Progress in Cardiovascular Nursing Winter 200818www.lejacq.docx

Progress in Cardiovascular Nursing Winter 200818
www.lejacq.com ID: 6611
Heart failure (HF) is the lead-ing cause of hospitalization for
persons older than 65 years and often
necessitates assistance from family
caregivers.1,2 Approximately 40% of
older adults are readmitted within
3 months postdischarge, resulting in
significant health care costs.2,3 Indeed,
more than one million hospitalizations
attributed to HF cost the patient and
United States health care system over
$27 billion a year.1 Hospitalizations
related to HF are complicated by
the aging process, comorbidities, and
psychosocial concerns that affect suc-
cessful management.2
In a study of patient outcomes post–
hospital discharge, Naylor and col-
leagues4 demonstrated that the use of
advanced practice nurses (APNs) was
effective in improving outcomes for
patients with HF. The feasibility of
adapting this approach is limited, how-
ever; costs for home visits by an APN are
high, a shortage of APNs employed in
home care exists, and funding for home
care has decreased with the Medicare
Prospective Payment System.5

An alternative strategy for promot-
ing self-management of HF is the
use of electronic home monitoring
(EHM). EHM is a form of tele-
medicine in which medical/nursing
management interventions are pro-
vided to individuals at a distance
from the health care provider.6 The
primary objective of this pilot study
was to examine the effectiveness of
postdischarge telemonitoring by an
APN on reducing subsequent hospital
readmissions, emergency department
(ED) visits, and costs and increasing
the time between discharge and read-
mission among older adults with HF.
Secondary objectives were to examine
depressive symptomatology, quality of
life, caregiver mastery, and social sup-
port for patients with HF.
BACKGROUND
Older adults with HF face a high
risk of early hospital readmission
within 3 to 6 months of discharge.2,3
Upon hospital discharge, patients
may encounter problems related to
depressive symptoms, threatened
quality of life, availability of informal
and formal social support, and how
they are monitored at home.2 Family
caregiving is affected by how one copes
with problems and resources available.

Researchers found that patients
with cardiovascular disorders including
HF have a high prevalence of depres-
sive symptoms or feelings of hopeless-
ness, with rates reported from 24% to
>40%.7,8 Depressive symptoms were
linked to increased hospital readmis-
sions, number of comorbidities, impair-
ment in activities of daily living, and the
need for informal social support.7–9
HF has an enormous impact on the
quality of life for patients because it is
a chronic condition without a cure.
According to the National Academy
on an Aging Society,10 persons with
heart disease are less satisfied with
their lives than the general population.
Heart failure (HF) is the leading cause of rehospitalization in
older adults. The
purpose of this pilot study was to examine whether
telemonitoring by an advanced
practice nurse reduced subsequent hospital readmissions,
emergency department
visits, costs, and risk of hospital readmission for patients with
HF. One hundred
two patient/caregiver dyads were randomized into 2 groups
postdischarge; 84 dyads
completed the study. Hospital readmissions, emergency
department visits, costs, and
days to readmission were abstracted from medical records.
Participants were inter-
viewed soon after discharge and 3 months later about effects of
telemonitoring on
depressive symptoms, quality of life, and caregiver mastery.

There were no signifi-
cant differences due to telemonitoring for any outcomes.
Caregiver mastery, infor-
mal social support, and electronic home monitoring were not
significant predictors
for risk of hospital readmission. Further studies should address
the interaction
between the advanced practice nurse and follow-up intervention
with telemonitor-
ing of patients with HF to better target those who are most
likely to benefit. Prog
Cardiovasc Nurs. 2008;23:18–26. ©2008 Le Jacq
From the College of Nursing, University of Akron, Akron, OH;1
the Department
of Nursing, MetroHealth Medical Center, Cleveland, OH;2 and
the Heart and
Vascular Center, Akron General Medical Center, Akron, OH3
Address for correspondence:
Karen A. Schwarz, PhD, RN, College of Nursing, University of
Akron,
Akron, OH 44325-3701
E-mail: [email protected]
Manuscript received June 13, 2007; revised August 10, 2007;
accepted August 16, 2007
P i l o t S t u d y
Telemonitoring of Heart Failure Patients and Their
Caregivers: A Pilot Randomized Controlled Trial
Karen A. Schwarz, PhD, RN;1 Lorraine C. Mion, PhD, RN;2
Debra Hudock, MSN, RN;3 George Litman, MD3
Progress in Cardiovascular Nursing® (ISSN 0889-7204) is
published Quarterly (March, June, Sept., Dec.) by Le Jacq,
located at Three Enterprise Drive, Suite 401, Shelton, CT

06484. Le Jacq is an imprint of Blackwell Publishing, which
was acquired by
John Wiley & Sons in February 2007. Blackwell’s programme
has been merged with Wiley’s global Scientific, Technical, and
Medical business to form Wiley-Blackwell. Copyright ©2008
by Le Jacq. All rights reserved. No part of this publication may
be
reproduced or transmitted in any form or by any means,
electronic or mechanical, including photocopy, recording, or
any information storage and retrieval system, without
permission in writing from the publishers. The opinions and
ideas expressed in
this publication are those of the authors and do not necessarily
reflect those of the Editors or Publisher. For copies in excess of
25 or for commercial purposes, please contact Ben Harkinson at
[email protected] or 781-388-8511.
®
Winter 2008 Progress in Cardiovascular Nursing 19
How patients adapt to a therapeutic
regimen is strongly influenced by how
they live within their disability.11 In
one of the few published studies that
has examined quality of life in patients
with HF that received post–hospital
discharge case management, Pugh and
colleagues12 reported that quality of
life scores were more favorable among
those who received intensive postdis-
charge collaboration with their provid-
ers than those who received usual care.
Furthermore, Goldberg and associ-

ates13 found that patients with HF
who had access to in-home telemoni-
toring had a slightly greater improve-
ment in quality of life than those who
received standard care.
Caregiver mastery may be viewed
as a personal resource that directly
and indirectly affects the relationship
between patient stressors and out-
comes. Caregiving mastery includes
the expectation that one is capable
of coping with problems.14 In a rare
study about caregiving skills, Scott15
related that caregivers of patients with
HF described both positive and nega-
tive components of receiving techno-
logic care. While caregivers found sat-
isfaction from caregiving, they feared
the responsibilities of learning to use
new technology. This learning may be
associated with caregiver mastery.
External resources in this study
included informal social support pro-
vided by family and friends and formal
social support from home health care
and EHM by an APN. Although fami-
lies provide 80% to 90% of informal
social support,16 there is a dearth of
studies about the relationship of infor-
mal social support and patient out-
comes. Schwarz and Elman’s17 findings
suggested that informal social support
significantly reduced the risk of hos-
pital readmission in patients with HF.

Formal social support such as home
care is a vital resource for patients with
HF because of the patient’s associ-
ated functional decline and need for
education. Stewart and colleagues18
reported that those patients receiving
a structured home visit from a cardiac
nurse 7 to 14 days after discharge had
fewer unplanned hospital readmis-
sions. Other researchers found that
a comprehensive treatment program
consisting of individualized home
visits improved quality of life and
decreased hospital readmissions and
costs for patients with HF.19
An EHM system is typically moni-
tored by an APN but does not replace
direct home care visits. Rather, telem-
onitoring provides more frequent (eg,
daily) surveillance of important clini-
cal parameters that allows for more
rapid intervention, which theoretically
in turn would delay or prevent ED
visits and hospital admissions.20 Some
researchers reported that the home
telecare intervention had significantly
reduced hospital readmissions, ED
visits, and costs postdischarge.20–22 In
addition, Roglieri and colleagues’23
findings indicated that a comprehen-
sive program of patient education and
telemonitoring by phone significantly
reduced hospital admissions and read-
missions. Using a daily EHM system,

Goldberg and coworkers13 found no
significant differences in the overall
time to death or first rehospitaliza-
tion, however, and McManus24 found
no significant differences in hospital
readmissions that were attributed to
telemonitoring. Although most of the
previous studies were randomized con-
trol trials,13,20,21,24 they differed on
patient age, technology used to moni-
tor patients, means of data collection,
and analyses of data.
Given the need to examine alterna-
tive methods to survey and monitor
patients with HF in the home in a
time of limited health care person-
nel, we examined the effectiveness
of telemonitoring with an APN in a
randomized clinical trial. The research
hypotheses were as follows:
-
sions, ED visits, and costs of care
will be significantly lower for HF
patients with EHM as compared
with usual care.
symptoms will be lower, but days to
readmission and measures of quality
of life and caregiver mastery will be
significantly higher in the EHM
group compared with usual care.
informal social support, and EHM

will significantly reduce the risk of
hospital readmission for patients
with HF.
METHODS
Setting and Sample
This pilot study was conducted at
a 537-bed tertiary teaching hospital
in Northeastern Ohio. The study
was reviewed and approved by the
institutional review board at the
participating hospital.
Potential participants for the study
included patient/caregiver dyads who
met the following criteria and rou-
tinely used the participating hospital.
The patients, aged 65 years or older,
had a diagnosis of New York Heart
Association (NYHA) classification II,
III, or IV HF25 and were functionally
impaired in at least 1 activity of daily
living (ADL) or one instrumental
activity of daily living (IADL), neces-
sitating assistance of a family caregiver.
They received home care from the
participating home care agency if it
was ordered by their physician, had
Medicare eligibility and an operat-
ing telephone line, and were able to
speak English. Classic symptoms of
clinical HF are shortness of breath and
fatigue, and abnormalities of systolic
and diastolic dysfunction may coex-
ist.25 The principal investigator (PI)
validated the diagnosis of systolic and/

or diastolic HF with chart review of
the cardiologist’s impressions related
to signs and symptoms of HF, ejection
fraction and/or the echocardiography
report after gaining oral consent from
the patient before hospital discharge.
Exclusion criteria included planned
discharge to a nursing home, inability
to be interviewed because of physical
illness, current use of a telemonitor-
ing scale, inability to be contacted
postdischarge, receiving regular infu-
sions or dialysis, NYHA class I, inde-
pendence in performing ADLs, no
caregiver, use of hospice care, client
of nonparticipating home health care
was acquired by
be
ideas expressed in

®
agency, participation in another study,
dementia, planned surgery, inability
to speak English, planned hospitaliza-
tion, and inability to stand on a scale.
Inclusion criteria for caregivers includ-
ed being cognitively intact, having a
familial relationship to the patient,
and providing assistance with at least 1
ADL or 1 IADL. Overall, 562 patients
were screened for eligibility (Figure).
Of these, 152 (27%) were eligible; 102
(67%) agreed to participate.
Sample size determination was
based on the reported difference
(22%) in the proportion of patients
readmitted in the control group vs the
intervention group within 3 months
of hospital discharge.19 The targeted
enrollment was 84 patient/caregiver
dyads using a power of 80% and a
one-tailed test of significance with
set at .05. Of the 102 dyads enrolled,
84 (82%) completed the study; 40
in the usual care group and 44 in
the intervention group. Attrition was
equivalent between groups.

