Referral and Use of Heart Failure Clinics: What Factors
Are Related to Use?
Shannon Gravely, PhD,a,b,cLiane Ginsburg, PhD,aDonna E. Stewart, MD, FRCPC,b,d
Susanna Mak, MD, PhD, FRCPC,b,d,eand Sherry L. Grace, PhD;a-don behalf of the
Cardiac Rehabilitation Care Continuity Through Automatic Referral Evaluation (CRCARE)
aYork University, Faculty of Health, Toronto, Ontario, Canada
bUniversity Health Network, Women’s Health Program, Toronto, Ontario, Canada
cCardiac Rehabilitation and Secondary Prevention Program, Toronto Rehabilitation Institute, Toronto, Ontario, Canada
dUniversity of Toronto, Faculty of Medicine, Toronto, Ontario, Canada
eMount Sinai Hospital, Department of Cardiology, Toronto, Ontario, Canada
Background: Heart failure (HF) clinics have been shown to reduce hos-
survival, and care costs. This study investigated the rates of referral and
use of HF clinics and examined factors related to program use.
Methods: This study represents a secondary analysis of a larger pro-
spective cohort study conducted in Ontario. In hospital, 474 HF inpa-
tients from 11 hospitals across Ontario completed a survey that ex-
amined predisposing, enabling, and need factors affecting HF clinic
assessed referral to and use of HF clinics.
Results: Forty-one patients (15.2%) self-reported referral, and 35
(13%) self-reported attending an HF clinic. Generalized estimating
equations showed that factors related to greater program use were
having an HF clinic at the site of hospital recruitment (odds ratio [OR]
? 8.40; P ? 0.04), referral to other disease management programs
(OR ? 4.87; P ? 0.04), higher education (OR ? 4.61; P ? 0.02), lower
stress (OR ? 0.93; P ? 0.03), and lower functional status (OR ? 0.97;
P ? 0.03).
Introduction : Il a été démontré que les cliniques d’insuffisance car-
ment une incidence favorable sur la qualité de vie, la survie et les coûts
associés aux soins. Cette étude avait pour but d’évaluer le taux
d’orientation des patients vers des cliniques d’IC et le taux de fréquenta-
tion, et d’examiner les facteurs liés à l’utilisation du programme.
Méthodes : Cette étude représente une analyse secondaire d’une
plus vaste étude de cohortes prospectives menée en Ontario. À
l’hôpital, 474 patients hospitalisés ayant une IC et provenant de 11
hôpitaux de l’Ontario ont rempli un sondage qui portait sur les facteurs
prédisposants, les facteurs habilitants et les besoins influant sur la
fréquentation d’une clinique d’IC. Puis, 1 an plus tard, 271 patients
ayant une IC ont rempli un sondage postal qui évaluait l’orientation
des patients vers des cliniques d’IC et la fréquentation.
Résultats : Quarante et un (41) patients (15,2 %) ont rapporté eux-
mêmes l’orientation vers une clinique d’IC, et 35 (13 %) ont rapporté
être allés dans une clinique d’IC. Les équations d’estimation générali
sées ont montré que les facteurs liés à une plus grande utilisation du pro-
There is a high prevalence and incidence of heart failure
(HF) globally,1,2and it is associated with high mortality,
morbidity, and cost of care.3,4The course of HF is marked
by frequent exacerbations that lead to hospital readmissions.
The reasons for high admission rates are multifactorial and
include both patient and health care provider factors.5At
the patient level, readmissions result not only from clinical
factors, but from behavioural factors such as nonadherence
to self-management recommendations. Moreover, given the
complexities in managing HF, research shows that posthos-
pitalization medical care is not always optimal.6,7
During the past decade, HF management programs have
been established to address these challenges in HF outpatient
care.8In particular, multidisciplinary outpatient HF clinics
may provide patient education on ways to manage HF and
recognize HF-specific symptoms, medication review and dose
Received for publication June 21, 2011. Accepted November 29, 2011.
Health, York University, Bethune 368, 4700 Keele Street, Toronto, Ontario
See page 487 for disclosure information.
