THE INTEGRATION OF EARLY PALLIATIVE CARE FOR PATIENTS WITH
HEART FAILURE: EFFECT ON PATIENT’S QUALITY OF LIFE
by
Jessie Harris
B.Sc., Simon Fraser University, 2011
B.S.N, British Columbia Institute of Technology, 2016

PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
IN
NURSING: FAMILY NURSE PRACTITIONER

UNIVERSITY OF NORTHERN BRITISH COLUMBIA
April 2025
© Jessie Harris, 2025

ii

Abstract
Heart Failure (HF) is a life-limiting condition which causes symptoms beyond the physical
manifestations of cardiac dysfunction. HF can significantly impact patients' quality of life
(QOL), which is often not addressed in standard regimes of HF care. QOL encompasses the
individual's physical, functional, psychological, and social aspects of life. The specialty of
palliative care (PC) addresses all these aspects and can significantly improve a patient’s QOL.
PC is underutilized for patients with HF due to the non-linear progression of the disease and the
general uncertainty of the prognosis. The aim of this integrative review was to explore the
impacts of early integration of outpatient PC on the QOL of patients with HF. Findings
demonstrate that outpatient PC can positively impact the QOL of HF patients and can be
introduced early in the disease process, even when patients are receiving life-prolonging
treatment. PC can improve measures of overall QOL, palliative symptom burden, HF symptom
burden, and depression in this populations. Primary care providers can implement the early
introduction of PC for their HF patients to preserve their QOL despite their current prognosis.

iii
Table of Contents
Abstract

ii

Table of contents

iii

List of Tables

v

Acknowledgement

vi

Chapter 1:

Introduction
Background
Heart Failure Incidence
Heart Failure Disease Course and Impacts on Quality of Life
Palliative Care
Benefits of Early Initiation of Palliative Care
Barriers to Palliative Care in Heart Failure
Uncertainty of Disease Progress
Lack of Knowledge of Benefits of Palliative Care
The Association of Palliative Care to End-of-Life
Current Heart Failure Guidelines

1
3
4
4
5
6
8
8
9
9
10

Inclusion and Exclusion Criteria
Data Extraction

11
12
12

Overview of Studies
Study Locations
NYHA Heart Failure Classifications
Delivery of Palliative Care
Effect of Palliative Care on Quality of Life in Heart Failure
Effect on Overall Quality of Life
Effect on Heart Failure Symptom Burden
Effect on Palliative Symptom Burden
Depression
Effective Heart Failure Programs
Qualitative Findings of Palliative Care on Quality of Life
Summary of Impact of Palliative Care on Heart Failure

14
14
14
15
18
19
20
25
27
29
30
32
33

Implications for Practice
Nurse Practitioner Roles in Provision of Palliative Care
Limitations
Sources of Bias
Future Research

34
36
38
39
40
41

Chapter 2: Method

Chapter 3: Results

Chapter 4: Discussion

iv

Conclusion
References
Appendices

42
44
Appendix A: Search Terms and PRISMA Diagram
Appendix B: Quality Assessment

54
56

v
List of Tables
Table 1: NYHA Classification (American Heart Association, 2023)

3

Table 2: Study Identification breakdowns

16

Table 3: Inclusion and Exclusion Criteria

17

Table 4: Total Quality of Life

24

Table 5: Total CHF Symptom Burden

26

Table 6: Total Palliative Care Symptom Burden

29

Table 7: Depression Measures

30

Table 8: Effective HF Programs

32

vi
Acknowledgement
I want to thank Dr. Nicola Waters and Dr. Catharine Schiller for their fantastic support
and encouragement throughout this process. Your guidance, expertise, and kindness have been
inexpressibly helpful and appreciated. I want to thank Brent, my fiancé and rock, who has been
highly supportive and encouraging; he has been my sounding board and my biggest cheerleader
throughout this journey. Finally, I would like to thank Hank, the ever-loyal office dog, who has,
without a doubt, listened to the content of this project the most; he has provided moral support in
the form of requesting endless pats and ensuring I get enough outside time and stress relief.

1

The Integration of Early Palliative Care for Patients with Heart Failure: Effect on
Patient’s Quality of Life
Heart failure is a life-limiting clinical syndrome caused by cardiac dysfunction; it is
diagnosed clinically based on the patient’s symptoms, which often first present as dyspnea and
fatigue (Colucci & Borlaug, 2024). There are many treatment options utilized to delay the
progression of this life-limiting disease, which patients can misconstrue as curative rather than
medical management (Namukwaya et al., 2017). When patients are symptom-free due to
effective medical management, they often presume that they no longer have HF, not realizing
that the medical management techniques are not curative (Namukwaya et al., 2017). Due to the
variance between periods of exacerbations and medical management, communicating the
prognosis of HF can be a challenge. Healthcare providers often struggle to predict the course of
HF, as many variables can alter the disease course, and there is wide interpatient variability
(Colucci, 2024; Jones et al., 2019). The uncertainty of future illness trajectory can be distressing
for patients, particularly during periods of exacerbations when their symptoms are not effectively
managed (Jones et al., 2019). During the chronic phases of HF, discussions between healthcare
providers and patients regarding the disease process, prognosis and advanced care planning are
imperative; this provides patients with a better understanding of their disease, and acute
exacerbations are less alarming and easier to manage (Jones et al., 2019). Patients appreciate
knowing what is going on, and providers taking the time to explain things can significantly
impact their quality of life (QOL) (Ramanayake et al., 2016).
QOL can have many definitions depending on the person and encompasses physical,
functional, psychological, and social aspects of the individual’s life (Fallowfield, 2009). Higher

2
levels of QOL are associated with improved prognosis, so assessing and maintaining QOL
throughout treatment is important (Fallowfield, 2009). Heo et al. (2009) found that the definition
of QOL in patients with HF was multi-dimensional, encompassing aspects such as the ability to
perform physical and social activities, happiness, the ability to be at peace, and being around
people who support you. Garcia-Soleto et al. (2013) found that QOL measures were significantly
higher in HF patients after discharge from the hospital, demonstrating the value of outpatient
care on QOL. Primary care providers (PCPs) play an important role in ensuring that patients get
the best outpatient care as they have a rapport with patients and their families and are typically
the easiest to access (Ramanayake et al., 2016). PCPs provide access to specialists, liaise with
appropriate providers through referrals, integrate specialists’ care plans with concurrent
treatments, and ensure the patient receives the best possible care (Ramanayake et al., 2016).
Early discussions of disease progression and advanced care planning can be difficult for PCPs to
have due to the uncertainty of how things will progress, particularly early in the disease process
and the resistance of patients and their families to recognize the severity of the disease (Nowels
et al., 2016). Implementing specialties such as palliative care (PC) can help patients and PCPs
ease into the transition of living with life-limiting chronic conditions and aid in these discussions
(Beernaert et al., 2014).
Regarding chronic conditions with inconsistent life expectancy, such as HF, PC is an
under-utilized specialty (Jones et al., 2019). There is often a general lack of knowledge about
when PCPs should refer to PC, and it is often done late in the disease progress, closer to end-oflife (Ramirez & Verma, 2024). PC has a negative connotation due to its association with end-oflife care. However, early introduction to PC has demonstrated improved QOL, symptom control,
and general patient satisfaction in their care with life-limiting diseases (Ramirez & Verma,

3
2024). It has also been demonstrated to prolong life by an average of 2.5 months in cancer
patients when introduced at the time of diagnosis (Ramirez & Verma, 2024). Although PC is
more commonly associated with conditions that have predictable disease progression, such as
cancer, this integrative review aims to determine the effect PC has on QOL in patients with HF.
How does the early introduction of outpatient PC affect QOL in patients with HF?
Background
HF is a clinical syndrome that can be caused by several different cardiac diseases
occurring individually or concurrently that progressively decrease the effectiveness of the heart
to pump blood (Colucci & Borlaug, 2022). Eventually, the heart cannot meet the body's
metabolic demands, which presents with various symptoms (Colucci & Borlaug, 2022).
Diagnosis is primarily made clinically based on presenting symptoms, history, physical
examination, and laboratory and diagnostics imaging studies (Colucci & Borlaug, 2023). The
New York Heart Association (NYHA) has developed a grading system based on the severity of
symptoms a patient presents with, which is known as the functional classification of HF
(Colucci, 2022). This classification (Table 1) is dynamic depending on the effectiveness of
medical management and is frequently used to help guide treatment (American Heart
Association, 2023).
Table 1: NYHA Classification (American Heart Association, 2023)
Classification Patient Presentations
I
No limitation of physical activity. Ordinary physical activity does not cause
undue fatigue, palpitation or shortness of breath
II
Slight limitation of physical activity. Comfortable at rest. Ordinary physical
activity results in fatigue, palpitation, shortness of breath or chest pain.
III
Marked limitation of physical activity. Comfortable at rest. Less than ordinary
activity causes fatigue, palpitation, shortness of breath or chest pain.
IV
Symptoms of heart failure at rest. Any physical activity causes further
discomfort.

4

Heart Failure Incidence
As the population ages, the incidence of HF diagnoses increases, and as time progresses,
medical therapies continue to advance; despite this, mortality rates of HF remain high (Colucci,
2023). The total number of deaths in Canada in 2023 due to major cardiovascular disease (CVD)
was 76,962 (Statistics Canada, 2025). Approximately 750,000 Canadians are living with HF,
with an estimated 100,000 new diagnoses annually (Saveski et al., 2025). According to a
systematic review conducted by Jones et al. (2019) looking at the prognosis of HF, the ten-year
survival rate of HF is 34.9%. Many factors affect the survival rates of HF, including age, sex,
and the cause of cardiac dysfunction (Colucci, 2023), with individuals at advanced ages having a
significantly higher mortality rate (Jones et al., 2019). Hospitalization for HF exacerbations is an
indication of a poorer prognosis for patients and is related to an increase in mortality (Colucci,
2023). Within Canada, HF is among the top reasons for hospitalizations, with over 70,000 yearly
admissions and a median length stay of 7 days (Saveski et al., 2025). The 30-day hospitalization
readmission rate for HF has remained at 20% over the past decade despite an improved
knowledge base and the presence of evidence-based guidelines for HF management (Saveski et
al., 2025). This data indicates that there is room for improvement in the standard care of HF,
with the potential for collaboration with specialties that manage other aspects of care in the
outpatient setting.
Heart Failure Disease Course and Impacts on Quality of Life
When a patient’s condition begins to deteriorate, leading to increased emergency
utilization and the need for hospitalization, it can be very distressing and significantly impact a
patient’s QOL (Colucci, 2023). Due to the unpredictable nature of HF and frequent fluctuations

5
between NYHA classifications, patients are left feeling anxious and depressed about their
condition, contributing to a negative impact on their QOL (Corliss, 2023). Providers are often
not confident in their prognosis due to the variations in the condition, and important
conversations around the anticipated disease progression may be delayed, causing uncertainty
for patients (Jones et al., 2024). The ambiguity in disease progression and frequent fluctuation
between NYHA classifications causes patients to overestimate their life expectancy and
experience undue duress when their conditions significantly decline (Jones et al., 2019).
Integrating these difficult conversations into the provision of HF could potentially ease some
stress and uncertainty for HF patients and outline a more apparent trajectory of their illness,
improving their overall QOL.
Palliative Care
PC is a medical specialty that encompasses all the domains of suffering, including the
physical, emotional, psychosocial and spiritual issues that accompany chronic illnesses such as
HF (Corliss, 2023) and can be effectively used alongside life-prolonging care (Ramirez &
Verma, 2024). In 2002, the World Health Organization updated the definition of PC as
An approach that improves the quality of life of patients (adults and children) and their
families who are facing problems associated with life-threatening illness. It prevents and
relieves suffering through the early identification, correct assessment and treatment of
pain and other problems, whether physical, psychosocial or spiritual. (World Health
Organization, 2025, para. 1).
Despite this definition suggesting improved QOL with early identification, PC continues to focus
on the treatment of those whose illness is no longer responsive to other medical modalities late
in the disease process and for end-of-life treatments (Ramirez & Verma, 2024). In the case of