Procedure
Institutional review board approval
was obtained, and cardiologists and
internal medicine physicians gave
written permission for their patients
to be identified and enrolled. Potential
participants were identified by the
HF care manager with the assistance
of care managers in 4 hospital units.
While making daily rounds, the HF
care manager informed potential
participants about the study and gained
oral permission for the PI to contact
them before hospital discharge. Prior to
discharge, the PI briefly explained the
study to the patient and/or caregiver,
provided a letter of explanation, and
received oral consent for a chart review
to verify whether they met study criteria.
Patients provided their phone numbers
for contact upon discharge. Participants
were randomized to usual post–hospital
discharge care or to usual care with a
telemonitoring scale by drawing from a
preprepared, sealed envelope.
Participants were interviewed in
their homes within 10 days of hospital
discharge and 90 days later by trained
registered nurses (RNs) who were not
part of postdischarge care. To main-
tain inter-rater reliability, checks were
conducted periodically throughout
the study and maintained at >90%

agreement. Written informed consent
and Health Insurance Portability and
Accountability Act (HIPAA) autho-
rization were provided by patients
and caregivers at the first interview.
During data collection, patients
received all standard treatments and
services ordered by their primary phy-
sicians/cardiologists.
Participants randomized to the
intervention group received the
Cardiocom EHM system (Cardiocom,
LLC, Chanhassen, MN) at the first
interview, and the nurse removed the
equipment 90 days later, at the sec-
ond interview. The HF care manager
trained the PI about use of the EHM
system and ensured its availability.
The RN data collector was further
trained by the PI about the equipment
and taught the patient/caregiver dyad
how to use the EHM system. The PI
met with the HF care manager weekly
to discuss technical issues with the
equipment. On occasion, the PI called
patients soon after placement of the
scales to inquire whether they had any
difficulty understanding instructions
for its use.
EHM System
The Cardiocom EHM system was
leased to the research team during the
study period, and patients were not
responsible for charges. The RN data

Hospitalized HF
patients assessed
for eligibility,
N=562 Excluded, n=460 Refused, n=50
Ineligible, n=410
Nursing home, n=117
Too ill, n=97
Telemonitoring use, n=52
Inability to contact, n=40
Dialysis, infusions, n=28
Independent ADL, n=24
No caregiver, n=18
Hospice care, n=10
Non-agency client, n=8
In other study, n=6
Dementia, n=3
Need for surgery, n=2
Non–English speaking, n=2
Planned hospitalization, n=2
Unable to stand on scale, n=1
Randomized,
n=102
Usual care,
n=51
Usual care plus
telemonitoring,
n=51
Attrition
Death, n=7

Nursing home, n=3
Withdrawal, n=1
Attrition
Death, n=4
Nursing home, n=2
Withdrawal, n=1
Figure. Algorithm of study participants who were screened for
eligibility.
was acquired by
be
ideas expressed in
®

collector placed a weight scale in the
participants’ homes and connected
via the telephone line to a computer
system in the collaborating hospital.
The data-receiving computer was
positioned in an office on the telemetry
unit of the study hospital. The EHM
system was programmed to measure
weight on a daily basis. The display
on the device asked the participants to
answer “yes” or “no” to questions about
shortness of breath, cough, fatigue,
swelling, chest discomfort, urination,
exercise, dizziness, medication use,
and sodium intake. The computer
stored each patient’s electronic health
file and automatically displayed
clinical variances when prescribed
parameters exceeded predetermined
ranges. Variances included failure to
call daily, changes in symptoms, and
weight outside prescribed parameters.
The Cardiocom Telescale (Cardiocom,
LLC, Chanhassen, MN) is accurate
to ±0.1 lb and detects as little as 45
mL of fluid gain (D. Consentino, oral
communication, February 8, 2002).
The HF care manager, an APN, was
responsible for daily monitoring of
parameters received electronically.
When participants had measurements
outside of prescribed parameters, the
monitoring nurse called the caregiver in
the dyad to further assess the situation,
provide education, and update the

medication regimen. In addition, the
APN notified the primary physician or
cardiologist about the patient’s status
as needed.
Variables and Measures
Demographics such as age, sex,
education, race, socioeconomic status,
and perceived health of the patient and
caregiver were measured by self-report at
baseline. Hospital readmissions, defined
as unplanned hospital readmissions
for HF symptoms within 3 months
post–hospital discharge, were collected
by medical record review after 90 days
postdischarge. Emergency department
visits for HF were ascertained through
medical record review after 90 days’
postdischarge. Days to readmission were
used as a measure of risk for hospital
readmission. Days to readmission,
defined as the number of days between
the date of initial hospital discharge and
the first readmission to the hospital,
was assessed through medical record
review after 90 days’ postdischarge.
Physiologic health indicators, blood
pressure, apical pulse, weight, and oxy-
gen saturation were assessed by the
PI or research RN at baseline and 3
months later. Comorbidities and pre-
scribed medications were abstracted
from the medical record before hos-
pital discharge and were confirmed at

baseline. Use of home health care was
documented with a computerized chart
review after 90 days’ postdischarge.
Severity of HF was assessed subjectively
by the PI or research RN using the
NYHA functional class25,26 at baseline
and at 90 days’ postdischarge.
Functional status was measured
as the ability to perform ADLs and
IADLs at baseline and 90 days’ post-
discharge. The ADL tool27 consists
of 6 items (eating, dressing, bathing,
transfers, incontinence, and toileting)
and is scored from 0 (totally indepen-
dent) to 2 (totally dependent). The
ADL Index has a Cronbach’s of 0.82
for hospitalized older adults.28 Seven
items from the IADL scale29 (eg,
cooking, housekeeping) were scored
similarly. The IADL scale has a high
reproducibility coefficient of 0.96 and
inter-rater reliability of 0.87.29 The
ADL and IADL sum score range is
0 to 26. Spector and Fleishman30
demonstrated the feasibility and valid-
ity of combining the 2 scales with a
sample of functionally disabled older
adults and reported that the correla-
tion between the IADL scores and
ADL scores was 0.70. For this sample,
Cronbach’s was 0.85 for the com-
bined scale.
Depressive symptomatology was
measured using the Center for

Epidemiological Studies Depression
Scale (CES-D)31 at baseline and 90
days’ postdischarge. Participants rated
20 items on a 4-point Likert scale
from 0 (“rarely”) to 3 (“most or all of
the time”) with a possible range of 0
to 60. Higher scores indicate more
depressive symptoms. The CES-D
demonstrated excellent psychometric
properties in community samples.31,32
In this sample, Cronbach’s at time 1
and time 2 were 0.89.
Quality of life, defined as patient’s
perceptions of the effects of HF on
one’s life, was measured with 18 items
from the Minnesota Living with HF
questionnaire (MLWHF)11,33 at base-
line and 90 days’ postdischarge. The
MLWHF measures individuals’ percep-
tions of the ways in which symptoms
of HF have impacted their lives in
the past month. Since the majority of
patients were older and not employed
and depression was assessed with the
CES-D, questions about working,
sexual activities, and depression were
eliminated from the original scale.
Eighteen items were rated on a 6-point
Likert scale from 0 (“no”) to 5 (“very
much”), with a possible range of 0
to 90. A higher score indicated more
symptomatic impact on one’s life. For
this sample, Cronbach’s coefficients
at time 1 and time 2 were 0.91. Rector

and Cohn33 reported that the MLWHF
was a valid patient self-assessment of the
therapeutic benefit of medical therapy.
Caregiver mastery, defined as a
positive view of one’s ability to provide
care, was measured with the mas-
tery subscale from the Philadelphia
Geriatric Center Caregiving Appraisal
Scale (PGCCAS)34 at baseline and 90
days’ postdischarge. Six items assess
the likelihood of caregiver uncertainty
about how to provide care, reassurance
that the patient is receiving proper
care, feeling on whether they should
be doing more for the patient, feel-
ing that they are doing a good job
of providing care, perceptions about
capability of dealing with problems as
they arise, and identifying the patient’s
needs. Caregivers rated 6 items on a
5-point Likert scale from 1 (“never”)
to 5 (“nearly always”), with a possible
range of 6 to 30. Higher scores indi-
cated greater mastery. Studies demon-
strated moderate Cronbach’s coeffi-
cients ranging from 0.61 to 0.73.34,35
For this sample, Cronbach’s was
0.65 at time 1 and 0.70 at time 2.
was acquired by

be
ideas expressed in
®
Informal social support, described
as instrumental activities performed
by families and friends, was mea-
sured with the tangible subscale from
the Modified Inventory of Socially
Supportive Behaviors Scale (MISSB)36
at baseline. The tangible subscale
reflects activities such as receiving a
monetary loan. Caregivers rated 9
items on a 4-point Likert scale from
1 (“never”) to 4 (“very often”), with
a possible sum score of 9 to 36.
Higher scores indicated more informal
social support. Cronbach’s coef-
ficients ranged from 0.71 to 0.92 in
studies of caregivers of patients who