Canadian Journal of Cardiology 28 (2012) 483–489
0828-282X/$ – see front matter © 2012 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.
titration, risk-factor management, prescription of a home-
based exercise schedule, monitoring of therapy compliance,
family-centred education, interprovider communication, and
Use of outpatient HF management programs is shown to
reduce morbidity, mortality, and health care costs. For exam-
ple, a meta-analysis of randomized controlled trials demon-
strated that multidisciplinary HF disease management pro-
grams (DMPs) are associated with a 26% reduction in HF
hospitalizations, a 19% reduction in all-cause hospitalization,
and a 25% reduction in mortality.10Based on this evidence,
Canadian,11American,12,13and European14guidelines pro-
mote referral to such clinics for patients with a recent HF hos-
pitalization or at high risk of clinical deterioration. Despite
these guidelines, however, the paucity of research that is avail-
able suggests that few patients access these programs.7,15-17
To investigate access to HF clinics, we applied an estab-
lished framework18in the current study. The objectives of the
and use and (2) examine health-system and patient factors re-
lated to HF clinic use.
Design and procedure
This study represents a secondary analysis of a larger prospec-
ics approval for human research was obtained from all participat-
ing hospitals, which included 11 acute care hospitals in Ontario,
were tertiary (onsite catheterization laboratory and revasculariza-
(100%) were located in urban centres.
Between 2006 and 2008, medically stable consecutive cor-
onary artery disease and/or HF inpatients were approached by
and cardiac surgery and catheterization floors during business
hours. After the patients consented, medical record data were ex-
that assessed factors affecting health care use according to Ander-
recruitment, participants were mailed a second follow-up survey
assessing self-reported HF clinic referral and use.
Inpatients with diastolic or systolic HF as a primary or sec-
ondary diagnosis were selected. Ascertainment of HF was de-
termined by (1) HF diagnosis indicated in the inpatient hospi-
tal medical record, (2) New York Heart Association (NYHA)
(3) patient self-report of an HF diagnosis.
Of the 873 HF inpatients approached, 474 consented to
participate in the study (176 declined participation, and 223
patients were excluded). Reasons for exclusion were based on
criteria for the larger study.19
Independent variables. Environmental (ie, health system)
and individual (ie, patient-level) factors affecting HF clinic use
were identified from previous studies that have evaluated HF
clinic7,16,21and CR participation.22,23The factors were ex-
tracted from medical records or assessed by patient self-report
with psychometrically validated scales available. A summary of
constructs is presented in Supplementary Figure S1.
Environmental (health-system) factors. In the present study, health-
system variables included hospital type (academic or other),
whether the hospital recruitment site had an established HF
by counting the number of services other than an HF clinic to
which the patient indicated a referral. These services included
CR, diabetes education, stroke rehabilitation, smoking cessa-
tion clinics, occupational or physical therapy, or consultation
with a registered dietitian.
Patient-level variables. AccordingtoAndersen’sframework,18(1)
characteristics predisposing to use, (2) characteristics enabling
use, and (3) need-related factors were assessed as outlined be-
low. The relevant factors were assessed in the baseline survey
unless otherwise indicated.
Predisposing factors. Sociodemographic characteristics assessed
tural background, work status, level of education, and gross
annual family income were assessed by self-report. The Beck
Depression Inventory-II (BDI-II) was administered to assess
Enabling factors. The sociodemographic characteristics of rural-
care site), marital status (yes or no), and living arrangements
(alone or with family) were assessed via self-report.
The Enhancing Recovery in Coronary Heart Disease Pa-
tients (ENRICHD) Social Support Inventory (ESSI)25was
Conclusion: Similar to previous research, only one-seventh of HF
patients were referred to and used an HF clinic. Both patient-level
and health-system factors were related to HF clinic use. Given the
benefits of HF clinics, more research examining how equitable ac-
cess can be increased is needed. Also, the appropriateness and
cost repercussions of use of multiple disease management pro-
grams should be investigated.
gramme étaient une clinique d’IC sur le site de l’hôpital (ratiod’incidence
de prise en charge des maladies (RIA ? 4,87; P ? 0,04), une instruction
supérieure (RIA ? 4,61; P ? 0,02), un stress niveau de plus faible (RIA ?