6
HF, this would be when cardiac dysfunction reduces cardiac output, hypotension and renal
dysfunction begin to dominate the disease process, and medications are no longer effective in
managing symptoms (Allen, 2025). Introducing PC before the HF symptom burden is too high
can greatly improve a patient’s QOL when they are living with the disease and decrease overall
morbidity.
HF can negatively impact an individual’s QOL to the point where they no longer want to
continue living. In BC, from April 1 to June 30, 2023, 19.6% of the total cases of medical
assistance in dying (MAID) were requested due to CVD (Government of British Columbia,
2023b). Of this 19.6%, HF comprised 54.6% of these MAID requests (Government of British
Columbia, 2023b). Although this data does not indicate whether those who opted for MAID had
previous encounters with PC, it does demonstrate that the effects on QOL are so severe that a
patient would choose MAID rather than continue in the progression of their HF. Addressing
issues in QOL early in the disease progression and providing PC could potentially mitigate
suffering and decrease the demand for MAID in HF.
Benefits of Early Initiation of Palliative Care
Introduction of PC at the time of diagnosis is recommended in seriously ill cancer
patients with a focus on the management of physical symptoms, emotions, social concerns and
spirituality (Ramirez & Verma, 2024). The benefits of early PC in cancer patients have
demonstrated prolonged lifespan, improvements in QOL, symptom control and patient/caregiver
satisfaction levels when compared to standard care (Ramirez & Verma, 2024). In cancer
patients, early PC was associated with less aggressive interventions, such as mechanical
ventilation and chest compressions, which are associated with a worse QOL after intervention
(Ramirez & Verma, 2024). This demonstrates that the early introduction of PC positively

7
impacts the QOL of patients with life-limiting conditions. The research by Ramirez and Verma
(2024) focuses on the effects PC has on cancer, so how does this relate to HF?
Cancer is the second most common cause of death after CVD, with HF being one of the
most frequent causes of hospitalization in CVD (Askoxylakis et al., 2010). Despite this, cancer is
the condition most associated with PC (Ramirez & Verma, 2024). In data from a systematic
review by Askoxylakis et al. (2010), the five-year survival rate after diagnosis for all cancers
was 43%, whereas the five-year survival rate for HF varied between 26 and 52%. Askoxylakis et
al. argue that based on the relative risk of survival, cancer does not necessarily have a worse
prognosis than HF despite cancer’s association with PC (Askoxylakis et al., 2010). The
trajectory of illness in HF tends to be more unpredictable than cancer (Askoxylakis et al., 2010),
which is why there are barriers to the early introduction of PC in HF (Corliss, 2024). A few
benefits seen in the early introduction of PC are improved management at home, leading to
fewer hospital-acquired infections and more time spent with family (Corliss, 2024). PC helps
patients better understand the risks and benefits of different treatment modalities and helps focus
on the individual desires that a patient has in terms of long-term goals and QOL (Corliss, 2024).
Despite HF having a worse prognosis than cancer (Askoxylakis et al., 2010), there remain
significant barriers to the early introduction of PC in HF. Early evidence suggests that HF
patients may benefit from integrating PC into their care model; however, it remains underutilized
(Corliss, 2024). PC has demonstrated positive effects on the QOL of cancer patients and their
caregivers (Ramirez & Verma, 2024). However, there is still limited knowledge of how PC use
in HF impacts QOL; this integrative review intends to address this current gap in knowledge.

8
Barriers to Palliative Care in Heart Failure
Significant barriers impact the number of HF patients who receive a referral to PC. This
includes the unpredictability of the HF disease process, a lack of knowledge of the benefit PC
can have on non-cancer illnesses, and its negative association with end-of-life care (Crimmins et
al., 2020). As healthcare workers, educating ourselves and identifying our biases in healthcare
provision, including those that potentially create barriers to introducing a beneficial service for
patients, is important.
Uncertainty of the Disease Progress. Throughout the disease course, HF patients will
face drastic changes in their functional capacity, both physical and psychological, and their
symptom burden in a non-linear manner, increasing demands on the patients, clinicians, and the
healthcare system (Crimmins et al., 2020). As outlined by Poon et al. (2022); both the
hospitalization and readmission rates of HF patients are high. Patients often have poor health
literacy when it comes to the management of their HF; this includes recognizing symptoms of
HF, medication management, dietary restrictions and how to prevent acute exacerbations
(Artinian et al., 2002). The misunderstanding of their diagnosis can have significant impacts on
their QOL as they pursue life-saving therapy into the terminal phases of their illness (Jones et al.,
2019). PC has demonstrated significant benefits for patient QOL for those living with lifelimiting illnesses (Corliss, 2024; Ramirez & Verma, 2024), and despite medical advances,
mortality (Colucci, 2023; Jones et al., 2019) and hospitalization and readmission rate (Poon et
al., 2022) of HF remain unacceptably high. Although many providers focus on the ambiguity of
the prognosis, PC is based on the needs of the patients, not the disease process and can be
appropriate at any time during the disease course, even if the patient is in a stable condition
(Crimmins et al., 2020). Many PCPs avoid having end-of-life discussions with their patients

9
early in the disease progression due to the uncertainty of the prognosis, so often, patients are
unaware of the benefits of PC (Enguidanos et al., 2020). Despite HF having an inconsistent
prognosis, collaboration with PC could potentially meet the varying needs of the patient. This
integrative review intends to examine the knowledge base on early PC, and explore how, despite
the ambiguity of the disease progress, it may impact the QOL of HF patients.
Lack of Knowledge of the Benefits of Palliative Care. Providers and patients have a
knowledge deficit of what benefit PC can provide to illness management before the patient is at
end-of-life (Crimmins et al., 2020; Ramirez & Verma, 2024). Enguidanos et al. (2020)
conducted a study on the provider-perceived barriers to home-based PC and found a wide
variance of knowledge and understanding of PC, ranging from a complete lack of knowledge to
many misconceptions and confusion about PC. Many assumed that PC was only for those near
end-of-life and no longer pursuing medical management of their conditions (Enguidanos et al.,
2020). This confusion could be due to the unawareness of the wide variety of services that PC
can provide (Enguidanos et al., 2020), including managing distressing symptoms such as
shortness of breath, pain, anorexia, fatigue, and depression that are often overlooked in regular
HF care (Crimmins et al., 2020). The primary focus of PC is to improve QOL for patients and
their families facing life-limiting illnesses, but it does not necessarily indicate that a patient is
close to end-of-life (Crimmins et al., 2020). It is important to address the knowledge gaps that
PCPs have on PC as there may be a benefit to those who are diagnosed with life-limiting illness.
The Association of Palliative Care to End-of-life. There is a negative connotation with
PC and the association with end-of-life, so there is often hesitancy on the part of the healthcare
provider and the patient in integrating PC (Ramirez & Verma, 2024). PCPs often erroneously
equate PC with Hospice and its association with end-of-life (Enguidanos et al., 2020). Hospice is

10
a subcategory of PC that is delivered when the patient is deemed to have less than six months
remaining to live; although all Hospice care is PC, not all PC is Hospice (Corliss, 2024; Ramirez
& Verma, 2024), and patients and providers often misconstrue this. PC allows for the medical
management of HF while offering symptom relief and interventions that address the patient's
holistic needs (Crimmins et al., 2020). Crimmins et al. (2020) argue that this is why PC is
important to implement; PC is a specialty that is trained to have difficult conversations about
disease progression, and it may be beneficial in supporting patients to ensure QOL is preserved.
The awareness of this negative association between PC and end-of-life can aid PCPs in having
open discussions with their patients about PC and how it may benefit their QOL.
Current Heart Failure Guidelines. The BC Guidelines (2023a) on HF management,
suggest that PC should not be delayed for a patient with serious illness who has physical,
psychological, social, or spiritual distress simply because they are pursuing disease-directed
treatment. PC in HF can address pain, dyspnea, and other associated symptoms while prioritizing
QOL (Government of British Columbia, 2023a). Despite clearly outlined evidence-based
instances of when to consider PC consultation in HF in the BC Guidelines (2023a), very few HF
patients receive this vital service early, if at all, due to ongoing gaps in current knowledge about
PC. The current barriers to introducing PC early in the disease process of HF demonstrate there
is a current gap in the knowledge on how PC can positively impact the care and QOL of HF
patients; the purpose of this integrative review is to address these knowledge gaps and determine
if the early introduction of PC impacts the QOL of HF patients.

11
Method
When performing an integrative review, developing a strong research question is the first
step in conducting research and shapes how you perform your search (Mohanan &
Parameswaran, 2022). After brainstorming research questions and subjecting them to the FINER
criteria (Mohanan & Parameswaran, 2022), the question ‘How does early introduction of
outpatient PC affect QOL in patients with HF?’ was developed. During the development of the
search strategy, A Step-by-Step Guide to Conducting a Search (Melilo, 2020) was reviewed,
which helped choose which databases to utilize and strongly recommended using resources such
as librarians in the search process. Following consultation with the knowledge synthesis
librarian, a search strategy was compiled.
Three databases were searched: CINAHL, Medline, and APA PsycInfo. A search was
conducted on Google Scholar to identify any articles that may not be in the databases and for
information pertinent to the background or introduction. A quick scan of the articles in Google
Scholar was done with a filter for any articles ‘Since 2020’, and any articles that met the
inclusion/exclusion criteria discussed below within the first three pages were utilized. Search
terms utilized aimed to find articles that discussed the effects of PC on HF patients’ QOL in
outpatient settings. The main search terms and Boolean phrases used for CINAHL and Medline
were “Palliative Care” or “Palliative Medicine” or “palliative care” AND “early introduction” or
“early referral” or “early initiation” or time* AND “Heart Failure” or “heart failure” or CHF
AND “Quality of Life” or “Psychological Well-Being” or “quality of life” or “well-being” or
“life satisfaction” AND “Home Health Care” or community or outpatient or home*. The main
search terms differed slightly for PsycInfo as they had different subtopics and included
“Palliative Care” or “Health Care Delivery” or “Spiritual Care” or “palliative care” AND “early

12
introduction” or “early referral” or “early initiation” or time* AND “heart failure” AND
“Quality of Life” or “Well Being” or “Life satisfaction” or “quality of life” or “well-being” or
“life satisfaction AND “Community Treatment” or “Outpatient Treatment” or “Home Care” or
community or outpatient or home*. This is summarized for each database, outlining the number
of articles retrieved using this strategy in a table in Appendix A.
Inclusion and Exclusion Criteria
The inclusion criteria that were employed in this screening were:
: studies focused on the patient’s experience and QOL
: studies focused on HF specifically
: studies focused on the outpatient provision of PC
: studies that focused on PC as an intervention
The exclusion criteria employed in this screening were:
: studies that utilized in-patient intervention
: studies that focused on caregivers’ experience
: studies that included patients without HF
: studies that focused on end-of-life
: pilot studies that did not include final data
: systematic and integrative reviews
Data Extraction
The search results from the three databases and Google Scholar were imported into
Covidence systematic review software (2024). “Covidence is a web-based collaboration software
platform that streamlines the production of systematic and other literature reviews” (Covidence
systematic review software, 2024, para. 5). A total of 61 articles were uploaded into Covidence;

13
seven were removed by the software as duplicates and double-checked to ensure they were not
removed in error. Sixty-four were entered into a title and abstracts were screened by a single
reviewer. Thirty-nine articles were deemed irrelevant based on inclusion/exclusion criteria in the
title and abstract screening. Fifteen articles entered a full test screening, and eight articles were
selected for data extraction by a single reviewer. See the PRISMA diagram in Appendix A for a
summary.
Data extraction and quality assessment were completed utilizing Covidence systematic
review software (2024). The quality assessment tool utilized was the Cochrane RoB1 tool
(Covidence Systematic Review Software, 2024), which is summarized in Appendix B. Data
extraction involved carefully reading through the results to determine the specific measures of
QOL utilized in each study, which will be discussed in the next section.