were recently hospitalized.17,32 For this
sample, the Cronbach’s coefficient
was 0.90.
Cost of care was calculated for the
90-day period post–initial hospital-
ization. Charges posthospitalization
were calculated by tracking billing
charges for rehospitalization, emer-
gency department visits, and charges
for usual home care from the provider
of home health care. Costs of care for
the EHM group included the former
charges plus the additional monthly
charge of renting the monitoring sys-
tem. Charges for usual home care were
calculated by multiplying the stan-
dard charge data times the number of
visits by the RN (at $155 per visit),
home health aide (at $85 per visit),
social worker (at $165 per visit), and
physical therapist, occupational thera-
pist, dietitian, or speech therapist (at
$140 per visit). Supply costs averaged
$38.50 per episode of care. Charges for
EHM were calculated for direct costs
of placement of the Cardiocom unit
($165). Data for reimbursement for
the telemonitoring specialist were not
available and, therefore, not included.
In addition, out-of-pocket expenses
for services posthospitalization were
determined by calculating the number
of physician office visits and instances
of laboratory work and assigning a co-

pay of $12.
Data Analyses
Descriptive and comparative analyses
were performed using SPSS for
windows, version 13 (SPSS, Inc,
Chicago, IL). Descriptive statistics,
frequencies, and measures of central
tendency and dispersion were used
to describe the sample. Associations
between variables were analyzed with
Pearson correlation coefficients for
interval variables and the Spearman
correlation coefficient for ordinal
variables. Means were substituted for
the relatively few areas of missing data.
The effectiveness of the intervention
was examined by using an intention-
to-treat analysis; was set at ≥.05.
Outcomes were examined between the
2 groups using chi-squared likelihood
ratio tests for categorical variables,
t tests for approximately normally
distributed variables, and Wilcoxon
rank sum tests for skewed variables.
Subgroup analyses were conducted,
comparing the intervention and usual
care groups by risk status.
Survival analysis with Cox propor-
tional hazard modeling37 was used to
assess risk for hospital readmission by
the number of days between discharge
and first readmission. Cox proportional
hazard modeling accommodates for the

Table I. Participant and Caregiver Characteristics at the Index
Hospital Visit by Study Group (N=102)
PATIENT INTERVENTION GROUP (N=51) USUAL CARE
GROUP (N=51) P VALUE
Age, y 77.1±7.3 79.1±6.9 .17
Femalea 22 (43) 31 (61) .07
Whitea 41 (80) 42 (82) .56
Marrieda 36 (71) 28 (55) .25
High school graduate or highera 42 (82) 25 (49) .01
ADLb/IADLc 6.5±4.9 8.1±4.1 .08
NYHA class IIa 12 (24) 9 (18) .74
NYHA class IIIa 23 (45) 26 (51)
NYHA class IVa 16 (31) 16 (31)
Comorbidities 4.2±2.4 4.9±2.1 .14
Current medications 10.2±4.5 9.9±3.7 .79
Heart medications 5.6±1.9 5.4±2.0 .51
Cardiologista 46 (90) 41 (80) .16
CAREGIVER
Age, y 63.9±15.4 63.0±16.7 .76
Relationship .12
Spousea 32 (64) 22 (43)
Childa 13 (26) 16 (31)
Othera 5 (10) 13 (26)
Values are expressed as mean ± SD unless otherwise indicated.
aValue is No. (%). bFunctionally impaired in
>1 activity. cFunctionally impaired in 1 activity. Abbreviations:
ADL, activities of daily living; IADL, instrumental
activities of daily living; NYHA, New York Heart Association.

was acquired by
be
ideas expressed in
®
censoring of information and accounts
for the competing risk.17,37 The pool of
potential predictors of risk for hospital
readmission specific to the dyad includ-
ed caregiver mastery, informal social
support, and EHM. The multivari-
able model was derived using multiple
model building techniques: backward
elimination with =.05 stay criteria,
stepwise with =.25 enter criteria, and
=.05 stay criteria to identify indepen-
dent predictors of days to readmission.

RESULTS
Participant Profile
One hundred two patients were
originally enrolled in the study; 51 in
the EHM group and 51 in the usual
care group. The mean age of the entire
sample was 78.1 years with a range of
65 to 94 years. Fifty-two percent (n=53)
were women. Participant characteristics
at the time of the baseline visit in
the hospital are shown in Table I.
Education level was significantly higher
for patients in the intervention group
( 2=18.5; P=.01). At baseline and 3
months later, there were no significant
differences between groups for
prescribed use of angiotensin-converting
enzyme inhibitors, -blockers, digoxin,
or diuretics.
Twenty percent of the participants
(n=20) had implanted defibrillators.
Significant differences existed for use
of defibrillators between the inter-
vention (n=14) and usual care (n=6)
groups at baseline ( 2=3.98; P=.05).
At 90 days’ postdischarge, differences
for defibrillators were similar between
the intervention (n=13) and usual
care (n=6) groups ( 2=2.53; P=.11).
Twenty percent of patients without
defibrillators did not finish the study.
The number of hospital readmissions
was similar between those with and
without defibrillators (t=–1.3; P=.19).

Use of home care, total number of
home care services, and informal social
support were similar between inter-
vention and usual care groups (P=.32,
.66, and .74, respectively).
The total sample reported having
multiple comorbidities: hypertension
(51%), diabetes (50%), atrial fibril-
lation (30%), myocardial infarction
(29%), stroke (13%), bypass surgery
(28%), chronic obstructive pulmo-
nary disease (29%), and cancer (6%),
and groups had similar comorbidi-
ties ( 2=12.13; P=.28). Systolic blood
pressure at baseline ranged from 84
to 180 mm Hg with a mean of
127.56±19.21 mm Hg, and diastolic
blood pressure ranged from 50 to 100
mm Hg with a mean of 69.3±9.74
mm Hg. Heart rate ranged from 40
to 110 beats per minute (bpm) with
a mean of 71.39±11.4 bpm. Oxygen
saturation ranged from 86% to 98%
with a mean of 94.9±2.36%. Weight
ranged from 85.6 to 372.5 lb with a
mean of 179.14±49.53 lb. Caregivers
reported providing assistance from 1
month to 27 years with a mean of
4.5±5.5 years.
Patient/caregiver dyads that com-
pleted the study (n=84) did not differ
from those who did not (n=18) on
demographic characteristics, physi-
ologic health indicators, severity of

illness, depressive symptomatology,
quality of life, informal social sup-
port, caregiver mastery, or cognition.
Patients not completing the study were
more dependent in ADLs and IADLs
than those who completed it (10.8±4.1
vs 6.6±4.3; t=–3.67; P<.001).
Electronic Home Monitoring
The majority of participants in the
intervention group (91%) reported
using the EHM system on a daily
basis during the 90-day post–hospital
discharge monitoring period.
According to the APN’s report,
however, the majority of patients
(93%) did not use the EHM system
on at least 1 day. The mean number of
days that EHM system was not used
was 16.1±17.9 days for the investigation
group with a range of 0 to 66 days. The
APN called the majority of patients
(95%) about symptoms that exceeded
the parameters on at least 1 day during
the 90-day monitoring period. The
average number of days that the APN
called patients in the intervention
group who reported symptoms that
exceeded the prescribed parameters
was 26.7±21.14 with a range of 0 to
77 days.
Hospital Readmissions, Emergency
Department Visits, and Costs of
Care Between Groups

Table II displays subsequent hospital
readmissions, emergency department
visits, and costs 90 days’ postdischarge.
There was no difference in hospital
readmission between the intervention
(n=12) and usual care (n=13) groups
( 2=0.27; P=.60). Hospital charges
alone did not differ significantly
between intervention and usual care
groups ($10,996.86±$29,230.05;
$5,462.58±$9,825.00, respectively;
P=.26). In addition, out-of-pocket
costs for medications, physician office
visits, and laboratory testing were
similar between groups.
Depressive Symptoms, Days to
Readmission, Quality of Life, and
Caregiver Mastery Between Groups
Table III displays depressive symptoms,
days to readmission, quality of life,
and caregiver mastery among the
intervention and usual care groups
at 90 days’ postdischarge. While
differences existed between groups
Table II. Subsequent Hospital Readmission, ED Visits, and Cost
of Care by Group (N=84)
VARIABLE INTERVENTION GROUP (N=44) USUAL CARE
Hospital readmission 0.32±0.6 0.33±0.6 .90
ED visits 0.34±0.6 0.38±0.5 .73
Costs of care, US $ 12,017.99±29,405.65 6,673.29±10,258.28
.28
Values are expressed as mean ± SD. Abbreviation: ED,
emergency department.