0,93; P ? 0,03) et un état fonctionnel plus faible (RIA ? 0,97; P ? 0,03).
Conclusion : De façon similaire aux recherches précédentes, seule-
ment un septième des patients ayant une IC ont été orientés vers une
clinique d’IC et l’ont fréquentée. Les facteurs liés aux patients et les
facteurs liés au système de santé ont été associés à la fréquentation
de la clinique d’IC. Étant donné les avantages des cliniques d’IC, da-
vantage de recherches examinant comment l’accessibilité équitable
peut être améliorée sont nécessaires. Aussi, la pertinence et la réper-
de nombreuses maladies devraient être évaluées.
484Canadian Journal of Cardiology
Volume 28 2012
used to measure social support. The Perceived Stress Scale
(PSS)26was used to examine the degree to which situations in
one’s life are appraised as stressful.
Need factors. Clinical indicators of objective need that were ex-
tracted from clinical medical records included cardiac risk fac-
tors (yes or no: hypertension, hyperlipidemia, diabetes, smok-
ing history, family history of heart disease, and overweight or
obesity), left ventricular ejection fraction (greater or less than
40%), and NYHA class (I-IV). Body mass index, cardiac his-
tory (yes or no), and comorbid conditions (count) were ex-
tracted from clinical medical records and where absent were
supplemented with self-report data.
to determine functional capacity as this index provides a valid
estimate of functional capacity in patients with HF.28The
Physical Activity Scale for the Elderly (PASE)29was used to
assess physical activity.
Finally, the patient’s use of health care services was also
assessed as an indicator of need for disease management pro-
gramming and was self-reported by participants 1 year post
recruitment. It included whether a patient (1) had been to see
his or her (a) general practitioner and (b) heart specialist, (2)
had visited an emergency department for symptoms related to
the heart, and (3) had been admitted to a hospital for HF
and/or another coronary event or procedure in the 12 months
was measured by self-report forced-choice questions in the
1-year–follow-up survey. Patients reported whether they were
referred to an HF clinic and, if “yes,” reported the site of use if
they attended (yes or no). Telephone calls were made to all
participants to verify referral and use of HF clinics specifically.
In the initial stages of analysis, a descriptive examination of
self-reported HF clinic referral and use was conducted. A ?
the 2 variables.
tient-level predisposing, enabling, and need factors related to
HF clinic use (yes or no), using chi-square and t tests where
able selection for an adjusted model based on theoretical (ie,
Andersen’s model) and empirical (P ? 0.1) criteria.
Finally, generalized estimating equations with a binary lo-
gistic model were used to examine factors associated with HF
clinic use in order to control for patient clustering within hos-
pital recruitment sites. SPSS Version 17.0 (SPSS Inc, Chicago,
IL) was used for all analyses.30
plemental Figure S2. Of the 474 consenting HF participants,
the final cohort consisted of 271 patients who completed the
1-year assessment reporting referral and use of HF clinics (120
patients were deemed ineligible and 83 declined). Specific rea-
sons for loss to follow-up that were considered to deem partic-
ipants ineligible for HF clinic participation were as follows:
moved and could not be located (n ? 64; 53.3%), deceased
(n ? 46; 38.3%), too ill (n ? 3; 2.5%), dementia (n ? 1;
0.8%), and “other” (n ? 6; 5.1%). Supplemental Table S1
displays participant characteristics by retention status.
Self-reported referral and use of an HF clinic
denoted as “missing.” Of the 270 participants, 41 (15.2%)
self-reported referral to an HF clinic, and 35 (13%) reported
using the program (85% of those referred) at 1 of 16 sites. The
concordance between referral to and use of an HF clinic was
92% (Cohen’s ?).
Factors related to HF clinic use
Generalized estimating equations were computed to predict
HF clinic use. The variable left ventricular ejection fraction ?