14
Results
The method described above yielded a total of 8 articles. The following section will
critically review these articles, beginning with an overview of the studies’ characteristics, how
the delivery of PC differed between studies and a comparison of how PC affected the QOL of
their HF subjects. Findings are organized into the different aspects of QOL explored in the
articles, including overall QOL, palliative and HF symptom burden, and depression, as well as
characteristics of an effective HF program and themes that emerged from qualitative interview
questions.
Overview of Studies
This section will review the characteristics of the studies included in this integrative
review based on their location, the NYHA classifications of their subjects, the type of PC
provided and the implications these may have on the integrative review findings.
Study Locations
The studies were from a variety of developed countries. To note, the three studies from
the United States of America (USA) (Evangelista et al., 2012; Flint et al., 2017; O’Riordan et al.,
2019) were the only studies included from countries that have solely privatized health care; the
other countries include Canada (Lewin et al., 2017), China (Ng & Wong, 2018), Switzerland
(Gonzalez-Jaramillo et al., 2022), Scotland (Boyd et al., 2009), and Colombia (Arenas Ochoa et
al., 2022) which utilize public health care systems with privatized options. The studies do not
mention whether the sampling of participants took place in privatized clinics or hospitals; one
study (Evangelista et al., 2012) included financial resources as a portion of the PC assessment,
two studies (Ng & Wong, 2018; Gonzalez-Jaramillo et al., 2022) included finances in their needs
assessment. This may have implications on this integrative review because sampling subjects

15
from privatized clinics may impact the subject’s baseline characteristics. Those with higher
socioeconomic status (SES) are more capable of paying for healthcare; lower SES is associated
with higher HF-related mortality even in countries with public healthcare (Averbuch et al.,
2022). This could impact the studies’ results as those with lower SES may have baseline poorer
QOL and, therefore, show a more significant increase in QOL with their intervention,
demonstrating the potential for selection bias (Melnyk & Fineout-Overholt, 2023).
All the studies included data collected from outpatient HF clinics or home-based care as
outpatient care is the focus of the current research question. One of the studies was from a rural
setting (Boyd et al., 2009), which may impact specialties such as PC and resources available to
these subjects as rural sites tend to be more underserviced.
NYHA Heart Failure Classifications
The NYHA classification of patients included in this review differed between studies and
is summarized in Table 2. Three studies included patients with NYHA classification III or IV
(Boyd et al., 2009; Lewin et al., 2017; Ng & Wong, 2018), which is associated with the
presentation of HF symptoms at rest (see Table 1 for definitions). This could have implications
for this review as the intention was to focus on early introduction. However, NYHA
classification is a dynamic process and does not imply these patients are late in the disease
course; it also does not specify if they are early after diagnosis of their HF; this is further
explored as a limitation of this integrative review. The overview of each study is summarized in
Table 2 and the exclusion and inclusion criteria of each study in this integrative review is
summarized in Table 3.

16

17

18
Delivery of Palliative Care
There are many ways outpatient PC can be provided to patients, and it is best
individualized to meet a person's specific physical, emotional, psychosocial and spiritual needs
(Corliss, 2023). For this reason, the method of PC delivery is important to discuss, as it can
impact the outcome of how it affects a person’s QOL. The type and delivery method of PC
varied between studies and could have potential effects on the outcomes of how it impacted
QOL in HF patients within the studies utilized in this review. Two studies (Ng & Wong, 2018;
O’Riordan et al., 2019) utilized a combination of in-home visits and telehealth for follow-up, one
study utilized only telehealth (Evangelista et al., 2012), and three studies were based within a HF
clinic (Arenas Ochoa et al., 2021; Gonzalez-Jaramillo et al., 2022; Lewin et al., 2017). One
study (Lewin et al., 2017) had access to a PC Nurse Practitioner (NP) providing coverage 24
hours a day, seven days a week for symptom management support. The PC interventions
provided were diverse between groups, but all focused on the key components of PC. The main
PC provided was symptom management (Ng & Wong, 2018; O’Riordan et al., 2019), social,
spiritual and existential support (Lewin et al., 2017; Ng & Wong, 2018; O’Riordan et al., 2019),
advanced care planning (Ng & Wong, 2018; O’Riordan et al., 2019), and basic HF symptom
management (Lewin et al., 2017). Two studies (Evangelista et al., 2012; Lewin et al., 2017)
provided a treatment plan based on the PC assessment accessible to the patient and all healthcare
providers. Four studies (Arenas Ochoa et al., 2021; Boyd et al., 2009; Flint et al., 2017;
Gonzalez-Jaramillo et al., 2022) did not provide any direct PC intervention. Flint et al. reviewed
subjects from previous data collected in a study that was based on symptom management in HF;
however, directly in this study, they did not provide any symptom management; they utilized
latent growth analysis to divide the subjects into groups based on their disease trajectories.

19
Arenas Ochoa et al. divided subjects into groups for comparison; the subjects’ cardiologists
deemed them to either require PC or not at the time of sampling; these groups were then
compared on QOL measures. Gonzalez-Jaramillo et al. assessed the needs of HF patients with
QOL measures and what they felt their current care was lacking in usual HF care. Boyd et al.
reviewed patients’, caregivers’, and providers’ perspectives on current HF care and what they
felt was missing. Although Arenas Ochoa et al. (2021), Boyd et al. (2009), Flint et al. (2017),
and Gonzalez-Jaramillo et al. (2022) do not directly explore a cause-and-effect relationship
between PC and QOL, they were included in this review as they look at QOL factors and assess
how PC can or cannot impact the care within these diverse groups.
The general overview of the studies utilized in this integrative review shows some
similarities and differences in the characteristics of each. Having an overarching understanding
of where the studies were conducted, the NYHA classification of the subjects included in the
studies, and the different ways that PC was provided or examined in each study is important due
to the implications these aspects may have on the outcomes of the studies.
Effect of Palliative Care on Quality of Life in Heart Failure
QOL is a multidimensional concept affected by physical and psychosocial symptoms that
limit a patient’s daily physical and social activities (Heo et al., 2009). Despite QOL being an
abstract concept, concrete measures have been developed to look at specific aspects of QOL.
The aspects of QOL identified and measured in the research articles included in this integrative
review were overall QOL, which measures overall physical, emotional, socio-economic, and
spiritual health (Arenas Ochoa et al., 2021; Evangelista et al., 2012; Flint et al., 2017; Lewin et
al., 2017; Ng & Wong, 2018; O’Riordan et al., 2019); palliative symptom burden, which
measures the impact of palliative-associated symptoms on a patient’s life (Ng & Wong, 2018;

20
O’Riordan et al., 2019; Evangelista et al., 2012; Flint et al., 2017); HF symptom burden, which
measures the impact of HF-related symptoms on a patient’s life (Arenas-Ochoa et al., 2021; Flint
et al., 2017; Lewin et al., 2017; Ng & Wong, 2018); and depression (Arenas Ochoa et al., 2021;
Evangelista et al., 2012; Flint et al., 2017). Other aspects the studies utilized in this review
looked at were the attributes that encompass an effective HF-PC program (Boyd et al., 2009;
Gonzalez-Jaramillo et al., 2022). Based on previous research on patients with other life-limiting
conditions, it was anticipated that PC would positively impact the QOL of HF patients involved
in these studies.
Effect on Overall Quality of Life
A patient’s overall QOL encompasses their physical, emotional, socio-economic and
spiritual well-being, which can be significantly impacted during the course of a chronic illness
such as HF. The impact of PC on HF patients’ overall QOL was measured in several of the
studies included in this review utilizing different tools that quantify the different aspects of QOL.
This section will review those studies and the impact the found PC had on QOL, comment on
how they differed, and the implications for this review.
In three studies, the total QOL measures showed overall improvements in both the
intervention group receiving PC and the control groups (Evangelista et al., 2012; Ng & Wong,
2018; O’Riordan et al., 2019). Within the intervention group, Ng & Wong (2018) found that
total QOL showed significant improvement over time (P=0.016). However, there were no
significant differences between groups in total QOL found by Ng & Wong and O’Riordan et al.
Ng & Wong measured the overall QOL utilizing the McGill Quality of Life Questionnaire
(Cohen, 1996), which is non-specific to HF and is utilized for anyone with a life-limiting illness,
validated to measure how the disease alters QOL (Cohen, 2014). It measures physical well-

21
being, physical symptoms, psychological symptoms, existential well-being and support, as well
as overall quality of life (Cohen, 2014). O’Riordan et al. utilized the Minnesota Living with HF
Questionnaire (Rector & Cohn, 1992), which focuses on how HF-specific symptoms can alter
physical and emotional health and day-to-day QOL (Bilbao et al., 2016). Ng & Wong and
O’Riordan et al. were randomized control trials (RCT) utilizing block randomization. Ng &
Wong utilized computer-generated sequences, whereas O’Riordan et al. had a researcher
uninvolved with the current study conduct random assignment to reduce allocation bias (Melnyk
& Fineout-Overholt, 2023). Due to the nature of the interventions, it was impossible to blind the
participants or the personnel involved in the RCTs, which could introduce performance bias
(Melnyk & Fineout-Overholt, 2023). To reduce selection bias, Ng & Wong and O’Riordan et al.
had similar patient characteristics between their study groups (Melnyk & Fineout-Overholt,
2023). Possible limitations to the O’Riordan et al. study are the small sample size of only 30
participants and the low adherence to the intervention, in which, on average, participants
received only five of the six components of the intervention with a range from one to six
components received. This could potentially contribute to why there was not as significant of a
change in the QOL seen in the PC intervention group compared to other studies utilized in this
review.
Evangelista et al. (2012) and Lewin et al. (2017) utilized a prospective case-control study
that compared groups with similar patient characteristics. In the Evangelista et al. study, the
intervention group received a PC consultation and treatment plan based on assessed needs, and
the comparison group were subjects in a previous RCT conducted by the same research group.
Evangelista et al. utilized the Minnesota Living with HF Questionnaire (Rector & Cohn, 1992).
They found significant between-group differences in total QOL (P<0.001), and physical health

22
significantly improved for patients in the PC group over time (Evangelista et al., 2012). Ng &
Wong (2018) found significant improvements in the physical (P=0.011), psychological (P=0.04)
and existential (P=0.027) domains of the McGill Quality of Life Questionnaire (Cohen, 1996)
between groups despite the findings of no significant difference in the total QOL measure
between groups. In their study, Lewin et al. compared their intervention group, which received a
PC consultation, a guide on PC care in HF and non-emergency support, to their control group,
which received usual HF care from a cardiologist. Lewin et al. utilized interview questions as
their measure of QOL and found that the PC group were satisfied with their care; 100% of
subjects appreciated having PC added to the care regime, had improved prognostic awareness
and ACP and appreciated having a holistic care approach, some participants (63%) found it
changed their view of their HF diagnosis, and found it assisted with illness understanding.
Evangelista et al., Lewin et al., and Ng & Wong all sampled patients who were referred or
deemed appropriate for PC by cardiology. Lewin et al. utilized patients in their control group
who were deemed appropriate for PC, but their cardiologist declined to approve of PC. This
could introduce some sampling bias as it is unclear if the same cardiologist oversaw all the
patients in the control group (Melnyk & Fineout-Overholt, 2023); Lewin et al. mention the
cardiologists of the patients in the control group had declined to allow their patients to be in the
intervention group as the patients were not dying and, therefore, not yet needing PC and
subjective feeling of still being able to offer more disease-modifying therapies. This is important
to note as the intention of this research is to determine the benefit of PC on QOL when it is
introduced early in the disease process in HF patients, and this demonstrates the gap in the
knowledge of current PC practices in HF.

23
In their retrospective cohort study, Flint et al. (2017) reviewed previous data collected
from subjects in a study based on symptom management in HF; they utilized latent growth
analysis to divide the subjects into groups based on their disease trajectories. Flint et al. used the
Sense of Peace measure (Steinhauser et al., 2006) to evaluate overall QOL and found significant
improvement in QOL within the first three months of all trajectory groups; however, over time,
the moderate disease trajectory group and the poor disease trajectory group showed little change
in their QOL, with the poor disease trajectory group showing a decline in QOL and the moderate
disease trajectory group plateauing. Flint et al. sampled patients from a previous study on
Patient-Centred Disease Management in HF; all subjects from the previous study were included
to reduce sampling bias (Melnyk & Fineout-Overholt, 2023), and no direct PC intervention was
provided; rather, a comparison of the disease trajectories was made. Arenas Ochoa et al. (2021)
utilized the Twelve Item Short Form Health Survey (Ware et al., 1996) to measure overall QOL.
They found that QOL was significantly lower in subjects in the NECPAL+ (subjects deemed by
their provider to be candidates for PC based on inclusion criteria) (Arenas Ochoa et al., 2021).
Arenas Ochoa et al. conducted a cross-sectional study which compared groups from two
different HF clinics; it does not mention if participants were aware of which comparison group
they were included in, which could introduce some performance bias (Melnyk & FineoutOverholt, 2023). The studies done by Flint et al. and Arenas Ochoa et al. demonstrate that some
groups with specific characteristics may experience more significant benefits from PC than
others.
These findings demonstrate that in all the studies that looked directly at overall QOL, PC
increased their subject’s overall QOL scores (Arenas Ochoa et al., 2021; Evangelista et al., 2012;
Flint et al., 2017; Lewin et al., 2017; Ng & Wong, 2018; O’Riordan et al., 2019). However,

24
some studies showed increases in QOL in both intervention and control groups despite the
control group not receiving PC (Ng & Wong, 2018; O’Riordan et al., 2019). These findings are
summarized in Table 4.