was acquired by
be
ideas expressed in
®
at baseline with regard to caregiver
mastery, there were no differences
between groups for any outcome at
the 90-day follow-up visit. For those
readmitted to the hospital, days to
readmission were similar between the
intervention and usual care group
(40.6±31.3; 41.2±24.0, respectively;
P=.96). For the entire sample, quality

of life improved significantly from
baseline to the 90-day follow-up visit
(t=3.9; P<.0001).
Caregiver Mastery, Informal Social
Support, and Telemonitoring as
Predictors of Reduced Hospital
Readmission
Cox proportional hazards regression
modeling was used to identify
independent predictors of risk
for hospital readmission in days.
Independent variables included
caregiver mastery, informal social
support, and telemonitoring (yes/
no). None of these predicted risk of
hospital readmission.
DISCUSSION
Aging of the US population and
concomitant increase in the prevalence
of HF dictate the need for strategies
to improve self-care management
and minimize costly health service
utilization. This pilot study examined
whether the addition of an EHM
system and APN responder to usual
postdischarge home care would reduce
number of hospital readmissions,
emergency department visits, health
service charges, and risk of readmission
among older patients with HF. In
addition, we examined whether more
frequent surveillance and contact with
patients and their caregivers would

decrease depressive symptoms, increase
days to readmission, improve quality
of life, and increase caregivers’ sense
of mastery in the management of HF.
We found no significant health care
consumption or psychological benefit
to patients by adding telemonitoring
in the health service.
The overall lack of effect of our
intervention might be related to several
issues, including the experience of the
current cohort of older adults and the
nature of their illness. Baby boomers
are more experienced with technology
and they may desire more sophisticat-
ed means of monitoring their health
as they age. A higher proportion of
our patients (79%) were classified as
NYHA class III or IV as compared
with an earlier study by Schwarz and
Elman.17 Newer therapies added to
traditional medical therapy have led
to improvements in function, exercise
capacity, and quality of life in many
studies of patients with mild to mod-
erate HF.25 In this study, equivalency
in hospital readmission and emer-
gency department visits among groups
may reflect the natural history of HF
for patients with a clinically advanced
state.13 Management of HF is further
compounded by many psychosocial
and economic factors that cannot
always be measured.2 Furthermore,

since the APN was not always avail-
able on weekends, monitoring by
phone may have varied within the
intervention group.
Although Jerant and associates20
and Benatar and colleagues21 found
that telemonitoring reduced hospital
readmissions and emergency depart-
ment visits, our findings are consistent
with the lack of effect of telemoni-
toring found by Goldberg and col-
leagues13 and McManus.24 Compared
with the reports of Jerant and cowork-
ers20 and Bentar and colleagues,21 our
patients were older and may have had
less chance to respond optimally in the
short follow-up time. Jerant and asso-
ciates20 followed patients for 180 days;
thus, a 90-day follow-up may not have
been adequate to educate patients and
their caregivers about self-care and
adherence to the plan of care.
Similar to Pugh and colleagues’12
findings but contrary to others,20–22
costs post–hospital discharge did not
differ significantly between groups.
For the present study, a member of
the research team was able to access
hospitalization costs for readmissions.
Costs were not categorized by physi-
cian visits, supplies, tests, etc. Although
telemonitoring did not save on costs for
health services, costs related to saving

Table III. Depressive Symptoms, Days to Readmission, Quality
of Life, and Caregiver Mastery at 90 Days by
Study Group
VARIABLE INTERVENTION GROUP (N=44) USUAL CARE
Depressive symptoms
At baseline 8.7±8.9 6.8±8.9 .32
At 90 days 8.2±11.2 6.6±6.7 .44
Days to readmission
At baseline
At 90 days 40.6±31.3 41.2±24.0 .96
Quality of life
At baseline 39.5±23.3 35.8±21.5 .46
At 90 days 27.4±21.7 27.3±21.6 .98
Caregiver mastery
At baseline 24.7±3.3 26.3±3.7 .05
At 90 days 25.2±3.8 25.8±3.0 .38
Values are expressed as mean ± SD.
was acquired by
be

ideas expressed in
®
time should also be considered. Future
research is needed to learn more about
EHM as a convenience to patients,
especially those who are homebound,
travel frequently, are socially isolated,
have transportation costs associated
with office visits, or work outside the
home during typical physician office
hours. Telemonitoring offers health
care providers and patients interaction
at a distance, when away from home,
and at the convenience of both parties.
Depressive symptoms and caregiver
mastery have rarely been studied in
patients receiving a home monitoring
intervention. Depressive symptoms
were low and caregiver mastery was
high in both groups and did not differ
significantly due to EHM. These find-
ings concur with those of Friedman
and Griffin38 who found that patients

were not generally depressed. Contrary
to the findings of Benatar and col-
leagues21 and Bondmass and cowork-
ers,22 quality of life scores did not
differ significantly between groups.
Reasons for these findings may be
related to the length of time that fam-
ily members had been providing care
and the type of care provided. Most
patients in this sample had been living
with HF or required assistance from
a caregiver for an average of 4 years.
Caregivers remarked that they had
adjusted to the problems that accom-
pany limited activity, many had very
good insurance benefits from their
past employers, and they expected the
changes that come with aging.
Informal social support was high
in this sample and was not a sig-
nificant predictor of risk of readmis-
sion. Although Schwarz32 found that
tangible social support predicted less
early hospital readmission, the sample
included patients with multiple comor-
bidities in addition to HF and who
were more functionally impaired.
Limitations
Our study has several limitations. Our
findings are limited to patients classified
in NYHA classes II, III, and IV. Since
31% of patients in this study were
NYHA class IV, a replication study

using less severely ill patients may lead
to greater differences between groups,
even with a short follow-up period.
Although the majority of intervention
patients reported that they used the
EHM system on a regular basis, the PI
did not have information about whether
teaching before hospital discharge was
consistent between groups.
Functional status, number of
comorbidities, and medication use
did not differ significantly between
groups at baseline or 90 days’ postdis-
charge. Patients subjectively reported
their functional abilities, however, and
severity of comorbidities was not stud-
ied. In past studies of patients with
HF, researchers reported variations in
how medications were prescribed and
issues with compliance.39,40 Although
patients reported taking medications
as prescribed, a formalized monitor-
ing system was not used. Information
about dosages or changes in medica-
tions was not collected, and these
variables could have differed between
groups and affected results.
Specific number of visits to the
patients’ cardiologist/primary physi-
cian and how physicians responded
to nursing assessments were also not
obtained as part of the study. Several of
the cardiologists voiced concerns about
the amount of paperwork involved

when monitoring via an EHM system.
Lack of attention to paperwork could
have minimized information used in
decision making and therefore limited
actions that could have prevented hos-
pitalization or early readmission.
Limitations of the study may be
due to absence of control over usual
care provided by the home care agen-
cy. Contrary to this study, others used
a study nurse to provide care, and
together the PI and nurse reviewed
assessments of patients.20 Finally, there
was no group that received EHM and
not home care in our study. Thus, we
do not know whether EHM would
benefit patients who have a similar
status as a solo resource/service.
CONCLUSIONS
Telemonitoring by EHM did not
reduce rates of hospitalization,
emergency department visits, cost of
care, or depression, and it did not
increase caregiver mastery, quality of
life, or days to readmission; however,
EHM did not cause harm, as there
were no negative differences between
groups in primary outcomes. Further
EHM technological developments
may enhance self-management of
HF and eventually lead to improved
clinical outcomes. Research is needed
to better target those most likely to

benefit from this intervention. Future
research should address the interaction
between the APN and follow-up
intervention with telemonitoring.
Disclosure: The project was supported by
Grant Number 1 R15 R008698–01 from
the National Institute of Nursing Research,
National Institutes of Health (NIH), and the
Ohio Board of Regents. Its contents are solely
the responsibility of the authors and do not
necessarily represent the official views of the
National Institute of Nursing Research, NIH.
REFERENCES
1 Rosamond W, Flegal K, Friday G, et al, on behalf
of the American Heart Association Statistics
Committee and Stroke Statistics Subcommittee.
Heart disease and stroke statistics—2007 update:
a report from the American Heart Association
Statistics Committee and Stroke Statistics
Subcommittee. Circulation. 2007;115:e69–e171.
2 Rich MW. Heart failure disease management: a
critical review. J Card Fail. 1999;5:64–75.
3 Proctor EK, Morrow-Howell N, Li H, et al.
Adequacy of home care and hospital readmis-
sion for elderly congestive heart failure patients.
Health Soc Work. 2000;25:87–94.
4 Naylor MD, Brooten D, Campbell R, et al.
Comprehensive discharge planning and home
follow-up of hospitalized elders: a randomized

clinical trial. JAMA. 1999;281:613–620.
5 Anderson MA, Clarke MM, Helms LB, et al.
Hospital readmission from home health care
before and after prospective payment. J Nurs
Scholarsh. 2005;37:73–79.
6 Casper GR, Kenron DA. A framework for tech-
nology assessment: approaches for the selection
of a home technology device. Clin Nurse Spec.
2005;19:170–174.
7 Jiang W, Alexander J, Christopher E. Relationship
of depression to increased risk of mortality and
rehospitalization in patients with congestive heart
failure. Arch Intern Med. 2001;161:1849–1856.
8 Vaccarino V, Stanislav VK, Abramson J, et al.
was acquired by
be
ideas expressed in

®
Depressive symptoms and risk of functional
decline and death in patients with heart failure. J
Am Coll Cardiol. 2001;38:199–205.
9 Oxman TE, Hull JG. Social support and treatment
response in older depressed primary care patients. J
Gerontol B Psychol Sci Soc Sci. 2001;56:P35–P45.
10 National Academy on Aging Society. Heart
disease: a disabling yet preventable condition.
http://www.agingsociety.org/agingsociety/pdf/
heart.pdf. Accessed May 1, 2000.
11 Rector TS, Kubo SH, Cohn JN. Patient’s self-
assessment of their congestive heart failure: part
2. Content, reliability, and validity of a new
measure, the Minnesota living with heart failure
questionnaire. Heart Failure. 1993;3:198–209.
12 Pugh LC, Havens DS, Xie S, et al. Case manage-
ment for elderly persons with heart failure: the
quality of life and cost outcomes. Medsurg Nurs.
2001;10:71–84.
13 Goldberg LR, Piette JD, Walsh MN, et al.
Randomized trial of a daily electronic home