40% was not included because of a large amount of missing
data. Thus, the DASI was forced into the model as an alternate
2 health system–level factors were significantly related to HF
than an HF clinic. With regard to patient-level factors, 1 each
of predisposing, enabling, and need factors was related to HF
stress, and lower functional status were associated with greater
HF clinic use.
Research has shown that multidisciplinary outpatient HF
clinics can support management of this clinical syndrome10,31
and reduce rehospitalizations.16,32Little is known, however,
HF clinic, representing less than one-seventh of the study sam-
ple. The extremely high concordance (92%) between referral
and use suggests that referred patients adhere to these recom-
Despite the established benefits of HF clinics, evidence
shows that referral to,15and subsequent enrollment in,16HF
clinics is low. The findings in this study of rates of referral and
enrollment are congruent with the current literature. First,
with regards to referral, the largest and most comprehensive
With the Guidelines (GWTG) program, 11,150 (19.2%) pa-
tients were referred to an HF DMP, a rate similar to the 15%
referral rate in the current study.
With regard to enrollment, 1 Canadian retrospective study
showed that among 8,731 HF patients from the Improving
Cardiovascular Outcomes in Nova Scotia (ICONS) provincial
registry,1611% of HF patients enrolled in 1 of 4 HF clinics.
Similar to Gharacholou et al.15and current study, all patients
discharged with an HF diagnosis were followed in order to
assess HF clinic enrollment.
Given the demonstrated benefits of these services, the rates
of referral and enrollment in the current study are discourag-
ingly low. It could be argued that capacity is insufficient and
thus, for cost-effectiveness, only patients with frequent read-
Gravely et al.
Access to Heart Failure Clinics
ateness then of this rate of use could be supported if need
factors were significantly related to HF clinic use. However,
number of emergency department visits was unrelated to use.
The appropriateness of patients accessing HF clinics is also not
supported in that the presence of risk factors, comorbidities,
and other health care visits were all unrelated to use. This find-
ing is similar to the CR literature, in which most studies have
of prognostic indicators.22,33However, patients with lower
ejection fraction and functional status were more likely to use
HF clinics. It has been demonstrated that HF patients with
lower functional capacity are at higher risk of major cardiovas-
cular events and reduced survival.28Although more research is
most in need34are assured timely access to DMPs and perhaps
that primary care–based or integrated DMPs be considered to
address the care gap.
use, we tested predisposing, enabling, and need factors affect-
ing HF clinic use. With regard to these patient-level factors, 3
were found to be related to HF clinic use—higher education,
lower stress, and lower functional status. With regard to the
Table 1. Bivariate analyses of factors associated with HF clinic use, according to Andersen’s model (N ? 270*)
HF clinic use
Age, mean years (SD)
Sex, female, n (%)
White ethnocultural background, n (%)
Education, completed high school, n (%)
Retired, n (%)
Family income ? CAD$50,000, n (%)
Depression (BDI-II), mean (SD)
Rural living, n (%)
Married, n (%)
Stress (PSS), mean (SD)
Social support (ESSI), mean (SD)
Living with family, n (%)
Index cardiac condition or procedure, n (%)
Diabetes, n (%)
Hypertension, n (%)
Dyslipidemia, n (%)
Smoker, current, n (%)
BMI, mean (SD)
LVEF ? 40%, n (%)
NYHA class III-IV, n (%)
History of cardiac disease, n (%)
Comorbid conditions, mean count (SD)
Functional status (DASI), mean (SD)
Physical activity (PASE), mean (SD)
Number of visits to a heart specialist in the past year, mean (SD)
Number of visits to a GP in the past year, mean (SD)
ED admission for cardiac care in the past year, n (%)
Hospital cardiac readmission in the past year, n (%)
Health system–level factors†
Referral to other DMPs, n (%)
Referral to CR, n (%)
Referral to a diabetes outpatient clinic, n (%)
Referral to OT or PT, n (%)
Referral to a stroke clinic, n (%)
Referral to a dietitian, n (%)
Referral to a smoking program, n (%)
BDI, Beck Depression Inventory; BMI, body mass index; CABG, coronary artery bypass graft; CR, cardiac rehabilitation; DASI, Duke Activity Status Index;
DMPs, disease management programs; ED, emergency department; ESSI, ENRICHD Social Support Inventory; GP, general practitioner; HF, heart failure; LVEF,
left ventricular ejection fraction; MI, myocardial infarction; NYHA, New York Heart Association; OT, occupational therapy; PASE, Physical Activity Scale for the
Elderly; PCI, percutaneous coronary intervention; PSS, Perceived Stress Scale; PT, physical therapy; SD, standard deviation.