25
Effect on Heart Failure Symptom Burden
With the progression of HF, the burden of symptoms increases, leading to more HFrelated hospital visits and can directly impact QOL. Increased hospitalization due to HF is
associated with greater morbidity and mortality in HF patients (Colucci, 2024) and poorer QOL
measures (Garcia-Soleto et al., 2013). Symptoms that are typical of advancing HF and indicate a
lack of hemodynamic improvement with usual HF therapy include orthopnea, jugular venous
distension, edema, weight gain and respiratory distress (Colucci, 2024). This section will review
the studies that look directly at these symptoms of worsening HF and their burden on QOL.
In two studies, the total HF symptom burden decreased in both the intervention and
control groups (Lewin et al., 2017; Ng & Wong, 2018). Ng & Wong used the Chronic HF
Questionnaire (Guyatt et al., 1989), which quantifies HF-related QOL, dyspnea, fatigue, and
emotional function (American Physical Therapy Association, 2020). They found significant
within-group differences over time in the dyspnea, emotional function, mastery and total
function domains (P<0.017) in the intervention group; there were no between-group differences
over the 12-week study period. To note, at the four-week mark, there were significant betweengroup differences in dyspnea (P=0.02), emotional function (P=0.014), mastery (P=0.019) and
total score (P=0.01) (Ng & Wong, 2018). Lewin et al. (2017) looked at the total number of HFrelated ED visits and hospitalizations, which displayed a significant decrease in ED visits
(P=0.067) between the intervention and control groups but no significant difference between
groups in HF-related hospitalizations (P=0.14). Flint et al. (2017) utilized the Kansas City
Cardiomyopathy Scale (Spertus, 1996), which quantitatively measures the severity of the
patient’s symptoms and how their activities of daily living are affected by their disease (Spertus,
2016). Flint et al. found significant improvement in all disease trajectory groups in the first 3

26
months; the poor disease trajectory group had a decline in HF symptom burden over time. The
markedly improved disease trajectory showed significant improvement in HF symptom burden
over time despite having similar initial scores in QOL measures, palliative symptom burden, and
HF symptom burden (Flint et al., 2017). Arenas Ochoa et al. (2021) utilized the Kansas City
Cardiomyopathy Scale (Spertus, 1996) and found that the NECPAL+ had a more significant HF
symptom burden than compared to the NECPAL- group.
These findings demonstrate that PC can impact the burden of HF-related symptoms on
patients’ QOL (Ng & Wong, 2018) and decrease ED visits for HF-related purposes, and fewer
hospital visits are associated with improved QOL (Lewin et al., 2017). These findings are
summarized in Table 5.

27
Effect on Palliative Symptom Burden
In usual HF care, the main focus is to manage the hemodynamic changes that occur with
worsening cardiovascular functioning (Colucci & Borlaug, 2024). However, patients often
experience symptoms that are not directly associated with cardiac dysfunction. These symptoms
that are typically associated with PC, such as pain, fatigue, depression, and dyspnea, are often
not addressed in the medication regime of usual HF care and can increase the burden on the
patient’s QOL. This section will review the studies that looked at the burden of symptoms that
are addressed in the provision of PC.
In three studies, the total palliative symptom burden improved in both the intervention
and control groups (Evangelista et al., 2012; Ng & Wong, 2018; O’Riordan et al., 2019). Ng &
Wong (2018) found that the intervention group who received usual HF care with PC homecare
and telehealth follow-up displayed better improvement in depression (P=0.01) and dyspnea
(P=0.018) domains at four weeks of their outcome measure and improved tiredness (P<0.017)
and overall palliative symptom burden scores (P=0.015) over time. Evangelista et al. (2012), in
their study, which provided patients with a PC treatment plan based on their assessed needs,
found the PC group had better improvement in fatigue (P<0.001), pain (P=0.044), well-being
(P=0.035), depression (P=.0.29), dyspnea (P=0.008) and nausea (P=0.045). In contrast, the
control group worsened in fatigue (P<0.001) and pain (P=0.044) domains of their outcome
measures and a significant difference in overall palliative symptom burden (Evangelista et al.,
2012). The total palliative symptom burden was measured using the Edmonton Symptom
Assessment Scale (Evangelista et al., 2012; Ng & Wong, 2018) and the Functional Assessment
of Chronic Illness Therapy with PC subscale (O’Riordan et al., 2019). The Edmonton Symptoms
Assessment Scale (Bruera et al., 1991) is a validated tool for assessing pain, fatigue, anxiety,

28
depression, appetite, well-being and shortness of breath, typically addressed with PC (Metis
Nation of Alberta, 2022). The Functional Assessment of Chronic Illness Therapy with PC
subscale (Lyons et al., 2009) measures physical well-being, social and family well-being,
emotional well-being, functional well-being, and symptoms typical of PC (FACIT Group, 2025).
Gonzalez-Jaramillo et al. (2022) utilized qualitative interview questions to determine what
patients found was lacking in their current HF care and how PC could impact this care. They
found that some patients when voicing symptoms such as nausea or pain that are not symptoms
caused by HF itself, felt unheard and unsupported by their cardiology team at the HF clinic.
O’Riordan et al. (2019) evaluated the difference between the control group, which received usual
HF care, and the intervention group, which received PC follow-up via homecare and telehealth.
They found no between-group differences in palliative symptom burden. Flint et al. (2017)
utilized the Symptom Burden Scale to measure palliative symptom burden. They found that the
poor disease trajectory group had a baseline higher palliative symptom burden than the other
disease trajectory groups (Flint et al., 2017).
This demonstrates that the burden of symptoms not typically addressed in usual HF care
and the resulting decreased QOL from this burden can be improved with the addition of PC
(Evangelista et al., 2012; Flint et al., 2017; Gonzalez-Jaramillo et al., 2022; Ng & Wong, 2018).
However, O’Riordan et al., 2019 found no difference between groups on their palliative
symptom burden. These findings are summarized in Table 6.

29

Depression
Depression is an aspect of psychosocial health that correlates to an individual’s QOL. In
addition to significantly affecting QOL, depression in HF reduces adherence to treatment
regimes, decreases adaptation to the disease, and causes disruption in the treatment process
(Moradi et al., 2022), which can impact the QOL by increasing their symptom burden. Although
depression has been measured in some of the other validated tools utilized in other sections, this
section reviews the findings of studies that took a direct measure of depression.
Evangelista et al. (2012) utilized the Patient Health Questionnaire-9 (PHQ-9) (Kroenke et
al., 2001), which is a common questionnaire utilized to quantify the degree to which depression
is affecting the subject’s day-to-day functioning (Kroenke et al., 2001). Evangelista et al. found
that both groups had an improvement in depression scores (P=0.002). However, the PC group

30
had a significantly greater improvement in depression scores (P=0.029) compared to the control
group (Evangelista et al., 2012). Flint et al. (2017) also utilized the PHQ-9 (Kroenke et al., 2001)
to show that the baseline data in the poor disease trajectory group had higher depression scores
than the other disease trajectory groups. Arenas Ochoa et al. (2021) utilized a specific aspect of
the Edmonton Symptoms Scale (Bruera et al., 1991) to assess depression and directly measure it.
The Edmonton Symptoms Scale measures the symptom burden associated with PC (Metis
Nation of Alberta, 2022). Arenas Ochoa et al. show that the NECPAL+ group had higher
depression scores than the NECPAL- group. Gonzalez-Jaramillo (2022) found that patients felt
lonely and hopeless when discharged from the HF clinic without the additional support of PC.
These findings demonstrate that PC can improve feelings of depression in patients with
HF, contributing to improved QOL (Evangelista et al., 2012), and specific groups may benefit
more than others (Arenas Ochoa et al., 2022; Flint et al., 2017). These findings are summarized
in Table 7.

Effective Heart Failure Program
The current outpatient HF programs offered to HF patients are disease-specific and often
do not include access to PC (Boyd et al., 2009). Two studies (Boyd et al., 2009; Gonzalez-

31
Jaramillo et al., 2022) evaluated the current HF programs offered to HF patients and conducted
interviews to find what subjects felt were missing and what could be added to be more effective
to meet HF patient’s needs. The needs focused on aspects of QOL and how PC could address
these.
Boyd et al. (2009) and Gonzalez-Jaramillo et al. (2022) utilized qualitative study designs.
Gonzalez-Jaramillo et al. utilized interviews until they reached data saturation; it is unclear if
this could introduce bias as excluded interviews may have contained conflicting information
inconsistent with their research question. Boyd et al. had eight patients who died during the
study period and do not address how the data that was collected from these patients was utilized
in the study, which could introduce attrition bias (Melnyk & Fineout-Overholt, 2023).
The findings that emerged were essential discussions were missing and there were unmet
care needs (Gonzalez-Jaramillo et al., 2022), prognostic uncertainty (Boyd et al., 2009;
Gonzalez-Jaramillo et al., 2022), there should be key healthcare professionals that coordinate
care utilizing care registries, databases, and electronic prompts, patient-held management plans,
holistic assessment and regular monitoring, implementation of guidelines for care in HF and PC,
better integration of PC into HF care (Boyd et al., 2009) and the recognition of the importance of
PC but also fearing referral due to a lack of understanding of what it entails (Gonzalez-Jaramillo
et al., 2022).
These findings demonstrate that patients enrolled in current HF programs are missing
essential services that align with what PC provides, and it is negatively impacting their QOL.
These findings are summarized in Table 8.

32

Qualitative Findings of Palliative Care Effects on Quality of Life
Interview questioning was utilized to collect data regarding patients’ interpretation of
how PC impacted their QOL, how providers, patients, and families think PC could impact HF
care and patients’ interpretation of their current HF care. From the direct quotations in the
research articles utilized in this review, themes were identified.
One theme that emerged from the quotations on standard HF care was that conversations
on disease prognosis were typically avoided due to uncertainty and the desire to improve the HF
until acute exacerbations occur (Boyd et al., 2009; Gonzalez-Jaramillo et al., 2022). Some
patients found it was much more distressing to have conversations about advanced care planning
during acute exacerbations because they felt it was inappropriate timing when they felt so unwell
and wanted to improve (Gonzalez-Jaramillo et al., 2022). Lewin et al. (2017) found that those
who received aspects of PC felt more supported and at ease with their disease progression;
Gonzalez-Jaramillo et al. (2022) similarly found that patients wanted more psychological
support and more transparency in their diagnosis. Boyd et al. (2009) found that without having
PC specialists involved in care, it is difficult for GPs and nursing staff to provide PC-specific

33
care as it is out of their comfort zone. These findings, based on the direct quotations outlined in
three studies (Boyd et al., 2009; Gonzalez et al., 2022; Lewin et al., 2017), show that both
patients and providers find the addition of PC can be beneficial for patients with HF.
Summary of the Impact of Palliative Care on Heart Failure Patient’s Quality of Life
The interpretation of the studies includes looking directly at the overall QOL of HF patients, the
palliative and HF symptom burden, and depression and how PC can impact this and improve
their QOL. The studies found there was significant improvements within the PC group in QOL
(Evangelista et al., 2012; Lewin et al., 2017; Ng & Wong, 2018), symptom burden (Evangelista
et al., 2012; Lewin et al., 2017; Ng & Wong, 2018), and depression (Evangelista et al., 2012).
This indicates that PC has a benefit on QOL in HF patients.