monitoring system in patients with advanced heart
failure: the Weight Monitoring in Heart Failure
(WHARF) trial. Am Heart J. 2003;146:705–712.
14 Pearlin LI, Mullan JT, Semple SJ, et al.
Caregiving and the stress process: an overview
of the concepts and their measures. Gerontologist.
1990;30:583–591.
15 Scott LD. Technological caregiving: a qualitative
perspective. Home Health Care Manage Pract.
2001;13:227–235.
16 Schwarz KA. Home health care: formal social
support to family caregivers of older adults.
Family Perspective. 1996;30:47–61.
17 Schwarz KA, Elman C. Identification of factors
predictive of hospital readmissions for patients
with heart failure. Heart Lung. 2003;32:88–99.
18 Stewart S, Marley JE, Horowitz JD. The addition
of a home visit by a cardiac nurse to usual multi-
disciplinary care reduced deaths and readmissions
in patients with chronic congestive heart failure.
Lancet. 1999;354:1077–1083.
19 Rich MW, Beckham V, Wittenberg C, et al. A
multidiscliplinary intervention to prevent the read-
mission of elderly patients with congestive heart
failure. N Engl J Med. 1995;333:1190–1195.
20 Jerant AF, Azari R, Nesbitt TS. Reducing the cost
of frequent hospital admissions for congestive
heart failure: a randomized trial of a home telecare

intervention. Med Care. 2001;39:1234–1245.
21 Benatar D, Bondmass M, Ghitelman J, et al.
Outcomes of chronic heart failure. Arch Intern
Med. 2003;163:347–352.
22 Bondmass M, Bolger N, Castro G, et al. The
effect of physiologic home monitoring and
telemanagement on chronic heart failure out-
comes. Internet J Asthma Allergy, Immunol [serial
online]. http://www.ispub.com/ostia/index.
php?xmlFilePath=journals/ijanp/vol3n2/chf.xml.
Accessed April 30, 2002.
23 Roglieri JL, Futterman R, McDonough KL, et
al. Disease management interventions to improve
outcomes in congestive heart failure. Am J Manag
Care. 1997;3:1831–1839.
24 McManus SG. A telehealth program to reduce
readmission rates among heart failure patients:
one agency’s experience. Home Health Care
Manage Pract. 2004;16:250–254.
25 Hunt SA, Abraham WT, Chin MH, et al, on
behalf of the American College of Cardiology,
the American Heart Association Task Force
on Practice Guidelines, the American College
of Chest Physicians, the International Society
for Heart and Lung Transplantation, and the
Heart Rhythm Society. ACC/AHA guideline
update for the diagnosis and management of
chronic heart failure in the adult: a report of the
American College of Cardiology/American Heart
Association Task Force on Practice Guidelines
(Writing Committee to Update the 2001

Guidelines for the Evaluation and Management
of Heart Failure): developed in collaboration
with the American College of Chest Physicians
and the International Society for Heart and Lung
Transplantation: endorsed by the Heart Rhythm
Society. Circulation. 2005;112:e154–e235.
26 Bennett JA, Riegel B, Bittner V, et al. Validity
and reliability of the NYHA classes for measur-
ing research outcomes in patients with cardiac
disease. Heart Lung. 2002;31:262–270.
27 Katz S. Assessing self-maintenance: activi-
ties of daily living, mobility, and instrumen-
tal activities of daily living. J Am Geriatr Soc.
1983;31:721–726.
28 Lockery SA, Dunkle RE, Kart CS, et al. Factors
contributing to the early rehospitalization of elder-
ly people. Health Soc Work. 1994;19:182–191.
29 Lawton MP, Brody EM. Assessment of older peo-
ple: self-maintaining and instrumental activities
of daily living. Gerontologist. 1969;9:179–186.
30 Spector WD, Fleishman JA. Combining activities
of daily living with instrumental activities of daily
living to measure functional disability. J Gerontol
B Psychol Sci Soc Sci. 1998;53:S46–S57.
31 Radloff LS. The CES-D scale. A self-report
depression scale for research in the general popu-
lation. Appl Psychol Meas. 1977;1:385–401.
32 Schwarz KA. Predictors of early hospital read-
missions of older adults who are functionally

impaired. J Gerontol Nurs. 2000;26:29–36.
33 Rector TS, Cohn JN. Assessment of patient
outcome with the Minnesota living with heart
failure questionnaire: reliability and valid-
ity during a randomized, double-blind, placebo-
controlled trial of pimobendan. Am Heart J.
1992;124:1017–1025.
34 Lawton MP, Kleban MH, Moss M, et al.
Measuring caregiver appraisal. J Gerontol.
1989;44:P61–P71.
35 Sevick MA, Matthews JT, Wielobob C, et al.
Volume-based ventilator-dependent patients:
measurement of the emotional aspects of home
caregiving. Heart Lung. 1994;23:269–278.
36 Krause N, Markides K. Measuring social sup-
port among older adults. Int J Aging Hum Dev.
1990;30:37–53.
37 Allison PD. Survival Analysis Using the SAS System:
A Practical Guide. Cary, NC: SAS Institute; 1995.
38 Friedman MM, Griffin JA. Relationship of physi-
cal symptoms and physical functioning to depres-
sion in patients with heart failure. Heart Lung.
2001;30:98–104.
39 De Geest S, Scheurweghs L, Reynders I, et al.
Differences in psychosocial and behavioral pro-
files between heart failure patients admitted to
cardiology and geriatric wards. Eur J Heart Fail.
2003;5:557–567.

40 Bennett SJ, Huster GA, Baker SL, et al.
Characterization of the precipitants of hospital-
ization for heart failure decompensation. Am J
Crit Care. 1998;7(3):168–174.
was acquired by
be
ideas expressed in
®
Since I’ve been teaching this course, I’ve learned that a lot of
students have difficulty with this assignment. Here is some
guidance that might help you complete this assignment
successfully. The numbers pertain to the question number.
1. The purpose of the study is clearly and explicitly stated in
this article.

2. The research question is clearly and explicitly stated in this
article.
3. Go back to Week 3 lesson and to chapter 2 of your text to
review research designs. This article explicitly states the
research design.
4. The question specifically states to go to Chapter 2 in your
text and look at the qualitative characteristic in the table (2.1).
Using this table, identify any of those characteristics that this
study contains.
5. Make sure you go to the journal’s (not the article) website. It
answers this question. Just Google the name of the journal and
you should find the website. You can also find a checklist to
determine if a source is credible (including evidence of peer
review) in your text.
6 and 7 are pretty self-explanatory.
8. Identify the TYPE of sampling that was used and the
strengths and weaknesses of this type of sampling. Go back to
Week 4 lesson and chapter 7 in your text. Identify the criteria
used for inclusion in the study
9. Go to your text to see the definition of vulnerable
populations.
10. Self-explanatory
The second article is more difficult, I think.
11. The purpose of the study is clearly and explicitly stated in
this article.
12. The questions are explicit in this article, but they are
called “hypotheses”.
13. The authors did not fully describe the design of the study,

but do talk about setting, sample, and what and how statistics
were collected – this will enable you to deduce the design of the
study.
14. Go back to Chapter 2 of your text again and do the same
thing you did for question 4.
15. See #5.
16. Self explanatory.
17. The population of the study is clearly and explicitly stated
in this article.
18. See question 8
19. See question 9
20. Self explanatory.
Telemonitoring of heart
failure patients and their
caregivers: a pilot rand...
Basic Search Advanced Publications Browse Preferences
English Help
Full text

Full Text
A Process of Decision Making by Caregivers of Family
Members With Heart Failure
Sanford, Julie, DNS, RN; Townsend-Rocchicciolli, Judith, PhD,
RN; Horigan, Annie, MSN, RN; Hall, Pat, PhD, CRNP.
Research and
Theory for Nursing Practice 25.1 (2011): 55-70.
Abstract (summary)
Heart failure (HF) is a major cardiovascular problem and the
number of people living with HF continues to climb.
Throughout the illness continuum, patients
and their family caregivers are involved in decision making. As
the illness worsens and patients can no longer make decisions,
decision making becomes the
responsibility of their caregivers who may have little
preparation for the role. The purpose of this grounded theory
study was to examine how caregivers of
family members with HF make decisions. A nonlinear decision-
making process consisting of several actions was identified,
which included actualizing;
seeking input, information, or support; reflecting; choosing;
evaluating; and validating the decision.
Headnote
Heart failure (HF) is a major cardiovascular problem and the
number of people living with HF continues to climb.
Throughout the illness continuum, patients
and their family caregivers are involved in decision making. As
the illness worsens and patients can no longer make decisions,
decision making becomes the
responsibility of their caregivers who may have little
preparation for the role. The purpose of this grounded theory
study was to examine how caregivers of

family members with HF make decisions. A nonlinear decision-
making process consisting of several actions was identified,
which included actualizing;
seeking input, information, or support; reflecting; choosing;
evaluating; and validating the decision.
Keywords: decision making; heart failure; caregiving; grounded
theory
Heart failure (HF), a complex cardiovascular syndrome, is
increasing in incidence throughout the world. In 2003, the
World Health Organization (WHO)
noted that cardiovascular disease accounted for more than 16.7
million deaths (29.2%) of all deaths worldwide with 7.2 million
of these deaths attributed to
ischemic heart disease. According to the American Heart
Association (AHA), almost 6 million Americans have HF with
more than 670,000 new patients who
are 45 years of age or older diagnosed each year (AHA, 2009).
In 2003, the Study Group on HF Awareness and Perception in
Europe (SHAPE) noted that
approximately 14 million people in Europe currently suffer from
HF and suggests that number will escalate to more than 30
million Europeans by the year
2020 as the population ages. Blackledge, Tomlinson, and Squire
(2003) predict that nearly 40% of HF patients will die within 1
year of hospitalization as
case fatality remains high and prognosis poor.
As the global population ages, the economic impact of HF on
global health systems will become even greater. Historically,
patients with HF faced rapid
deterioration and quickly died from the disease. With advances
in pharmacologic therapy and other treatment interventions to
support the failing heart, the
trajectory of illness in HF has evolved into one that is more