*HF clinic data is missing for 1 participant and could not be verified.
†Hospital-level variables were included in the multivariate analysis only, because bivariate analyses do not take into account the clustering of patients within
486Canadian Journal of Cardiology
Volume 28 2012
to use an outpatient HF clinic compared to those with lower
education. This finding is consistent with the broader cardiac
literature, which shows more affluent or better educated pa-
tients are more likely than those with lower education to access
studies have shown that socioeconomically disadvantaged pa-
tients are less likely to modify lifestyle risk behaviours and have
in the current study regarding the association of education to
ever,16,21other sociodemographic factors, such as age, sex, and
ethnocultural background, were unrelated to HF clinic use.
Health system factors related to HF clinic use
Two health system factors were shown to be related to
greater HF clinic use: referral to other DMPs and presence of
the former, patients who received a referral to other DMPs
were nearly 5 times more likely to use an HF clinic. In fact, of
the patients who used an HF clinic, over 90% had received a
referral to other DMPs. There may be several reasons for such
a finding. First, the patients who are using multiple outpatient
programs may be in greater clinical need of such care. Second,
DMP programs refer among their services based on patients’
needs. Thus once a patient is referred to 1 service, the patient
smoking) and comorbidities (eg, diabetes). Similarly, Gharac-
holou et al.15also found that more patients who were referred
to an HF DMP were also referred to CR (20.7%), compared
with those not referred (3.9%). Third, patients who use HF
clinics may be informed health care consumers who request
referral to multiple DMPs. Fourth, patients may be appropri-
ately using different DMPs over time as they live with their
chronic cardiac condition.
established program at the hospital site of patient recruitment.
Patients recruited from a site with an HF clinic were 8 times
more likely to use these programs. Indeed this was the most
important factor in determining which patients used an HF
clinic. The availability or supply of health services is shown to
over, it is likely that having an HF clinic on-site is related to
greater awareness of the benefits of such services by physicians
where they receive care, have equitable access to HF clinics, be
it in person or through alternative models of care (eg, home
care, telephone support, or remote monitoring).
The findings presented herein should be interpreted with
caution, most notably because of design, measurement, and
generalizability. With regard to design, this was a secondary
analysis of a larger prospective study on access to CR. The
inclusion-exclusion criteria were designed for the larger study
Moreover, because of the nature of the larger study, many pa-
tients were receiving care on hospital wards with CR referral
systems. Physicians may have deemed a referral to an HF clinic
redundant if the patient was going to receive care in a CR
assess an exhaustive list of patient and health system–level fac-
tors. For example, the type of HF (systolic or diastolic), the
symptoms, and the nature of HF (acute decompensation or
many variables were ascertained via self-report, which raises
questions of bias. Chiefly, HF diagnosis could have been ascer-
tained by patient self-report, which has uncertain validity. Ad-
ditionally, HF clinic referral and use were assessed by self-re-
port only. Although HF clinic use was not verified with the
clinic sites, there is evidence that supports the “almost-perfect”
congruence between self-report and DMP-report data.40
not be generalizable as a result of selection and retention bias.
In conclusion, one-seventh of HF patients were referred to
and used an HF clinic. Over 90% of patients who reported
tional status were related to greater HF clinic use. At the health
ization and referral to other DMPs were related to greater HF
clinic use. Given the benefits of HF clinics, policies to achieve
more equitable access based on need should be considered.