34
Discussion
The research studies included in this integrative review demonstrate that outpatient PC
can positively impact the QOL of HF patients with varying NYHA classifications. Studies
showed that there was an increase in QOL (Evangelista et al., 2012; Lewin et al., 2017; Ng &
Wong, 2018; O’Riordan et al., 2019), a decrease in HF symptom burden (Lewin et al., 2017; Ng
& Wong, 2018) and palliative symptom burden (Evangelista et al., 2012; Ng & Wong, 2018;
O’Riordan et al., 2019), and depression (Evangelista et al., 2012) in both the PC group and the
control group. However, there were significant improvements within the PC group in QOL
(Evangelista et al., 2012; Lewin et al., 2017; Ng & Wong, 2018), symptom burden (Evangelista
et al., 2012; Lewin et al., 2017; Ng & Wong, 2018), and depression (Evangelista et al., 2012)
over time in these studies demonstrating that PC has a benefit on QOL in HF patients. O’Riordan
et al. (2019) found no significant difference between PC and control groups in QOL measures in
their population, which analyzed 30 subjects with NYHA classifications II-IV; they did not
analyze the within-group data over time, as seen in the other studies included in this review.
Symptoms that are atypical in HF care and more prevalent in PC, such as fatigue, nausea,
dyspnea, pain, and depression, demonstrated significant improvement in the PC group compared
to the control group (Evangelista et al., 2012; Ng & Wong, 2018) and Gonzalez-Jaramillo et al.
(2022) found that subjects in the HF programs felt that complaints of these symptoms seemingly
fell on deaf ears and were not addressed in their regular HF regime. Lewin et al. (2017) found
that those who received PC had significantly fewer ED visits for HF-related symptoms than
those in the control group. The PC intervention improved support and symptom management by
utilizing a PC NP available after hours, increasing access, and providing a key contact person to
coordinate care (Lewin et al., 2017). This indicates that having access to outpatient PC in HF

35
management could reduce healthcare costs and the burden on the ED by improving symptom
control in an outpatient setting. A finding from the study conducted by Boyd et al. (2009) was
that their subjects felt a key person to contact who coordinates their care was missing in the
current HF program; in the Lewin et al. (2017) study, having the PC NP seems to have
remediated that.
Overall, all the subjects in this integrative review that received outpatient PC intervention
showed improvements in QOL, indicating that outpatient PC is a positive adjunct to typical HF
care. This is congruent with current evidence on the benefits of early introduction of PC, as seen
in cancer patients, on overall QOL and symptom burden (Kim et al., 2023; Rodin et al., 2022).
Findings indicate that specific patient populations have better improvements in their
QOL with the initiation of PC than others (Arenas Ochoa et al., 2021; Flint et al.,. 2017). This is
similar to previous research that looked at the impact of the early introduction of PC in cancer
patients suggesting that greater impacts of PC on QOL was noted in patients with more severe
baseline symptoms (Rodin et al, 2022). This suggests that the timing of the PC intervention, the
type of PC intervention, and the PC delivery may impact the degree to which it improves the
patients’ QOL. This is consistent with findings in cancer patients that the timeliness of a PC
referral impacts how PC improves overall QOL and how successful its integration is into a
patient’s care (Hausner et al., 2021). Similar to the studies included in this review, Hausner et al.
(2021) found that the Edmonton Symptom Assessment Scale (Bruera et al., 1991) scores
improved in cancer patients with early PC integration compared to those with later PC
integration. PC should be individualized to the patient to address their needs, whether this is
improving physical symptom burden or the psychosocial burden of HF, to see the most benefit
on QOL.

36
This review expands on the current knowledge that PC positively impacts the QOL of
cancer patients (Hausner et al., 2021; Kim et al., 2023; Ramirez & Velma, 2024; Rodin et al.,
2022) and that it can be implemented as an adjunct to care despite the non-linear disease
progression typical of HF. The implications on future practice and the NP’s role in PC delivery
will be discussed further.
Implications For Practice
The findings of this integrative review demonstrate that PC positively impacts the QOL
of some HF patients, and there is a benefit to introducing PC into their usual HF care. Certain
groups of HF patients could benefit from PC more than others, and it is important to be able to
identify those who could benefit from PC in their HF management. In Arenas Ochoa et al.’s
(2021) study, the NECPAL+ group demonstrated baseline lower QOL, higher HF symptoms
burden and depression, indicating that this is a population that could be a target for effective PC
programs. This group was selected based on the clinical judgement of their healthcare provider.
Flint et al. (2017) found that the marked improvement group showed the most benefit from PC;
this group and the poor trajectory group both had poor baseline health status. The poor trajectory
group had worse QOL at the end of the study period, indicating the importance of targeting this
group for PC to ensure their QOL is maintained through the HF disease process. The reviewed
studies demonstrated within-group improvements in all the aspects of QOL evaluated
(Evangelista et al., 2012; Lewin et al., 2017; Ng & Wong, 2018), showing that if the appropriate
patients are selected, it could significantly benefit their overall QOL.
As Boyd et al. (2009) found, the importance of having a single contact that coordinates
all their specialty care dramatically improves the patient’s adherence and QOL. Primary
healthcare providers play an important role as their patients’ main contact for healthcare. They

37
can be a key contributor to ensuring the appropriate patients receive a referral to PC to maximize
the benefits for the patient. A common misconception is that PC operates independently of HF
therapy and is reserved for end-of-life care (Ramirez & Verma, 2024). Lewin et al. (2017) found
that the cardiologists who declined for their patients to be in the PC group for their study did so
because their subjective feeling was that they could still offer more disease-modifying therapies,
and their patients were not dying. This demonstrates a misunderstanding of the possibility of
offering PC as an adjunct to therapy. Gonzalez-Jaramillo et al. (2022) found that their subjects
feared a PC referral as they felt this indicated that they were dying. The notion that PC is
associated with end-of-life needs to be reframed for the healthcare provider and their patients
(Ramirez & Verma, 2024) as it has demonstrated improved QOL, symptom burden and
psychosocial health for HF patients in various NYHA classifications. PCPs are in a unique
position to provide holistic care and offer education and support on PC to their HF patients to
ensure a better understanding of the benefits of integrated PC (Boyd et al., 2009). Early
discussions around PC can be comforting for patients as it helps them better understand their
diagnosis and prognosis and have appropriate conversations about ACP before they are in an
acute exacerbation with increased uncertainty (Boyd et al., 2009; Lewin et al., 2017; GonzalezJaramillo et al., 2022).
The PCP is in an ideal position to provide individualized patient-centred care that
addresses the patient’s need for improved QOL. PCPs often have the closest relationship with
these patients. Having frequent conversations with HF patients regarding how the disease
process is impacting their QOL can help gauge whether they could benefit from the introduction
of PC. Reducing the stigma around PC and its association with end-of-life can help ensure HF
patients get PC introduced into their care regime and optimize their QOL.

38
Nurse Practitioners Roles in Palliative Care Provision
While this project focuses on how early PC introduction can benefit the QOL of patients
with HF, I would be remiss not to mention the NP’s role in improving this. These suggestions
can be applied to any PCP, but since this project is part of the process of working towards a
MSc-FNP, the focus will be on NPs.
Lewin et al. (2017) utilized an NP with specialized knowledge in PC who was available
for contact at any time. This significantly improved the management and delivery of PC,
improving the patient’s QOL and reducing the need for ED visits and hospitalization (Lewin et
al., 2017). Since Lewin et al.’s research in 2017, the role of the NP has evolved, which may have
more significant impacts on the patient’s QOL with a PC NP if this research was repeated. NPs
have increased autonomy in their provision of care and can specialize in population-specific
fields such as PC (Boehning & Punsalan, 2023). This further increases access to PC, particularly
in underserved populations (Boehning & Punsalan, 2023).
Besides having NPs specialized in PC, NPs can also benefit their HF patients in the
primary care setting by utilizing aspects of PC. This can be accomplished by taking time to have
open and honest conversations with patients early in the disease’s progress, given the uncertain
prognosis and progression, so patients do not have unrealistic expectations (Jones et al., 2019).
Utilizing the BC Guidelines (2023a), which outline cases when a PC referral is recommended.
Early discussions on what a good QOL looks like to each individual patient and focusing on
their treatment goals during the disease process (Boyd et al., 2009).
PC is commonly provided in the inpatient setting even though HF patients spend most of
their time out in the community (DeGroot et al., 2020); this is typically due to a lack of access or
resources in the community. This gap could be filled with PC-trained NPs who can work within

39
a team of PC specialists to expand the provision of care into the outpatient setting, whether in a
patient’s home or an outpatient clinic. I have spoken with Dr. Brenda Millar, who is a PC
physician operating in the sea-to-sky area in BC; she explained that a PC-specialized NP would
greatly expand the provision of PC services in the area, allowing for more home visits and
significantly decrease the need for hospitalization in her patient panel. This would also allow for
the coverage of patients with life-limiting conditions beyond cancer, such as HF, which the PC
team currently has limited capacity for.
This integrative review demonstrates that outpatient PC positively impacts the QOL of
HF patients if it is provided in an individualized manner to meet the patient’s needs and is
integrated at the correct time for that individual. The PCP plays an integral role in discussing the
disease progression of HF and how PC can positively impact their QOL. Having these
conversations helps to assess the patient’s readiness to integrate PC into their care regime and
can improve the success rate that PC will positively impact the patient’s QOL. These
conversations can also help reduce the association of PC with death and dying for both patients
and providers, so more patients are open to integrating PC into the care regime.
Limitations
The limitations associated with this integrative review stem from the ability of a single
researcher to comb through the vast amount of research associated with PC. Initially, when
brainstorming topics for this research project, I did not focus on a single condition and was
looking at the effect of PC on any non-malignant condition. The vast amount of research on PC
in non-malignant illnesses was too much for a single researcher to tackle. The choice was made
to focus on outpatient PC in HF, which significantly reduced the amount of research;
consequently, it reduced the level of research available to include in the study. This could impact

40
the quality of evidence used in this review as only two of the studies were RCT, which is leveltwo evidence (Melnyk & Fineout-Overholt, 2023).
Another limitation was with the studies included in this integrative review and their
implication on the research question. Although this review aimed to answer whether QOL was
improved early after diagnosis of HF, studies that had subjects considered NYHA classification
III/IV were included as NYHA classification is dynamic through the disease process. It is
difficult to determine whether individuals included in these studies were recently diagnosed or
had HF management long-term prior to entering the study. One study (Arenas Ochoa et al.,
2021) had inclusion criteria that their subjects must have attended at least two appointments at
the HF clinic before being included in the study, indicating that these individuals may have had a
recent diagnosis. However, the data on the length of time after HF diagnosis is not summarized
in the studies included in this review. This may affect whether the data found in this integrative
review can be implied as an early introduction to PC.
Sources of Bias
I work in an ED in a rural setting with limited PC available, so the PC team focuses on
malignant illnesses as that is all they have the capacity for. The ED is often inundated with HF
patients who do not have a sufficient understanding of their illness and could greatly benefit
from PC to help manage atypical symptoms. Evidence supporting the greater need for PC could
introduce funding for more PC providers, which could benefit me in the future if I pursue a
career as a PC NP. Ihis knowledge could have acted as a source of researcher of bias to motivate
the findings of this review to reflect this (Melnyk & Fineout-Overholt, 2023).

41
Future Research
This integrative review could stimulate further research in the topic area of PC in HF
patients. Future studies could look directly at rural sites, as this review did not factor in the
locations of the study. As the focus for the implications for practice was on how NPs and PCPs
could approach implementing PC for their HF patients, future studies could review PC
interventions provided in rural settings as they tend to have less access to specialties and rely
more on PCPs to provide these services. Future research could delve into data on the PCP and
patients’ experience of providing and receiving PC through primary care and its effect on QOL
in HR patients.
There is room for research on defining the patients that could benefit from PC the most.
As demonstrated in the studies by Flint et al. (2017) and Arenas Ochoa et al. (2022), certain
groups would benefit more than others from PC. More research into the characteristics of an
appropriate PC candidate can help guide policy and create guidelines for PC referral in HF. This
could be executed by measuring the change in overall QOL over time in a population of HF
patients who all receive PC and investigating how their characteristics differ. It could help
implicate the creation of a PC readiness scale for HF patients that can help PCPs determine if
their patients are appropriate for PC referral.

42
Conclusion
HF is a life-limiting condition with a non-linear prognosis, which is challenging to
convey to patients (Colucci, 2024). The acute phases of HF can cause significant distress for
patients, increasing the frequency of ED visits and hospital utilization (Jones et al., 2019). The
rate of HF in Canada continues to increase, and mortality and hospitalizations due to HF remain
high despite medical advances in treatment plans (Colucci, 2023). This can impact a patient’s
QOL and increase their morbidity and mortality (Jones et al., 2019). QOL encompasses an
individual's physical, functional, psychosocial, and social aspects of their life (Fallowfield,
2009). PC is a specialty that focuses on treating and improving a patient’s physical, emotional,
psychosocial, and spiritual health (Corliss, 2023), which aligns directly with a person’s QOL.
PC can have a positive impact on the lives of HF patients and improve their QOL
(Arenas Ochoa et al., 2022; Boyd et al., 2009; Evangelista et al., 2012; Flint et al., 2017;
Gonzalez-Jaramillo et al., 2022; Lewin et al., 2017; Ng & Wong, 2019), not all patients with HF
will benefit from PC and it is up to the discretion of the PCP to determine if someone is
appropriate for a HF referral (Arenas Ochoa et al., 2022; Flint et al., 2017; O’Riordan et al.,
2019). This could be an area where more research is completed to help guide future policy on
what characteristics a person has that make them an appropriate PC candidate. A patient does not
need to be near end-of-life to benefit from PC; early introduction can help patients to feel more
supported, have less fear, and have a better understanding of their prognosis (Boyd et al., 2009;
Lewin et al., 2017) despite the lability of the disease process. PCPs are in a unique situation to
provide holistic, supportive care that encompasses the domains of PC, including the physical,
emotional, psychosocial and spiritual issues that accompany chronic illnesses such as HF
(Corliss, 2023). Based on the clinical presentation, they can determine who could benefit from

43
early PC (Arenas Ochoa et al., 2022) and effectively provide PC alongside life-prolonging care
(Lewin et al., 2017; Ramirez & Verma, 2024). It is important to break the stigma and fear around
PC being reserved for end-of-life and utilize it to its full potential in providing supportive
symptom management to our complex, chronically ill patients. Patients value open and honest
communication regarding their illness, providing them all the information to help them make an
informed decision and discussing what is most important to the patients (Boyd et al., 2007;
Gonzalez-Jaramillo et al., 2022; Lewin et al., 2017). Implementing improved guidelines for PC
referral and PC education can help PCPs provide better holistic care to patients with life-limiting
illnesses and ensure their QOL does not suffer.