gradual in its progression, allowing patients to live longer, lead
more productive lives, and make
more decisions as their health status changes. When the patient
with HF is discharged from the acute care facility or
rehabilitation center, the family may
become overwhelmed with the physical and mental requirements
of care and the many decisions that must be made. Family
caregivers of patients with HF
often do not possess the skills necessary to navigate health care
systems that have become increasingly complex. Implicit in this
need to make decisions is
the ability of the caregiver to make treatment decisions or assist
with decision making at critical points as the disease
progresses. The family's ability to
cope effectively and make good treatment decisions with the
needs of the patient in mind may affect the patient's outcome
(Family Caregiver Alliance,
2009).
To assist patients with HF and their caregivers in making
treatment and care decisions, nurses must understand how the
decision process for caregivers
occurs. Caregivers have an integral and critical role throughout
the illness experience and play a crucial part in the decision-
making process; however, little
is known about how they make decisions for patients with HF.
The purpose of this study is to describe decision making by
caregivers of patients with HF. The
specific research question for this study is this: How do
caregivers of family members with HF make decisions?
CAREGIVING AND DECISION MAKING
Caring for a patient with HF is stressful and becomes more so
as the disease progresses and physical and emotional care
become more difficult. The need

for complex decision making becomes apparent. Estimates of
the numbers of family caregivers in the United States vary
based on the definitions and
criteria used. A 2004 report estimates that 22.9 million
households or 44.4 million Americans are involved in caring for
a person aged 50 and older (National
Alliance for Caregiving and the American Association for
Retired Persons, 2004). Rogers and Komisar (2003) report that
13 million adults in the United
States have chronic conditions that impair their ability to
function independently. Although there are no exact numbers of
informal caregivers of patients
with HF, it is clear that the projected numbers will increase as
the disease incidence increases in an aging society.
http://search.proquest.com.proxy.devry.edu/?accountid=147674
http://search.proquest.com.proxy.devry.edu/advanced?accountid
=147674
http://search.proquest.com.proxy.devry.edu/docview.pagelayout
:publication?t:ac=853503862/Record/354CEF3F10A4D9CPQ/6
http://search.proquest.com.proxy.devry.edu/docview.pagelayout
:browse?t:ac=853503862/Record/354CEF3F10A4D9CPQ/6
http://search.proquest.com.proxy.devry.edu/docview/853503862
/354CEF3F10A4D9CPQ/6?accountid=147674#
http://search.proquest.com.proxy.devry.edu/docview/853503862
/354CEF3F10A4D9CPQ/6?accountid=147674#
javascript:newPopup('/help/academic/webframe.html?Document
_overview.html');
http://www.springerpub.com/
http://search.proquest.com.proxy.devry.edu/indexinglinkhandler
/sng/au/Sanford,+Julie,+DNS,+RN/$N?accountid=147674
/sng/au/Townsend-
Rocchicciolli,+Judith,+PhD,+RN/$N?accountid=147674
/sng/au/Horigan,+Annie,+MSN,+RN/$N?accountid=147674

/sng/au/Hall,+Pat,+PhD,+CRNP/$N?accountid=147674
http://search.proquest.com.proxy.devry.edu/pubidlinkhandler/sn
g/pubtitle/Research+and+Theory+for+Nursing+Practice/$N/288
49/DocView/853503862/fulltext/$B/1?accountid=147674
http://search.proquest.com.proxy.devry.edu/indexingvolumeissu
elinkhandler/28849/Research+and+Theory+for+Nursing+Practic
e/02011Y04Y01$232011$3b++Vol.+25+$281$29/25/1?accounti
d=147674
The daily continuing burden of caregiving can result in negative
physical, mental, emotional, and social outcomes (Family
Caregiver Alliance, 2009). Luttik,
Jaarsman, Veeger, and Van Veldhuisen (2005) note the burden
caregivers encounter when caring for patients with HF,
suggesting that oftentimes, the
caregivers have greater physical challenges than the patient.
Caregivers have little preparation for the caregiving role and are
in great need of physical,
emotional, and respite support as well as support to make sound
decisions.
Decision Making in Caregiving
With advances in medicine, people with chronic illnesses are
living longer, many times necessitating assistance with or
abdication of the decision making to
their caregivers. As the patient's health declines, caregivers are
called on to make decisions more frequently (Hall, Sanford &
Demi, 2008). Although the
patient may have discussed their wishes or left written
documentation of their preferences for care, such requests often
do not have an impact on the
decisions that are eventually made by caregivers (Shalowitz,
Garrett-Mayer, & Wendler, 2006; Vig, Taylor, Starks, Hopley,

& Fryer-Edwards, 2006). An
understanding of how caregivers make decisions can serve to
strengthen needed support and information during the
caregiving experience.
Caregivers affect how decisions concerning the health of the
patient occur, particularly when the patient can no longer make
decisions on their own. It is
important to note that decision-making studies are more
prevalent in other chronic diseases such as cancer, dementia,
and renal failure, but few studies are
available that examine decision making in HF. This is
significant in that caregivers' decisions may ultimately affect
the entire family and may create strain on
the patient and caregivers themselves. It is often hard to
separate what is best for the patient and what is best for the
family. A major challenge that
caregivers face is making decisions for a family member who
has impaired judgment (Menne & Whitlatch, 2007).
Empirical Evidence Regarding Caregiver Decision Making.
Research has shown that shared decision making between
patient with HF and the caregiver can
lead to a better self-care. Sebern and Riegel (2009) found that
older patients with HF and caregivers who report their patient's
health as good also report
better shared communication and decision making, self-care
maintenance, and self-care confidence. However, not all
caregivers and patients want
information regarding the prognosis of the illness. Fried,
Bradley, and O'Leary (2003) studied end-of-life care in cancer
patients and found that many elders
and caregivers are unable or unwilling to accept a prognosis of
limited life expectancy despite previous reports indicating a
desire for such disclosure.
Hansen, Archbold, Stewart, Westfall, and Ganzini (2005) report

that role strain for caregivers exists during the actual decision-
making phase, as well as
during the days, months, and years prior to the event and may
continue after the decisions are made. Quinn, Dunbar, and
Higgins (2010) examined the
degree of congruence between patients with HF and their
primary caregivers on symptom assessment and self-care
management behaviors. Findings
suggest that caregiver as proxy appears to be a reasonable
substitute for patient's responses in a community setting. The
study is important in that it
validates the importance of the need for caregivers to have
specific knowledge of the disease to make the best decisions
possible.
Theoretical Evidence Regarding Caregiver Decision Making.
Examining the evidence of how caregivers and patients with HF
make decisions to engage in
self-care is also an important consideration in how decision
making occurs in HF. In a qualitative study, Clark et al. (2008)
examined individual and
contextual factors perceived by patients and their informal
caregivers that influence their willingness to undertake effective
HF self-care. This study is
significant in that it suggests that knowledge of HF is
potentially a determinant of outcomes based on the ability of
the caregiver to make decisions. A
grounded theory study by Crist, Garcia-Smith, and Phillips
(2006) examined the process by which 23 Mexican American
elders and their caregivers decided
to use formal home care services. A three-stage theory emerged
that describes the decision process to use formal home care:
taking care of our own,
acknowledging options, and becoming empowered. This study is
important in caregiving decision research in that it purports that
the Mexican American

family maintains their cultural norms while making difficult
treatment decisions. In a phenomenological study in Taiwan,
nine mothers shared their
experience of family interactions and relationships while facing
decisions about their child's heart surgery. A five-step decision
process emerged and findings
indicate the entire family experienced psychological distress,
role reorganization, and a remodeling of family functioning
(Shu-Fan, Pei-Fan, & Kai-Sheng,
2007).
Hall et al. (2008) examined moral decision making by wives of
patients with life-threatening cardiovascular disease. Using
grounded theory, factors
influencing decision making and decision-making patterns were
identified. Hall (1994) describes a five-step process of decision
making, which includes
searching, seeking, reflecting, accepting, and decision making.
This study was limited to only one specific group of caregivers
and examined decision
making retrospectively after a family member had died.
Application of this theory to concurrent decision making by
caregivers other than wives forms the
foundation for the current study.
After review of the literature and examination of possible
theories that could explain how caregivers of family members
with HF make decisions, researchers
determined that none is sufficient to explain how this group
makes decisions. As a result, these theories are used as a
sensitizing framework for the current
study. Although there is limited empirical evidence that
validates how decision making occurs between patients with HF
and their caregivers, it is clear that
the willingness, knowledge, and ability to make these decisions
is inherent in the outcomes of care.

METHODS
A qualitative design using grounded theory methods was used to
examine the process of decision making among caregivers of
patients with HF (Charmaz,
2006). After Institutional Review Board approval, 20
participants were recruited from cardiology offices, inpatient
hospital units, or adult day care facilities
over a 12-month period from 2008-2009. To ensure data
variation, five caregivers of patients with HF were interviewed
from each of the four stages of the
HF classification (Hunt et al., 2005). To qualify as a
participant, the caregiver had to be related to the patient with
HF, provide one activity of daily living,
and/or assist the care recipient with two instrumental activities
of daily living and not be paid for services. Demographic data
collected included caregiver
gender, marital status, ethnicity, employment status, income,
living arrangement, and relationship to patient with HF.
Data Collection
After informed consent was obtained, unstructured open-ended
interviews were conducted in private mutually agreed on
locations: the caregivers' homes,
places of employment, or the library. The interviews were
audiotaped and questions began broadly with statements such
as, "Tell me about your family
member's illness." As the conversation progressed, questions
specifically related to decision making were asked (see Table 1
for the interview guide). The
interviewers kept memos about the experience and took notes on
key points that needed further clarification. Interviews lasted
from 45 minutes to 2 hours,
which included time for completion of demographic data. The