We gratefully acknowledge the study coinvestigators and
recruiters for efforts in patient accrual.
This study was funded by Canadian Institutes of Health
grant HOA-80676. With regard to personnel support, S.L.G.
by the Ontario Women’s Health Council/CIHR Institute of
Gender and Health.
The authors have no conflicts of interest to disclose.
Table 2. Generalized estimating equation analysis of factors
associated with HF clinic use
OR95% CIP value
Education (completed high
school or greater)
Stress (greater) (PSS)*
Functional status (greater)
Health system-level factors
HF clinic at the site of hospital
Referral to other DMPs (yes)
Hospital type (academic)
CABG, coronary artery bypass graft; CI, confidence interval; DASI, Duke
Activity Status Index; DMPs, disease management programs; HF, heart fail-
ure; OR, odds ratio; PSS, Perceived Stress Scale.
Gravely et al.
Access to Heart Failure Clinics
2. Young JB. The global epidemiology of heart failure. Med Clin North Am
3. Lee DS, Johansen H, Gong Y, Hall RE, Tu JV, Cox JL. Regional out-
comes of heart failure in Canada. Can J Cardiol 2004;20:599-607.
4. Medical Advisory Secretariat, Ministry of Health and Long-Term Care.
evidence-based analysis. Ontario, Canada: Ontario Health Technology
Assessment Series, 2009.
5. Tsuyuki RT, McKelvie RS, Arnold JM, et al. Acute precipitants of con-
gestive heart failure exacerbations. Arch Intern Med 2001;161:2337-42.
6. Berkowitz R, Blank LJ, Powell SK. Strategies to reduce hospitalization
in the management of heart failure. Lippincotts Case Manag 2005;
7. Ehrmann Feldman D, Ducharme A, Frenette M, et al. Factors related to
time to admission to specialized multidisciplinary clinics in patients with
congestive heart failure. Can J Cardiol 2009;25:e347-52.
8. McAlister FA, Teo KK, Taher M, et al. Insights into the contemporary
Heart J 1999;138:87-94.
9. Malcom J, Arnold O, Howlett JG, et al. Canadian Cardiovascular Society
consensus conference guidelines on heart failure—2008 update: Best
practices for the transition of care of heart failure patients, and the recog-
nition, investigation and treatment of cardiomyopathies. Can J Cardiol
10. McAlister FA, Stewart S, Ferrua S, McMurray JJ. Multidisciplinary strat-
egies for the management of heart failure patients at high risk for admis-
sion: a systematic review of randomized trials. J Am Coll Cardiol 2004;
11. Arnold JM, Liu P, Demers C, et al. Canadian Cardiovascular Society
consensus conference recommendations on heart failure 2006: Diagnosis
and management. Can J Cardiol 2006;22:23-45.
12. Jessup M, Abraham WT, Casey DE, et al. ACCF/AHA guidelines for the
ican College of Cardiology Foundation/American Heart Association task
force on practice guidelines: developed in collaboration with the Interna-
tional Society for Heart and Lung Transplantation. Circulation 2009;
13. Heart Failure Society of America. Executive summary: HFSA 2006 com-
prehensive heart failure practice guideline. J Card Fail 2006;12:10-38.
14. Dickstein K, Cohen-Solal A, Filippatos G, et al. ESC guidelines for the
diagnosis and treatment of acute and chronic heart failure 2008: the Task
Force for the Diagnosis and Treatment of Acute and Chronic Heart Fail-
ure 2008 of the European Society of Cardiology. Developed in collabora-
tion with the Heart Failure Association of the ESC (HFA) and endorsed
by the European Society of Intensive Care Medicine (ESICM). Eur
J Heart Fail 2008;10:933-89.
15. Gharacholou SM, Hellkamp AS, Hernandez AF, et al. Use and predictors
of heart failure disease management referral in patients hospitalized with
heart failure: insights from the Get With the Guidelines program. J Card
16. Howlett JG, Mann OE, Baillie R, et al. Heart failure clinics are associated
with clinical benefit in both tertiary and community care settings: data
from the Improving Cardiovascular Outcomes in Nova Scotia (ICONS)
registry. Can J Cardiol 2009;25:e306-11.