44
References
Allen, L.A. (2025). Palliative care for advanced heart failure: Decision support and management
of symptoms. In S.A. Hunt, & R.S. Morrison (Ed.), UpToDate. Retrieved March 23,
2025. https://www.uptodate.com/contents/palliative-care-for-advanced-heart-failuredecision-support-and-management-ofsymptoms?search=what%20happens%20when%20heart%20failure%20medications%20
are%20no%20longer%20effective&source=search_result&selectedTitle=6%7E150&usa
ge_type=default&display_rank=6
American Heart Association. (2023). Classes and stages of heart failure. American Heart
Association. Retrieved on January 6, 2024. https://www.heart.org/en/health-topics/heartfailure/what-is-heart-failure/classes-of-heart-failure
American Physical Therapy Association. (2020). Chronic heart failure questionnaire. American
Physical Therapy Association. https://www.apta.org/patient-care/evidence-basedpractice-resources/test-measures/chronic-heart-failure-questionnaire-chq-chfq
Arenas Ochoa, L.F., Gonzalez-Jaramillo, V., Saldarriaga, C., Lemos, M., Krikorian, A., Jairo
Vargas, J., Gomez-Batiste, X., Gonzalez-Jaramillo, N., Eychmuller, S. (2012).
Prevalence and characteristics of patients with heart failure needing palliative care. BMC
Palliative Care, 20(184), (1-10). https://doi.org/10.1186/s12904-021-00850-y
Artinian, N.T., Magna, M., Christian, W., Lange, Patricia. (2002). What do patients know about
their heart failure? Applied Nursing Research, 15(4), 200-208.
https://doi.org/10.1053/apnr.2002.35959
Askoxylakis, V., Thieke, C., Pleger, S.T., Most, P., Tanner, J., Lindel, K., Katus, H.A., Debus,
J., Bischof, M. (2010). Long-term survival of cancer patients compared to heart failure

45
and stroke: A systematic review. BMC Cancer, 10(105), 2-8.
http://www.biomedcentral.com/1471-2407/10/105
Averbuch, T., Mohamed, M.O., Islam, S., Defilippis, E.M., Breathett, K., Alkhouli, M.A.,
Michos, E.D., Martin, G.P., Kontopantelli, E., Mamas, M.A., Van Spall, H.G.C. (2022).
The association between socioeconomic status, sex, race/ethnicity and in-hospital
mortality among patients hospitalized for heart failure. Journal of Cardiac Failure,
28(5), 697-709. doi: 101016/j.cardfail.2021.09.012
Beernaert, K., Deliens, L., De Vlemink, A., Devroey, D., Pardon, K., Van den Block, L., Cohen,
J. (2017). Early identification of palliative care needs by family physicians: A qualitative
study of barriers and facilitators from perspective of family physicians, community
nurses, and patients. Palliative Medicine, 28(6), 480-490. doi:
10.11770269216314522318
Bilbao, A., Escobar, A., Garcia-Perez, L., Navarro, G., Quiros, R. (2016). The Minnesota living
with heart failure questionnaire: Comparison of different factor structures. Health Quality
Life Outcome 14(23). doi: 10.1186/s12955-016-0425p-7
Boehning, A.P., Punsalan, L.D. (2023). Advanced practice registered nurse roles. StatPearls.
https://www.ncbi.nlm.nih.gov/books/NBK589698/
Boyd, K.J., Worth, A., Kendall, M., Pratt, R., Hockley, J., Denvir, M., Murray, S.A. (2009).
Making sure services deliver for people with advanced heart failure: A longitudinal
qualitative study of patients, family carers, and health professionals. Palliative Medicine,
23(8), 767–776. doi: 10.1177/0269216309346541

46
Bruera, E., Kuehn, N., Miller, M.J., Selmser, P., Macmillan, K. (1991). The Edmonton symptom
assessment system (ESAS): A simple method for assessment of palliative care patients.
Journal of PPalliative Care 7(2), 6-9. PMID 1714502
Cohen, S.R. (1996). Existential well-being is an important determinant of quality of life:
Evidence from the McGill quality of life questionnaire. Journal of the American Cancer
Society 77(3), 576-586. https://doi.org/10.1002/(SICI)10970142(19960201)77:3<576::AID-CNCR22>3.0.CO;2-0
Cohen, S.R. (2014). McGill quality of life questionnaire. In: A.C. Michalos (Ed.), Encyclopedia
of Quality of Life and Well-Being Research. Springer. https://doi.org/10.1007/978-94007-0753-5_1749
Colucci, W.S. (2022). Predictors of survival in heart failure with reduced ejection fraction. In
S.S. Gottlieb and A.S. Jaffe (Eds.), UpToDate. Retrieved on January 5, 2024.
https://www.uptodate.com/contents/predictors-of-survival-in-heart-failure-with-reducedejectionfraction?search=new%20york%20heart%20association%20class&sectionRank=1&usage
_type=default&anchor=H3&source=machineLearning&selectedTitle=1%7E150&display
_rank=1#H3
Colucci, W.S. (2023). Prognosis of heart failure. In S.S. Gottlieb (Ed.), UpToDate. Retrieved:
January 2, 2024. https://www.uptodate.com/contents/prognosis-of-heartfailure?search=Heart%20failure%20survival%20rates&source=search_result&selectedTi
tle=2%7E150&usage_type=default&display_rank=1#H1
Colucci, W.S., Borlaug, B.A. (2022). Heart failure: Clinical manifestations and diagnosis in
adults. In S.S. Gottlieb (Ed.), UpToDate. Retrieved January 5, 2024.

47
https://www.uptodate.com/contents/heart-failure-clinical-manifestations-and-diagnosisinadults?search=heart%20failure%20definition&source=search_result&selectedTitle=1%7
E150&usage_type=default&display_rank=1
Corliss, J. (2023, December 1). What is palliative care for heart failure? It involves specialized
clinicians who provide additional care and support for patients and families in
collaboration with a cardiologist. Harvard Heart Letter.
https://www.health.harvard.edu/heart-health/what-is-palliative-care-for-heart-failure
Covidence systematic review software. (2024). Veritas Health Innovation, Melbourne, Australia.
Retrieved from www.covidence.org.
Crimmins, R.M., Elliott, L., Absher, D.T. (2020). Palliative care in a death-denying culture:
Exploring barriers to timely palliative efforts for heart failure patients in the primary care
setting. American Journal of Hospital and Palliative Medicine 38(1). doi:
10.1177/1049909120920545
DeGroot, L., Koirala, B., Pavlovic, N., Nelson, K., Allen, J., Davidson, P., Abshire, M. (2020).
Outpatient palliative care in heart failure: An integrative review. Journal of Palliative
Medicine, 23(9), 1257–1269. doi: 10.1089/jpm.2020.0031
Enguidanos, S., Cardenas, V., Wenceslao, M., Hoe, D., Meja, K., Lomeli, S., Rahman, A.
(2020). Health care provider barriers to patient referral to palliative care. American
Journal of Hospice and Palliative Medicine, 38(9). doi: 10.1177/1049909120973200
Evangelista, L.S., Lombardo, D.L., Malik, S., Ballard-Hernandez, J., Motie, M., Liao, S. (2012).
Examining the effects of an outpatient palliative care consultation on symptom burden,

48
depression, and quality of life in patient with symptomatic heart failure. Journal of
Cardiac Failure, 18(12), 894-899. http://dx.doi.org/10.1016/j.cardfail.2012.10.019
FACIT Group. (2025). Functional assessment of chronic illness therapy – Palliative care. FACIT
Group. https://www.facit.org/measures/facit-pal
Fallowfield, L. (2009). What is quality of life? Health Economics, 2, 1–8.
https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=b5eb4bdf371b1752a3
a9bc5a323a350c41809840
Flint, K.M., Schmiege, S.J., Allen, L.A., Fendler, T.J., Rumsfield, J., Bekelman, D. (2017).
Health status trajectories among outpatients with heart failure. Journal of Pain and
Symptom Management, 53(2), 224-231.
http://dx.doi.org/10.1016/j.jpainsymman.2016.08.018
Garcia-Soleto, A., Parraza-Diez, N., Aizpuru-Barandiaran, F., Aros-Borau, F., Mendoza-Ruiz de
Zuazu, H., Martin-Gudino, M.J., Regalado de los Cobos, J. (2013). Comparative study of
quality of life after hospital-at-home or in-patient admission for acute decompensation of
chronic heart failure. World Journal of Cardiovascular Diseases, 3(1). doi:
10.4236/wjcd.2013.31A025
Gonzalez-Jaramillo, V., Maessen, M., Luethi, N., Guyer, J., Hunziker, L., Eychmuller, S.,
Zambrano, S.C. (2022). Unmet needs in patients with heart failure: The importance of
palliative care in a heart failure clinic. Frontier in Cardiovascular Medicine, 9, 1–10. doi:
10.3389/fcvm.2022.866794
Government of British Columbia. (2023a). Heart failure: Diagnosis and management. BC
Guidelines. Retrieved on January 6, 2025.

49
https://www2.gov.bc.ca/gov/content/health/practitioner-professional-resources/bcguidelines/heart-failure-chronic#Definition
Government of British Columbia. (2023b). Medical assistance in dying (MAID) statistical report
2023 quarter two April 1-June 30, 2023. Government of British Columbia. Retrieved on
January 6, 2025. https://www2.gov.bc.ca/assets/gov/health/accessing-health-care/homecommunity-care/bc-medical-assistance-in-dying-statistical-report-2023-q2.pdf
Guyatt, G.H., Nogradi, S., Halcrow, S., Singer, J., Sullivan, M.J., Fallen, E.L. (1989).
Developmental and testing of a new measure of health status for clinical trials in heart
failure. Journal of General Internal Medicine, 4(2), 101-107. doi: 10.1007/BF02602348
Hausner, D., Tricou, C., Mathews, J., Wadhwa, D., Pope, A., Swami, N., Hannon, B., Rodin, G.,
Krzyzanowska, M.K., Le, L.W., Zimmermann, C. (2021). Timing of palliative care
referral before and after evidence from trials supporting early palliative care. The
Oncologist 26(4), 332-340. doi: 10.1002/onco.13625
Heo, S., Lennie, T.A., Okoli, C., Moser, D.K. (2009). Quality of life in patients with heart
failure: Ask the patients. Heart and Lung, 38(2), 100-108. doi:
10.1016/j.hrtlng.2008.04.002
Jones, N.R., Roalfe, A.K., Adoki, I., Hobbs, F.D.R., Taylor, C.J. (2019). Survival of patients
with chronic heart failure in the community: A systematic review and meta-analysis.
European Journal of Heart Failure, 21, 1306–1325. doi: 10.1002/ejhf.1594
Kim, C.A., Lelond, S., Daeninck, P.J., Rabbani, R., Lix, L., McClement, S., Chochinov, H.M.,
Goldenberg, B.A. (2023). The impact of early palliative care on the quality of life in
patients with advanced pancreatic cancer: The IMPERATIVE case-crossover study.
Supportive Care in Cancer 31(250). https://doi.org/10.1007/s00520-023-07709-3