sample includes 20 caregivers of family members of patients
with HF who live in the
Southeastern United States (see Table 2 for demographic
characteristics of the participants).
Data Analysis
Data were transcribed verbatim, checked for accuracy, and
entered into the NVivo qualitative software program.
Researchers independently coded the data
line by line after each interview and then met for focused
coding to develop the most salient categories of the data. The
core conceptual categories were
identified, and links between them resulted in theoretical
categories. As data were analyzed, theoretical sampling of
pertinent data was used to elaborate
and refine categories in the emerging theory until saturation was
obtained (Charmaz, 2006). Memo writing of impressions during
data collection, thoughts
during analysis, and progression to theoretical development
were completed to ensure rigor of the study. A theoretical
model was developed that describes
the process of decision making by caregivers of family members
with HF (see Figure 1). Triangulation is a method used by
qualitative researchers to
establish validity in their work (Guion, 2002). Theory
triangulation involves the use of multiple theoretical
perspectives to draw inferences or conclusions
from a set of data in an effort to validate data findings (Watson,
McKenna, Cowman, & Keady, 2008). Theory triangulation was
used to determine if the
process of decision making among participants in this study is
linked with a theory that emerged from a previous study of

decision making by wives of
patients with HF at end of life (Hall, 1994), as well as
comparing findings to current literature.
FINDINGS
The theoretical model (see Figure 1) that emerged from data
describes the process of decision making by family caregivers
of patients with HF. Generally,
caregivers make decisions through a process of phases; though
at any time, caregivers may progress through these actions in a
nonlinear fashion.
Phase 1: Actualization of Issue, Problem, or Challenge
Caregivers of patients with HF are confronted with many types
of decisions. Some decisions occur at the onset of diagnosis,
whereas others, such as when
to go to the hospital and decisions about whether to work, are
revealed as the patient continues through the disease process.
Actualization of an issue,
problem, or challenge, the realization that the caregiver has a
decision to make, seems to be especially pertinent at the point
of diagnosis. A few caregivers
note that their family member is dealing with what they thought
to be stable chronic illnesses and the diagnosis of HF itself
seems to blindside them. A 34-
year-old African American wife of a patient with Stage II HF
states, "A cardiologist came in and that was when, as we put it,
'all hell broke loose.' They told
us that he was diagnosed with HF. So, there were no prior signs
or any type of heart problems."
Actualization of a problem is experienced as a change in how
common decisions about everyday life are affected by illness.
Decisions that used to be simple

and uncomplicated now have an additional layer of complexity
due to the illness. A 26-year-old African American wife of a
patient with Class III HF shares,
"We have had to make decisions based on everything in our life.
We can't even decide on a vacation without having
considerations about his health and
ability. How long we stay, where, what devices we need."
Significant situations that emerge as challenges that caregivers
have to make decisions about
include when to access the emergency medical system, when to
go to the doctor, and how to manage medication. Contemplating
a situation when her
husband's implanted defibrillator went off, a 42- year-old White
caregiver of a patient with Stage III HF states, "Now if it had
knocked him out cold, I
wouldn't have hesitated. I would have automatically called 911.
That was what helped me make that decision." Patients with HF
who become symptomatic
need adjustment of their medications that often require
intervention by caregivers. One African American daughter who
cared for her 76-year-old mother
with Stage IV HF shares how she monitors her mother's blood
pressure and adjusts medications as instructed, "From time to
time, we change her
medication, especially when its [BP] real abnormal."
Another issue that requires decision making by almost all
caregivers interviewed includes the need to make financial and
work decisions. Caregivers often
have to face the challenge that there is no other choice for their
loved one but to seek disability. The inability to sustain
employment is in stark contrast to
their youth and the expected role of their family member and
points to the seriousness of the diagnosis. A 34-year-old
African American wife of a patient
with Stage II HF stated, "The doctors came in to tell us

everything about filing for disability . . . doctors don't come and
tell you at a young age when you're
full of life to fill out disability papers because they don't want
you on it."
Phase 2: Seeking Information, Input, or Supp ort
The next phase in the theoretical model that emerged from the
data is seeking information, input, and support. Caregivers of
patients with HF consistently
share that they need to get information, input, and support for
the decision to be made. Patient input is desired above all others
in the caregivers' need to
put the patient as the focus of the decision. Some caregivers
share that the patient is still the primary decision maker
although the caregiver often have
great influence in the choice that is made. Patient abdication of
decision making somewhat correlates with the trajectory of
illness; other times it is
dependent on the relationship between the patient and caregiver.
As caregivers assume more of the responsibility for decision
making, they are clear in
their need for information, input, and support from others. A
49-year-old White caregiver of her spouse, who has Stage II HF,
states,
Currently he is still making the majority [of decisions] but he
isn't making them alone. He knows what he wants but he doesn't
know how to get it or he
doesn't have the patience. So he comes to me, we research it
together, we talk about the decisions that need to be made, and I
talk him into what he needs
to do.
Caregivers sought to include others when making decisions and
sought support and input from many sources. A caregiver who

depends on support from
others for decision making states, "I wouldn't suggest that
anybody try to do it (make decisions) by themselves. It would
tear you apart."
Information is critical to the caregivers' ability to make
decisions, whether that choice is made with the patient or for
the patient. A 51-year-old White wife
whose husband suffers from Stage III HF shares, "Now as far as
how we make decisions, information is very important to us, we
have to have a lot of
information, medically to look at pros and cons." Another
caregiver, a 36-year-old African American whose mother has
Stage IV HF shares, "Yeah, I'm a
hairdresser so I deal with a lot of people with HF, high blood
pressure, all of these conditions . . . talking to the customers
you know I learned . . . really
talking with people and getting information."
Caregivers often share that the process of seeking information
occurs simultaneously with seeking input and support. A 38-
year-old African American wife
of a patient with Stage III HF states, "Everybody has health
issues and they kinda bounce them off of each other. They are
supportive. They are in contact a
lot." And,
We always talk to our extended family, our parents, my sister . .
. friends give us advice and guidance and support in difficult
times as well as difficult
decisions . . . We have been very much together and a
partnership. John knows everything about his condition, there
are no secrets and we both want

honest evaluation and appraisals so we can make decisions.
Caregivers are clear that support is necessary for good decision
making. They share that family, friends, and health care
providers are essential sources of
support and information. A 49-year-old White caregiver whose
husband has Stage III HF states, "You need someone that can
support you . . . someone that
can be there . . . it is like you are the go to person and you need
someone to go to and if nobody is there, that is hard."
Caregivers share that relationships
with health care providers are essential because they provide
support and understanding that is critical to the decision making
process. A 56-year-old White
caregiver whose husband has Stage II HF shares, "I have visited
doctors who were in and out [of the examination room]. But the
people that we have met
have told us what they thought, and how they intended to work
with us and deal with it." Health care providers who view the
caregiver as a partner in the
treatment plan of the patient with HF provide support and
understanding that caregiver's state is critical to the decision-
making process. An African
American caregiver whose 43-year-old husband has been
recently diagnosed with Stage III HF shares,
The nurse called after he had an echo done. She said, "Well, he
is going to have to have a pacemaker. How would you like to do
this, would you like to tell
him first, and then he come in and talk to the doctor, or would
you rather the doctor told him?" I will be forever grateful for
that, just for her to give me the
opportunity to sit down and initially break it to him.
Caregivers also share that they need to seek spiritual support
when caring and making decisions for their family members

with HF. A 55-year-old White
caregiver whose mother has Stage II HF states, "If nothing else,
find you a church and realize that you can't make someone do
something and you just
have to accept what changes they are willing to make." A 43-
year-old African American whose mother has Stage IV HF
states, "All you can do is hope and
pray that you make the right decisions, stay strong and give it
your all and try your best and take one day at a time.
Phase 3: Reflecting
For the caregivers of patients with HF, the ability to manage
what is often complex and unfamiliar information they receive
from physicians, nurses, friends,
and family is frequently frightening and involves a period of
thinking and self-reflecting prior to making a decision. As the
concept of reflection emerges in
the model, it is often employed as a means for review of how
information is received and handled. Reflection is spontaneous
in nature and allows caregivers
to assess information, examine their problem-solving ability,
and put their thoughts into an organized perspective. In
addition, reflecting via discussion with
others often illustrates selfawareness of an issue as well as
insight into a specific behavior or a "why" something is done.
One 49-year-old White caregiver,
when reflecting on how she uses information to make decisions
about her husband with Stage III HF says, "I guess the best way
I make decisions is try to
look at the big picture and long-term effects versus what it's
like right now. I can't afford to not sit down and rationally think
something out."
Phase 4: Decision Choice

After realizing that they are faced with an issue or challenge,
seeking input or support, and reflecting on their options, it
becomes apparent that about
midway through this process, caregivers have to make a
decision or a choice. One caregiver recalls how she has to make
choices about her husband's
health even though her husband with Stage II HF may feel she is
overreacting. The 42-year-old White caregiver shares, "I wanted
to call 911 but he is
hardheaded and it is hard for me to do it because if he doesn't
want me to, it stresses him out even more. Sometimes I have to
go over his head."
Phase 5: Evaluating Decision Choice
Once a decision is made, caregivers critically evaluate that
choice to determine if the right decision has been made. A 24-
year-old African American
caregiver who makes difficult treatment decisions for her
husband diagnosed with Stage IV HF evaluates her decision
choice when she shares, "That was
hard, it has really taught me to be a little bit more adult like in
my decisions. I had to figure out if I had done the right thing."
Whether the decisions relate
to managing medications, decisions about family and work, or
disease treatment, caregivers evaluate the decisions they make.
A 44-year-old daughter who
provides care for her father with Stage III HF refers to how she
evaluates her decision choice, "Just going with your gut feeling
and trying to make sure you
make the best choice. I don't care if it causes conflict. I'll just
make the decision, think about it, and be confident in the
decisions I make."
Phase 6: Seeking Validation