17. Jurgens CY. Somatic awareness, uncertainty, and delay in care-seeking in
acute heart failure. Res Nurs Health 2006;29:74-86.
does it matter? J Health Soc Behav 1995;36:1-10.
19. Grace SL, Russell KL, Reid RD, et al. Effect of cardiac rehabilitation
Intern Med 2011;171:235-41.
20. Criteria Committee of the New York Heart Association, ed. Nomencla-
Boston, MA: Little, Brown, 1994.
21. Houde S, Feldman DE, Pilote L, et al. Are there sex-related differences in
specialized, multidisciplinary congestive heart failure clinics? Can J Car-
22. Grace SL, Gravely-Witte S, Brual, J, et al. Contribution of patient and
level study. Eur J Cardiovasc Prev Rehabil 2008;15:548-56.
23. Grace SL, Evindar A, Kung TN, Scholey PE, Stewart DE. Automatic
referral to cardiac rehabilitation. Med Care 2004;42:661-9.
24. Beck AT, Steer RA, Brown GK. Manual for the Beck Depression Inven-
tory-II. San Antonio, TX: Psychological Corporation, 1996.
Support Inventory. J Cardiopulm Rehabil 2003;23:398-403.
26. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived
stress. J Health Soc Behav 1983;24:385-96.
27. Hlatky MA, Boineau RE, Higginbotham MB, et al. A brief self-adminis-
tered questionnaire to determine functional capacity (the Duke Activity
Status Index). Am J Cardiol 1989;64:651-4.
levels in chronic heart failure secondary to ischemic or idiopathic dilated
cardiomyopathy. Am J Cardiol 2009;103:73-5.
29. Washburn RA, Smith KW, Jette AM, Janney CA. The Physical Activity
Scale for the Elderly (PASE): development and evaluation. J Clin Epide-
30. SPSS for Windows [computer program]. Version 17.0. Chicago, IL, 2008.
31. Hauptman PJ, Rich MW, Heidenreich PA, et al. The heart failure clinic:
32. Gustafsson F, Arnold J. Heart failure clinics and outpatient management:
review of the evidence and call for quality assurance. Eur Heart J 2004;
33. Cooper AF, Jackson G, Weinman J, Horne R. Factors associated with
cardiac rehabilitation attendance: a systematic review of the literature.
Clin Rehabil 2002;16:541-52.
heart failure clinics: discrepancies between health-related quality of life and
function in men and women. Can J Cardiol 2011;27:382-7.
35. Alter DA, Iron K, Austin PC, Naylor CD; SESAMI Study Group. Socio-
of acute myocardial infarction in Canada. JAMA 2004;291:1100-7.
tion or coronary bypass surgery. Circulation 2007;116:1653-62.
488Canadian Journal of Cardiology
Volume 28 2012
37. Chan RH, Gordon NF, Chong A, Alter DA; Socio-Economic and Acute Download full-text
lifestyle behavior modifications among survivors of acute myocardial in-
farction. Am J Cardiol 2008;102:1583-8.
38. Alter DA, Venkatesh V, Chong A; SESAMI Study Group. Evaluating the
performance of the Global Registry of Acute Coronary Events risk-adjust-
ment index across socioeconomic strata among patients discharged from the
hospital after acute myocardial infarction. Am Heart J 2006;151:323-31.
39. Gulliford M, Figueroa-Munoz J, Morgan M, et al. What does ‘access to
health care’ mean? J Health Serv Res Policy 2002;7:186-8.
40. Kayaniyil S, Leung YW, Suskin N, Stewart DE, Grace SL. Concordance
of self and program reported rates of cardiac rehabilitation referral, enroll-
ment and participation. Can J Cardiol 2009;25:e96-9.
To access the supplementary material accompanying this
article, visit the online version of the Canadian Journal of
Cardiology at www.onlinecjc.ca and at http://dx.doi.org/
Gravely et al.
Access to Heart Failure Clinics