50
Kroenke, K., Spitzer, R.L., Williams, J.B. (2001). The PHQ-9: Validity of a brief depression
severity measure. Journal of General Internal Medicine 12(9). doi: 10.1046/j.15251497.2001.016009606.x.
Lewin, W.H., Cheung, W., Norvath, N., Haberman, S., Patel, A., Sullivan, D. (2017). Supportive
cardiology: Moving palliative care upstream for patients living with advanced heart
failure. Journal of Palliative Medicine, 20(10), 1112–1119. doi: 10.1089/jpm.2016.0317
Lyons, K.D., Bakitas, M., Hegel, M.T., Hanscom, B., Hull, J., Ahles, T.A. (2009). Reliability
and validity of the functional assessment of chronicillness theraoy-palliative care
(FACIT-Pal) scale. Journal of Pain Symptom Management 37(1). doi:
10.1016/j.jpainsymman.2007.12.015
Melilo, K.D. (2020). A step-by-step guide to conducting an integrative review. In C. Toronto, R.
Remington, (Eds.) Springer.
Melnyk, B. M., & Fine-Out-Overholt, E. (2023). Evidence-based practice nursing & healthcare:
A guide to best practice (5th ed.). Wolters Kluwer.
Metis Nation of Alberta. (2022). Edmonton symptom assessment scale (ESAS) tool. First
Nations, Inuit and Metis Program. https://albertametis.com/app/uploads/2022/01/ESASTool_V4.pdf
Mohanan, S., Parameswaran, N. (2022). FINER criteria – What does it mean? CosmoDerma,
2(115), 1-3. https://cosmoderma.org/finer-criteria-what-does-it-mean/
Moradi, M., Doostkami, M., Bahnamfar, N., Rafiemanesh, H., Behzadmehr, R. (2022). Global
prevalence of depression among heart failure patients: A systematic review and metaanalysis. Current Problems in Cardiology, 47(6). doi: 10.1016/j.cpcardiol.2021.100848

51
Namukwaya, E., Murray, S.A., Downing, J., Leng, M., Grant, L. ‘I think my body has become
addicted to those tablets.’ Chronic heart failure patients’ understanding of and beliefs
about their illness and its treatment: A qualitative longitudinal study from Uganda. PLoS
One, 12(9). https://doi.org/10.1371/journal.pone.0182876
Ng, A.Y.M., Wong, F.K.Y. (2018). Effects of home-based palliative heart failure program on
quality of life, symptom burden, satisfaction and caregiver burden: A randomized
controlled trial. Journal of Pain and Symptom Management, 55(1), 1-11.
http://dx.doi.org/10.1016/j.jpainsymman.2017.07.047
Nowels, D., Jones, J., Nowels, C.T., Matlock, D. (2016). Perspectives of primary care providers
towards palliative care for their patients. Journal of American Board Family Medicine,
29(6), 748–758. doi: 10.3122/jabfm.2016.06.160054
O’Riordan, D.L., Rathfon, M.A., Joseph, D.M., Hawgood, J., Rabow, M.W., Dracup, K.A., De
Marco, T., Pantilat, S.Z. (2019). Feasibility of implementing a palliative care intervention
for people with heart failure: Learning from a pilot randomized clinical trial. Journal of
Palliative Medicine, 22(12), 1583–1588. doi: 10.1089/jpm.2018.0633
Poon, S., Leis, B., Lambert, L., Macfarlane, K., Anderson, K., Blais, C., Demers, C., Ezekowitz,
J.A., Hawkins, N.M., Lee, D.S., Moe, G., Sandhu, R.K., Virani, S.A., Wilton, S.,
Zieroth, S., McKelvie, R. (2022). The state of heart failure care in Canada: Minimal
improvement in readmissions over time despite an increased number of evidence-based
therapies. Canadian Journal of Cardiology Open, 4, 667–675.
https://doi.org/10.1016/j.cjco.2022.04.011

52
Ramanayake, R.P.J.C., Dilanka, G.V.A., Premasiri, L.W.S.S. (2016). Palliative care: Role of
family physicians. Journal of Family Medicine and Primary Care, 5(2), 234-237. doi:
10.4103/2249-4863.192356
Ramirez, C.T., Verma, R.K. (2024). Early palliative care improves patients and caregiver quality
of life. Clinical Journal of Oncology Nursing, 28(5), 496–501. doi:
10.1188/24.CJON.496-501
Rector, T.S., Cohn, J.N. (1992). Assessment of patient outcome with the Minnesota living with
heart failure questionnaire: Reliability and validity during a randomized, double-blind,
placebo-controlled trial of Pimobendan. American Heart Journal 124, 1017-1025. doi:
10.1016/0002-8703(92)90986-6
Rodin, R., Swami, N., Pope, A., Hui, D., Hannon, B., Le, L.W., Zimmermann, C. (2022). Impact
of early palliative care according to baseline symptom severity: Secondary analysis of a
cluster-randomized controlled trial in patients with advanced cancer. Cancer Medicine,
11(8), 1869-1878. https://doi-org.prxy.lib.unbc.ca/10.1002/cam4.4565
Saveski, D., Kok, M., Poon, S., Rojas-Fernandez, C., Virani, S.A., Honos, G., McKelvie, R.
(2025). The Canadian heart failure (CAN-HF) registry: A Canadian multicentre
retrospective study of outpatients with heart failure. CJC Open, 7(1), 1–9. doi:
10.1016/j.cjco.2024.09.014
Spertus, J. (2016). Medical device development tool qualifications decision summary for Kansas
City cardiomyopathy questionnaire (KCCQ). Saint Luke’s Mid America Heart Institute.
https://www.fda.gov/media/108301/download

53
Statistics Canada. (2025). Deaths and age-specific mortality rates, by selected grouped causes.
Statistics Canada. Retrieved March 21, 2025.
https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1310039201
Steinhauser K.E., Voils, C.I., Clipp, E.C. (2006). “Are you at peace?” One item to probe
spiritual concerns at end of life. Archive of Internal Medicine 166(1), 101-105. doi:
10.1001/archinte.166.1.101
Ware, J., Kosinki, M., Keller, S.D. (1996) A 12-item short-form health survey: Construction of
scales and preliminary tests of reliability and validity. Med Care 34(3), 220-233. doi:
10.1097/00005650-199603000-00003
World Health Organization. (2025). Palliative care. World Health Organization.
https://www.who.int/news-room/fact-sheets/detail/palliative-care

54

Appendix A: Search Terms and PRISMA Diagram
Date of
Search
10/2024

Search Terms and Boolean Phrases:
Database
CINAHL

10/2024

Medline

10/2024

APA PsycInfo

11/2024

Google Scholar

Search Terms utilized

MH “Palliative Care” or MH “Palliative Medicine” or “palliative care”
AND “early introduction” or “early referral” or “early initiation” or time*
AND MH “Heart Failure” or “heart failure” or CHF AND MH “Quality
of Life” or MH “Psychological Well-Being” or “quality of life” or “wellbeing” or “life satisfaction” AND MH “Home Health Care” or
community or outpatient or home*
MH “Time-to-treatment” or MH “Palliative care” or MH “Palliative
Medicine” or MH “Hospice and Palliative Care Nursing” or “palliative
care” AND MH “Heart Failure+” or CHF or “heart failure or HF AND
MH “Quality of life” or MH “Value of Life” or “quality of life” or wellbeing” or “life satisfaction” AND “early introduction” or “early referral”
or “early initiation” or timely or timeliness AND MH “Home Care
Services” or community or outpatient or home*
DE “Palliative Care” or DE “Health Care Delivery” or DE “Spiritual
Care” or “palliative care” AND “early introduction” or “early referral” or
“early initiation” or time* AND “heart failure” AND DE “Quality of
Life” or DE “Well Being” or DE “Life satisfaction” or “quality of life” or
“well-being” or “life satisfaction AND DE “Community Treatment” or
DE “Outpatient Treatment” or DE “Home Care” or community or
outpatient or home*
heart failure and palliative care and outpatient and early intervention
Filtered search articles since 2020

Articles
Retrieved
24

25

10

17,700

55
PRISMA Diagram

Studies from databases/registers (n = 61)

Identification

Bra3
Google Scholar (n = 2)

https://www.who.int/news-room/factsheets/detail/palliative-care from other sources (n
=)
Citation searching (n = )
Grey literature (n = )

References removed (n = 7)
Duplicates identified manually (n = 0)
Duplicates identified by Covidence (n = 7)
Marked as ineligible by automation tools (n = 0)
Other reasons (n = )

Studies screened (n = 54)

Studies excluded (n = 39)

Studies sought for retrieval (n = 15)

Studies not retrieved (n = 0)

Studies assessed for eligibility (n = 15)
Studies excluded (n = 7)
Wrong setting (n = 1)
Wrong outcomes (n = 2)
Wrong comparator (n = 1)
Wrong intervention (n = 1)
Does not include final data (n = 2)

Studies included in review (n = 8)

Included studies ongoing (n = 0)
Studies awaiting classification (n = 0)

56
Appendix B: Quality Assessment

Study ID

Ng 2018

Sequence Generation

Allocation
concealment

Judgement,
Comments &
Quotes

Judgement,
Comments &
Quotes

Low
‘the site manager, who
had no
knowledge of the
subjects, opened a
sealed opaque
envelope with a
computer-generated
sequence of
random numbers
inside for assignment.
Block randomization
with a block size of 6
was adopted’

Low
‘After the baseline
data were collected
and the consent forms
signed, the site
manager, who had no
knowledge of the
subjects, opened a
sealed opaque
envelope with a
computer-generated
sequence of random
numbers inside for
assignment.’

Blinding of
participants and
personnel for All
outcomes
Judgement,
Comments &
Quotes

High
‘Blinding of the
interventionist and
participants was
impossible due to the
nature of the
intervention.
Only the data collector
was blinded to the
group
assignment.’

Blinding of
outcome
assessors for
All outcomes
Judgement,
Comments &
Quotes

Low
‘Only the data
collector was
blinded to the
group
assignment’

Incomplete outcome
data for All outcomes
Judgement, Comments
&
Quotes
Low
‘The data were analyzed
using the Predictive
Analysis SoftWare
(PASW) Statistics 18.
Descriptive statistics
were used to present the
demographic and
clinical characteristics.
Repeated-measures
analysis of variance was
used to examine the
effects of the HPHF
intervention group and
the control group on
continuous outcome
variables that are
normally distributed.
The Sidak correction for
multiple corrections was
applied
in examining the withingroup difference in
preventing alpha
inflation. All statistical
differences were twotailed, with an alpha set
at 0.05. If the normal
distribution principle
was violated, the
Friedman and Mann-

Selective outcome reporting

Other sources
of bias

Judgement, Comments,
& Quotes

Judgement,
Comments &
Quotes

Low
“There were significant
improvements in the physical (P
= 0.011), psychological (P =
0.04), and existential (P =
0.027) domains between the
intervention and control groups
over time. No significant
differences were
noted in the support domain and
global QOL items.
Overall, the total MQOL score
reached a significant difference
when the two groups were
compared over time (P = 0.016),
and a significant group time
interaction was also detected (P
= 0.032) CHQ-C results show
that a significant
difference was noted between
the intervention and
control groups at four weeks in
the aspects of dyspnea
(P = 0.02), emotional function
(P = 0.014), mastery (P =
0.019), and the total score (P =
0.01). There
was no between-group effect
noted at 12 weeks for
any group. However, there was
a significant within-

Low
‘The work
described in this
paper was fully
supported by a
grant from the
Research Grants
Council of the
Hong Kong
Special
Administrative
Region,
China (RGC Ref
No 549212). The
authors declare
no conflicts of
interest’

57
Whitney U tests were
applied for betweengroup comparison over
time. The Wilcoxon
signed
ranks test was used for
within-group analysis
over
time.54 Bonferroni
correction was
employed to protect
against the inflated risk
of a Type I error due to
multiple comparisons,
and the defined value of
the overall alpha level
was divided by the
number of pairs being
compared. All analyses
were conducted on an
intention-to-treat basis.
Missing data were
imputed by the multiple
imputation method.
Effect size was
estimated by calculating
partial eta squared h2p ,
where the small,
moderate, and large
effect sizes were
defined as 0.01, 0.06,
and 0.14, respectively.’

group difference (P < 0.017),
that is when the group
was compared with itself over
time, for the intervention group
throughout the 12 weeks in the
aspects
of dyspnea, fatigue, mastery,
and in the total score
Edmonton Symptom
Assessment Scale showed no
significant between-group
symptom improvement at 12
weeks. However, the
intervention group had better
improvement than the
control group at four weeks in
two symptoms depression, P =
0.01 and shortness of breath P =
0.018). When the groups were
compared on their own over
time, the intervention group
showed improvement in
tiredness and total score (P <
0.017) throughout the 12 weeks,
but there was no such
improvement in
the control group (Table 4).
There was no significant
difference, either between
groups or within groups in terms
of the functional status (Table
5). The intervention group had
significantly higher satisfaction
than
the control group at both four (P
= 0.001) and
12 weeks (P = 0.001), and there
was a significant increase over
time in the intervention group (P
= 0.015)’

58

O'Riordan
2019

Low
Patients were
randomized within
blocks of six to
minimize
potential bias and
confounding.
A member of the
research
team with no contact
with the study patients
conducted a
random assignment
procedure to prevent
any bias in the allocation to groups.1

Lewin 2017

High: Placed in
control group if
cardiologist did not
approve PC consult,
unclear as to why the
cardiologist did not
approve, or if all the
members in the
control group were
under the care of the
same cardiologist.
‘Nonrandomized
prospective study
comparing
outcomes over a sixmonth study period
for patients receiving
PC, in addition to

Low
‘A member of the
research team with no
contact with the study
patients conducted a
random assignment
procedure to prevent
any bias in the allocation to groups.’

