-Hitchcock Medical Center. 
186. 
Bakitas M, Daretany K. Improving End-of-Life Care: Hospital-based Palliative Care. In: Ferrell B, Coyle 
N, eds. Oxford Textbook of Palliative Nursing, 2nd Edition. Oxford: Oxford University Press; 2006:787-
815. 
187. 
Bakitas MA. Background Noise: The experience of chemotherapy-induced peripheral neuropathy. 
Nursing research. 2007;56(5):323-331. 
188. 
Skalla K, Bakitas M, Furstenberg C, Ahles T, Henderson J. Patients' need for information about cancer 
therapy. Oncol Nurs Forum. 2004;31(2):313-320. 
189. 
Bakitas M, Lyons Doyle K. Oncology Clincians' Perspectives on Providing Palliative Care for their 
Patients with Advanced Cancer. Paper presented at: 10th National Conference on Cancer Nursing 
Research2009; Orlando, FL  
190. 
Flemming K, Adamson J, Atkin K. Improving the effectiveness of interventions in palliative care: the 
potential role of qualitative research in enhancing evidence from randomized controlled trials. Palliative 
medicine. Mar 2008;22(2):123-131. 
191. 
Protheroe J, Bower P, Chew-Graham C. The use of mixed methodology in evaluating complex 
interventions: identifying patient factors that moderate the effects of a decision aid. Fam. Pract. 
December 1, 2007 2007;24(6):594-600. 
192. 
Lyons KD, Bakitas M, Hegel MT, Hanscom B, Hull J, Ahles TA. Reliability and validity of the Functional 
Assessment of Chronic Illness Therapy-Palliative care (FACIT-Pal) scale. J Pain Symptom Manage. 
Jan 2009;37(1):23-32. 
193. 
Green CP, Porter CB, Bresnahan DR, Spertus JA. Development and evaluation of the Kansas City 
Cardiomyopathy Questionnaire: a new health status measure for heart failure. Journal of the American 
College of Cardiology. Apr 2000;35(5):1245-1255. 
194. 
Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the Hospital Anxiety and Depression 
Scale: An updated literature review. Journal of Psychosomatic Research. 2002;52(2):69-77. 
195. 
Weitzner M, Jacobsen, P.B., Wagner, H., Friedland, J., & Cox, C. The caregiver quality of life index-
cancer (CQOL-C) scale: Development and validation of an instrument to measure quality of life of the 
family of caregiver of patients with cancer. Quality of Life Research 1999;8:55-63. 
196. 
Montgomery RJV, Borgatta EF, Borgatta ML. Societal and family change in the burden of care. In: Liu 
WT, Kendig H, eds. Who Should Care for the Elderly? Singapore: Singapore University Press; 2000:27-
54. 
197. 
Rosemann T, Laux G, Szecsenyi J, Grol R. The Chronic Care Model: congruency and predictors 
among primary care patients with osteoarthritis. Qual Saf Health Care. Dec 2008;17(6):442-446. 
198. 
Carver CS. You want to measure coping but your protocol's too long: Consider the brief COPE. 
International Journal of Behavioral Medicine. 1997;4:92-100. 
199. 
Oxman TE, Hull JG. Social support and treatment response in older depressed primary care patients. J 
Gerontol B Psychol Sci Soc Sci. Jan 2001;56(1):P35-45. 
200. 
Bakitas M, Ahles T, Skalla K, et al. Proxy perspectives regarding end-of-life care for persons with 
cancer. Cancer. 2008;112(8):1854-1861. 
201. 
Downey L, Curtis JR, Lafferty WE, Herting JR, Engelberg RA. The Quality of Dying and Death 
Questionnaire (QODD): empirical domains and theoretical perspectives. J Pain Symptom Manage. Jan 
2010;39(1):9-22. 
202. 
Curtis JR, Patrick DL, Engelberg RA, Norris K, Asp C, Byock I. A measure of the quality of dying and 
death. Initial validation using after-death interviews with family members. J Pain Symptom Manage. Jul 
2002;24(1):17-31. 
203. 
Prigerson HG, Maciejewski PK, Reynolds C, et al. Inventory of Complicated Grief: A scale to measure 
maladaptive symptoms of loss. Psychiatry Research. 1995;59:65-79. 
204. 
MacKinnon DP. Introduction to statistical mediation analysis. New York: Taylor and Francis; 2008. 
205. 
MacCallum R, Browne M, Sugawara H. Power analysis and determination of sample size for 
covariance structure modeling. Psychological Methods. 1996;1(2):130-149. 
References Cited
Page 126
Contact PD/PI: Bakitas, Marie

206. 
Fritz MS, Mackinnon DP. Required sample size to detect the mediated effect. Psychol Sci. Mar 
2007;18(3):233-239. 
207. 
Garin O, Ferrer M, Pont Ä, et al. Disease-specific health-related quality of life questionnaires for heart 
failure: a systematic review with meta-analyses. Quality of Life Research. 2009;18(1):71-85. 
208. 
Sullivan MD, Newton K, Hecht J, Russo JE, Spertus JA. Depression and health status in elderly 
patients with heart failure: a 6-month prospective study in primary care. The American journal of 
geriatric cardiology. Sep-Oct 2004;13(5):252-260. 
209. 
Pedersen SS, Hoogwegt MT, Jordaens L, Theuns DAMJ. Relation of Symptomatic Heart Failure and 
Psychological Status to Persistent Depression in Patients With Implantable Cardioverter-Defibrillator. 
The American journal of cardiology. 2011;108(1):69-74. 
References Cited
Page 127
Contact PD/PI: Bakitas, Marie