Seeking validation occurs at each phase of the decision-making
process of the caregivers. Validating emerges as an important
task for caregivers,
particularly in the areas of seeking information and input, and
decision choice. Some caregivers seem to second-guess their
decisions, but most caregivers
make decisions and move forward. Researchers note that
caregivers ask questions and validate information with
physicians and nurses at many points
along the disease trajectory. Family also assists with validating
decisions. A White 48-year-old daughter who provides care for
her mother with Stage II HF
reports validating information with her aunt, and although her
aunt did not assist in any actual decision making, she serves as
a sounding board, which
allows the caregiver to stay focused and on track.
Influences and Context
The process of decision making is influenced by situations,
people, relationships, and the environment. As the caregivers
describe how they make decisions,
they also share what influences their decision making. In the
background of the decisionmaking process is the context of the
caregiver and patient. Context
is the world the family lives in, and how their world influences
decision making is unique for each family. Several themes
emerge from the data regarding
influences and context that are shared by most caregivers.
The relationship between caregivers and their family member is
an essential influence on the decision-making process. A 34-
year-old African American
married participant expresses the shock at having to adjust her
expectations to this life-threatening disease when she states,

I think we are at a very young age to have to be making these
decisions. We have had a lot of crises since we have been
married. This is not the Cinderella-
type marriage I thought I would have. These are not the
decisions I thought I would be making for my husband at age
40.
Another wife, a 52-year-old White woman, shares that her
relationship with her husband who has Stage II HF has caused
them both to grow, stating, "I feel
very positive that we have the kind of relationship we do where
we talk about these things together and listen to others' advice."
Each caregiver identifies family relationships as significantly
influencing decision making. Strong relationships with family
members are consistently cited as
a positive influence, whereas difficult family relationships often
lead to stress for the caregiver and patient with HF. Sibling
relationships are frequently cited
as influential to decision making. A 47-year-old White
daughter, when discussing her sibling, shares, "There were
times I needed help and I needed to work-
she just couldn't do it. I told her right then, 'Well, you don't
ever come up here and run the show when you can't show up
now.'" An African American wife,
26 years old, whose husband is newly diagnosed with Stage III
HF has to interact with skeptical in-laws stating, "My in-laws
have his best interest at heart;
this was like a deal breaker-type of situation. All eyes on me, 'Is
she going to stick in there? Is she going to hang on?'"
Relationships with children in the
caregiver families also influence the decisions that are made. A
36-year-old White mother who cares for her husband with Stage

III HF and her 11-year-old
son says, "My love for him [son] influences the decisions I
make because he needs his Daddy."
When making decisions for patients with HF, caregivers often
express that their feelings and those of the patients' influence
the process. Caregivers share
that they are scared when making decisions. A 43-year-old
White wife of a patient with Stage IV HF describes her fear of
making the wrong decision, "I
want to make the right decisions for him. I was scared of
upsetting him more and him freaking out even more than he was
already." Caregivers report that
communication and relationships with health care providers also
influence decision making. A 43-year-old White wife of a Stage
III HF patient shares,
"Communication with the health care workers dealing with my
husband helps me make decisions."
Consistently, one of the common themes that emerge as an
influence to decision making is the financial considerations of
the family. Families struggle with
situations where patients with HF who are in their prime
working years are suddenly diagnosed and could no longer earn
an income. Caregivers also share
their frustrations with the social security disability process and
the length of time it takes to get a disability designation. These
same caregivers share that
they have difficulties working because they are afraid to leave
their family members home alone or they have frequent
absences to take their family
members to appointments. Many patients who became
unemployed have worked jobs that did not offer health
insurance benefits and the financial toll on
the family results in bankruptcy or severe financial strain.
Caregivers spoke of the costs of medication and how they make

decisions about treatment
regimens based on available resources for medication purchase.
Those caregivers and patients who have health insurance
express gratitude for the coverage. A 36-year-old African
American wife of a patient with Stage IV
HF describes viewing her husband's first hospitalization bill
when he was diagnosed with HF:
When I opened up that, I was like, I've got to be reading this
wrong. I looked at it again and I saw $114,000. I saw six figures
and tears began to roll down
my face, and I really became emotional because all I kept
thinking was, "God what if I didn't have this insurance?"
Because at one point, he was in-between
insurance and that October prior to him becoming sick, I
transferred him on to my insurance.
Though caregivers who have insurance are thankful, they still
struggle with co-pays for medication, doctor visits, and
hospitalizations. Caregivers share that
the costs of medications to manage HF are expensive and that
samples from the physician's offices often keep the patients
from not doing without their
medications. A 43-yearold White wife describes her husband's
decision to not refill his carvedilol (Coreg), "He was off of it
and I had no idea. He was out of
it and even with my $50 co-pay, he couldn't pay it, and he didn't
want to tell me. I said, 'That's your life or death.'"
CONCLUSIONS
Findings from this study highlight that the essence of decision
making by caregivers of family members with HF is a nonlinear
process consisting of several
phases including actualization of the challenge, issue, or

problem; seeking input, information, or support; reflecting on
the decision; making a decision
choice; evaluating the decision made; and validating the
decision. This study supports and validates findings from
previous studies (Crist et al., 2006; Hall
et al., 2008; Limerick, 2007; Shu-Fan et al., 2007) and expands
understanding of the difficulties family caregivers of patients
with HF encounter in making
decisions. This study suggests that each action represents an
important part of the process used by caregivers as they make
decisions for their family
member with HF.
Actualizing the decision occurs when caregivers realize that a
decision needs to be made on behalf of their family member
with HF. Many different types of
decisions are made, including those regarding medications,
treatment procedures, finances, and range from simple to
complex. Seeking information,
primarily from health care providers, is considered by
caregivers as essential to making decisions. Although caregivers
consider their family members with
HF to be the primary decision maker, when they are unable to
do so or if the family member abdicates the decision making to
the caregiver, the family
member's input is considered most important.
After caregivers gather information and receive input and
support from others, a period of conscious reflection on their
options for decision making occurs.
Decisions that caregivers are presented with are often
considered complex and frightening. At times, caregivers feel
overwhelmed with their responsibility
for decision making. Reflecting allows a time for caregivers to
organize their thoughts and carefully consider all alternatives to
avoid making ill-informed

decisions that may result in unwanted consequences, which may
be regretted later.
Understanding the possible choices, coming to terms with the
need to act, and then choosing the best option from available
alternatives enable caregivers
to make a decision for their family member. Although
caregivers frequently experience some relief in actually making
the decision, they experience many
other emotional reactions they then have to deal with. On
occasion, when one decision is made, others emerge and
caregivers have to start the whole
process over with each new decision. Simultaneous decision
making is not uncommon.
Making the right decision is important to caregivers, and after
arriving at a decision, they evaluate the decision to make sure
they have made the right one.
Seeking input and support from others as a means of validating
that they made the right choice from available alternatives is
important at this stage as
well. Although most decisions are then implemented, sometimes
alternatives present themselves, which result in making a
different choice or returning to
previous phases, especially seeking information and reflecting
prior to making the decision. In addition, guessing their
decision is not uncommon, and
validation serves to confirm for caregivers that they made the
right decision.
Decision making does not occur in a vacuum and, in the case of
decision making by caregivers of family members with HF, the
context in which the
decisions are made is an important consideration. Different

decisions are made at various points in time along the illness
continuum. There are other factors
that influence decision making such as the specific
circumstances and situations when the decisions are made,
individuals involved in the decision making
and their relationship to one another, and the environment
where the decisions are made. The most important variable
affecting decision making is the
relationship between caregivers and their family member.
Health care providers play a pivotal role in assisting caregivers
in making decisions by providing
information as well as support. Caregivers consistently express
concern for finances, which not only affect the decisions that
are made but frequently add to
the stress that caregivers experience.
Few studies have examined the decision-making process used by
caregivers of family members with HF; therefore, findings from
this study are compared
with those of prior studies that investigate caregivers' process
of decision making. Findings from this study are similar to
those described by Hall (1994);
however, the current study further expands understanding of the
process of decision making as well as specific factors affecting
the decision-making process
and the context in which it occurs for caregivers of family
members with HF. Although the five-part decisionmaking model
by Hall is validated in the current
study, findings suggest that there are additional actions
involved in the decision-making process such as actualizing the
decision when caregivers are
confronted with a decision to be made as well as evaluating and
validating the decision choices.
The previously described study by Crist et al. (2006) that
examines the process by which Mexican American elders and

their caregivers decide to use formal
home care services has commonalities with the current study.
Their stage of acknowledging options is similar to the stage of
actualizing in the current study
and likewise requires seeking input, information, or support for
the decision. What they describe as the process of becoming
empowered actually occurs for
participants in the current study during the time when they are
validating the decision. Parallels can be drawn between findings
from Shu-Fan et al. (2007)
and the current study. Families in the Shu-Fan et al. study are
shocked and confused when they learn of the child's diagnosis
of a potentially lethal
condition. Families transition through the hope that surgery
would not be necessary but concluded that it is essential for the
survival of their child. This step
in the process is similar to that of actualization in the current
study that caregivers realize there is a decision that must be
made for the health of their loved
one. Families also endeavor to make the right decision for their
child, develop a trust for health care providers, and seek support
from others who have
gone through the same experience. Caregivers of those with HF
consistently state that they need information and support from
others to make the right
decision for their family member. Further, they spend time
evaluating their decision choice to ascertain whether the right
decision has been made.
Studies that explore caregivers' decision-making process
regarding the withdrawal of life-sustaining treatments also
support the current findings. Limerick
(2007) found that there are three influencing domains that
caregivers fluctuate among when making end-of-life decisions
for their loved ones. Just as
participants in the current study seek information, input, and

Progress in Cardiovascular Nursing Winter 200818www.lejacq.docx

Progress in Cardiovascular Nursing Winter 200818www.lejacq.docx

Recommended

Recommended

More Related Content

Similar to Progress in Cardiovascular Nursing Winter 200818www.lejacq.docx

Similar to Progress in Cardiovascular Nursing Winter 200818www.lejacq.docx (20)

More from wkyra78

More from wkyra78 (20)

Recently uploaded

Recently uploaded (20)

Progress in Cardiovascular Nursing Winter 200818www.lejacq.docx