Low: Clinical nurse
specialist is selecting
based on outlined
criteria
‘Our clinical nurse
specialist met weekly
with the cardiac team
to identify eligible
patients from the
inpatient setting’

High:
This was not
mentioned in the
article, however, due
to the nature of the
interventions it is not
possible to blind the
personnel or the
participants to the
treatment

Low
‘The
statistician was
blinded to
group coding’

Low
‘This approach adjusts
for sources of variation
and correlation among
repeated measures
within a subject.
Further, the analysis of
repeated measurements
ensures subjects with missing data
can still be included. ‘

Low
Not applicable

Unclear:
Unknown if
this resident
was involved
in the
provision of
the
intervention or
not.
‘A medical
resident
completed a
chart review
for the purpose
of comparing
pre-/post-data
outcomes.
Only

Low
‘All patients in the
intervention group who
were discharged to longterm care or
home were referred to
follow-up with
outpatient PC. Nine out
of the 14 (64%) patients
received outpatient PC,
with an average of 4.5
visits (range 1-12 visits)
per patient throughout
the study period. The
majority of patients (7
out of 9, 78%) received
same-day joint visits
with the PC and HF

Low
‘Patients in both groups reported
improvements in all outcomes
except depression across the
three assessment periods: heartrelated QoL ( p = 0.001), QoL (
p = 0.03), anxiety (p = 0.003),
severe pain ( p = 0.05), dyspnea
( p = 0.03), and depression ( p =
0.15) (Table 4). There were no
differences between the two
groups over the course of the
study. Patient satisfaction with
the care they received was
documented at the initial
assessment as well as during
three- and six-month follow-up
assessments. We found no
difference in satisfaction with
care between the two study
groups at any of
these three assessment periods’
Low
‘There was no baseline
difference between intervention
and
control group ACP
documentation (v2(1, n = 35) =
0.68, p = 0.41). However, there
was an increase in ACP
documentation for the
intervention group throughout
the study period
(v2(1, n = 35) = 21.39, p <
0.001). ACP increased from
40% to 100% for patients in the
intervention group (Table 3).
More patients in the intervention
group elected DNR code status
after receiving PC consultation

Unclear:
could influence
researchers to
encourage
palliative care
for increased
funding of
palliative care in
the future
‘Funding by
palliative care
research centre’

Low
‘No competing
financial
interests exist.’

59
standard cardiac care
versus standard
cardiac care alone.’

Evangelista
2012

Low:
Not an RCT so not
applicable
‘This prospective
case-control study was
conducted at a single
university-affiliated
medical center.
Participants were
recruited
from the inpatient
setting during an
episode of acute HF
exacerbation through
HF provider referrals;
The goal of the

information
obtained from
our hospital’s
electronic
medical record
was used.

High
‘In addition,
participants were not
individually
randomized but rather
matched on
sociodemographic
variables and
functional class to
optimize our ability
to compare the
effects of providing
PC services to
patients with
symptomatic HF.
Although nearly all

Low:
Not applicable due to
the nature of the study

Unclear:
This is not
mentioned in
the article.

teams. Only two patients
requested an outpatient
PC visit on a different
day than their scheduled
HF appointment.’

Low
‘From March 1, 2008, to
July 30, 2008 (5
months), 57patients with
symptomatic HF were
approached, of whom42
consented (73.6%
recruitment); 9 (60%)
were not interested in
participating, and 6
(40%) cited time
requirements. Thirty-six
(85.7%) of the 42
patients who signed
informed consent came
for a PC consultation.

(30% pre vs. 80% post). ACP
documentation did not change
throughout the study period for
the control group. Only 5 out of
15 charts (33%) had a
documented code status, and
only 1 of these patients elected
DNR code status. When
examining ED visits, we
conducted a Group
(Intervention, Control) X Time
(Pre-Treatment, Post-Treatment)
repeated-measures ANOVA. No
Group X Time interaction
emerged, F(1,33) = 1.29, p =
0.27. Interestingly, there was a
main effect for Time, F(1,33) =
18.57, p < 0.001, suggesting that
across groups there was a
general decrease in ED
utilization throughout the study
period. The main effect for
Group was nonsignificant,
F(1,33) = 0.95, p = 0.34.
Low
‘Table 2 presents the baseline
and 3-month follow-up data
for the variables of interest.
Patients in both groups
demonstrated significantly
lower levels of symptom
(P < .001) and depression (P =
.002) and better emotional
health (P = .001) and overall
QOL (P < .001). Physical
health improved for patients in
the PC group worsened
for patients in comparative
group. Over time, group
differences were statistically

60
matching was to
include subjects in the
comparison group,
balanced by sex, age,
race, and New York
Heart Association
(NYHA) functional
class, to increase our
ability to
compare them with
intervention subjects
regarding the study
measures’

Flint 2017

Low
‘We used data from
The Patient-Centered
Disease Management
for Heart Failure trial
(PCDM), which
enrolled 392
outpatients from four
Veterans Affairs
Medical Centers with
a new or existing
diagnosis of heart
failure with preserved
or reduced ejection
fraction, any New
York Heart
Association class, and
a Kansas City
Cardiomyopathy
Questionnaire
(KCCQ) overall
summary score <60
Briefly, the PCDM

baseline
characteristics in the
2 groups were
similar, we can not be
sure that the
differences in
symptom burden, depression, and QOL at
follow-up were
indeed related to the
PC intervention

Low
‘Because the PCDM
intervention did not
influence health
status, this analysis
includes all trial
participants,
irrespective of
randomization’

Three participants
decided to withdraw
from the study: 2 moved
away, and 1patient was
lost to follow-up before
the PC consultation.’

Low:
This is not addressed
in the article but is not
applicable in this
study

Unclear:
This is not
addressed in
the article

Low
‘Missing data occurring
as a result of attrition
over
time were addressed by
estimating the growth
models with all available
data using full
information maximum
likelihood estimation;
the small amount of
missing data
on the predictors and
covariates was
addressed using multiple
imputation.’

significant in all outcomes.
Participants who received a PC
consultation were more likely to
show improvements in fatigue
(P < .001), pain (P = .044), wellbeing (P = .035), depression (P
= .029), dyspnea (P = .008), and
nausea (P = .045) than
participants in the matched
control group (Table 3).
Furthermore, a greater proportion of patients in the
matched control group showed
worsening symptoms of fatigue
(31% vs 11%; P < .001)
and pain (28% vs 10%%; P =
.044).’
Low
‘One of the trajectories had
few patients (5%); therefore, we
only examined predictors of
trajectory membership between
the two major trajectories. The
two most common trajectories
(moderate health status
and poor health status) showed
initial improvement
from baseline to three months,
followed by little change
throughout the rest of the
follow-up period. These
trajectories differed primarily in
their baseline values, not their
change over time. The marked
improvement trajectory
consisted of a small group of
patients whose health status was
initially very poor but improved
substantially and progressively
throughout the year.’

Low
‘The views
expressed in this
article are those
of the authors
and do not
necessarily
reflect the
position
or policy of the
Department of
Veterans Affairs
or the U.S.
government. The
authors declare
no conflicts of
interest.’

61
trial randomized
participants to a
collaborative care
model of symptom
management or usual
care’

Arenas
Ochoa
2021

Low
Not Applicable

Unclear
It is not mentioned
whether the patients
were aware they were
in the NECPAL+ or
NECPAL - group

GonzalezJaramillo
2022

Low
‘we transcribed and
thematically analyzed
the longest interviews,
as they were the most
content- rich because
participants engaged
in deeper discussions
with the interviewer.
Before transcription,
we heard all
interviews and noticed
that the shortest ones

Low
‘We then included
interviews until we
reached data
saturation, that is, the
point at which the
inclusion of
additional interviews
would have not added
substantial new
information to the
analysis and the
resulting themes and

Low
Not Applicable due to
the nature of the study

Low
‘In the
invitation
package that
was mailed to
patients, we
mentioned that
the project
aimed to
evaluate the
performance of
a questionnaire
to assess the

Low
A researcher
scored the
answers from
the SF-12 and
the KCCQ
instruments.
The attending
cardiologist
filled out the
NECPAL tool

Low
‘VGJ, a female
physician who
was
completing a
PhD on PC in
HF at the time
of the study,
performed all
analyses with
support
from SCZ, a
female

Low
Cardiologists also considered
four other patients to need PC
despite those patients having a –
NECPAL due to a negative
surprise question (yes, the
physician would be surprised by
patient death). The prevalence
of PC needs in patients at
NYHA III/IV was two times
fold the prevalence in patients at
NYHA I/II (77% vs 36%). The
prevalence of PC among
patients older than 70 years was
almost two times fold the prevalence in patients under or equal
to 70 years (57% vs 30%).
There was no difference
between PC needs of men and
women, nor across LVEF
categories

Low
The authors have
no conflicts of
interest to
declare that are
relevant to the
content of this
article

Low
‘Participants were in general satisfied
with the treatment and information
received at the ambulatory HF clinic,
however, upon further questioning,
they would often report several unmet
needs. We therefore identified three
ambivalences as main themes:
(I)”feeling well-informed but missing
essential discussions”, (II)
“although feeling mostly satisfied with
care, remaining with
unmet care needs”, and (III) “fearing a

Low
‘This project was
supported by
Stiftung
Lindenhof Bern,
Teaching
and Research
Fund (grant
numbers: 20-03F and WRO013). The
funder had no
role on the study

Low
Of the 184 patients who
met the inclusion
criteria, 178 accepted
participation, 89 from
each HF clinic

Unclear
‘Of the 70 interviews
undertaken for the
validation study, we
reached data saturation
at
31 interviews. The
interviews included in
this study lasted 31 min
in average (range: 24-48
min).’

62
did not allow for a
comprehensive
understanding of
participants’
experience of
symptoms and of their
unmet needs and
therefore decided that
not all could be
analyzed in the depth
that thematic analysis
requires.’

Boyd 2009

Low
‘Purposive sampling
enabled recruitment of
interview
participants who
reflected the local
epidemiology of
advanced heart failure
(New York Heart
Association
[NYHA] Class III/IV)
and were using the
spectrum of services
available’

subthemes (9). Of the
70 interviews
undertaken for the
validation study, we
reached data
saturation at 31
interviews. The
interviews included
in this study lasted 31
min in average
(range: 24–48 min)’

Low:
Not applicable

needs of
patients with
HF and to
improve the
quality of care
delivered to this
population.’

Low:
Not applicable

psychologist
with expertise
in qualitative
methods and
PC research.
VGJ and SCZ
coded
independently
one of the
interviews and
compared all
initial codes, to
finetune the coding
process.’
Low:
Not applicable
‘The interview
and focus
group data
were
recorded,
transcribed and
analysed
thematically
with
the aid of
NVivo.
Interview
triads for
individual
cases
were analysed
longitudinally
and constant
comparison
within and
across cases
ensured that
the thematic

referral to palliative care
but acknowledging its importance”

Unclear:
unclear how the 8
participants who died
during the study could
alter the results
‘The 18 male and 17
female patients had a
mean age of 76 years
(range 48-91). Nine
lived alone, 17 with a
spouse or partner, two in
sheltered housing and
two in care homes. Most
had multiple comorbidities and
experienced the
numerous physical and
psychosocial difficulties
well documented in
these patients and
families.11 Services
with regular input or a
key role were heart
failure nurses (17),
cardiologist (2), elderly

Low
‘Working with the spectrum of
participants who contributed to the
interviews and focus groups enabled us
to identify key areas for service
improvement and relate these to
published recommendations.
Consensus-based criteria were thought
to be helpful in enabling professionals
to recognize when a palliative care
approach to care that focuses on
quality of life as much as a reduction in
morbidity has become appropriate.

design, data
collection,
analysis,
or interpretation
of the results.’

Low
‘The study was
funded by the
Policy Research
Programme
as part of the
Department of
Health/British
Heart
Foundation Heart
Failure Research
Initiative.
Ethics approval
for the study was
obtained from
Lothian
Research Ethics
Committee and
R& D approvals
were
obtained from
the local Health
Boards.
The authors have
no competing

63
analysis
represented all
perspectives.19
Transcripts
were
coded to
include
anticipated and
unforeseen
themes.’

medicine (5) and
primary care (11); three
patients had specialist
palliative care
involvement (Appendix
I). Eight patients died
during the study’

interests to
declare.’