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O R I G I N A L R E S E A R C H

Effects of multidisciplinary Internet-based program on management of heart failure

Machiko R Tomita1

Bin-Min Tsai2

Nadine M Fisher1

Neeraj A Kumar1

Greg Wilding3

Kathy Stanton1

Bruce J Naughton4

1Department of Rehabilitation Science, University at Buffalo, Buffalo, New York, USA; 2Department of Occupational Therapy, I-Shou University, Taiwan; 3Department of Biostatistics, University at Buffalo, Buffalo, New York, USA; 4Department of Medicine, University at Buffalo, Buffalo, New York, USA

Objectives: To develop and test the effectiveness of an Internet-based self management program

by multidisciplinary health care professionals for patients with heart failure (HF).

Methods: The comprehensive educational material for HF was created and posted on a website.

A computer with Internet connection and computer training were provided first. A secure and

simple web-based recording system of vital signs and health behaviors and a mechanism for

feedback regarding each participant’s record were developed. A randomized controlled trial

with a one-year intervention was conducted using a total of 40 patients who were assessed three

times in their homes. An intention-to-treat analysis used multivariate statistics.

Results: The treatment group had a high (85%) adherence to the intervention. Only the

treatment group showed a significant improvement in the knowledge level (p 0.001), amount

of exercise (p = 0.001), and quality of life (p = 0.001), and reduction in HF related symptoms

(dyspnea, p = 0.001; fatigue, p = 0.003; functional emotion, p 0.001), blood pressure

(systolic, p = 0.002; diastolic, p 0.001), frequency of emergency room visit, and length of

hospital stay (both p = 0.001).

Conclusions: An effective program to change one’s behaviors in managing HF takes a

multidisciplinary approach to create and provide feedback regarding a patient’s daily record,

which can be accomplished through Internet use.

Keywords: e-health, self-management, Internet, heart failure, older adults, exercise

Correspondence: Machiko R Tomita 515 Kimball Tower, UB, 3435 Main Street, Buffalo, NY 14214, USA Tel +1 716 829 6740 Fax +1 716 829 3217 Email [email protected]

Introduction Heart failure (HF), or congestive heart failure, is a debilitating illness affecting about

five million Americans, with 550,000 new cases diagnosed each year.1 Approximately

79% of adults with HF are over 65 years of age, with a 30%–40% annual hospital-

ization rate.2 This is the most expensive illness among the population 65 years and

over due to recurring emergency room visits and hospitalizations. In 2005, in the US

alone, HF-related costs rose to $27.9 billion, a $4.7 billion increase in three years.3

This rise is likely to continue due to the rapid growth in the aging population along

with a longer life expectancy. HF is a final common pathway of various illnesses and

conditions and is usually chronic without a cure. HF, therefore, is a condition that

greatly impacts the individual and society as a whole.

One strategy for slowing decline with chronic HF is to improve daily healthy

behaviors including reducing and monitoring salt and fat intake, smoking, and

alcohol consumption, committing to regular exercise,1 medication adherence, and

maintaining a positive attitude. This strategy takes a multidisciplinary approach to

develop and individualize. Although effective, the obstacles for this intervention

have been identified: the high cost and the large amount of effort4 for providers as

well as patients.

In order to overcome these limitations, Internet use has been suggested as a means

to change daily health behavior4 by empowering a large number of patients to take

Journal of Multidisciplinary Healthcare 2009:2 13–21 © 2009 Tomita et al, publisher and licensee Dove Medical Press Ltd.This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited.

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Tomita et al

more control of their health.5 An early study with HF patients

compared the efficacy of an interactive voice response system

and interactive web-based technologies (e-health group)

to change health behavior.6 After one year of intervention,

exercise and general activities were similar for both groups,

but the e-health group had lower health care costs. A study

using a meta-analysis concluded that Internet-based health

interventions can improve behavioral outcomes such as

increased exercise time, knowledge of nutritional status,

knowledge of asthma treatment, body shape perception, and

was also effective in weight loss maintenance.7

Although Internet access is less common among older

adults than younger adults, once they use, their use pattern is

similar to that of younger adults.8,9 As rapid growth of Internet

use among older adults advances, theoretically, so do both

the opportunity and the tools to improve health practices and

improve health outcomes while reducing health costs.

A conceptual framework, Model Toward Optimal

Independence through Technological Adoption

(M-TOMITA) was formed for this study based on the Trans-

theoretical Model (TTM),10 social support theory,11 and a

mass communication theory called Uses and Gratifi cations.12

The M-TOMITA works best when individuals are already

aware of their chronic conditions and are contemplating

doing something to manage their illness but are not sure

what to do (the contemplation stage). If someone has little

knowledge of their illness and is not aware that changing

health behavior may help them, this model may not be effec-

tive. The model is an empowerment process that progresses

through stages from contemplation, preparation, and action,

to maintenance. Using the Internet method, four types

of support by health care professionals can be provided.

Informational support or education of chronic illness and

suggested health behaviors is especially important in the

initial stage but should continue all the stages. Among the

recommended health behaviors, patients will choose an

activity to focus on. Once the first activity is successfully

implemented, additional activities will be added, one by one.

After the decision regarding a particular health behavior

is made, Instrumental support should be provided via the

Internet. Through the online record-keeping system the

participant can track their own vital signs and health behav-

iors so that they can become aware of a cause (life style)

and effect (symptom and general health) relationship. The

website also provides participants and nurse monitors the

record with alerts for critical measures so that health care

providers can be notified. This record is shared with their

health care providers at office or home visits for the purpose

of monitoring as well as appraisal support to reinforce patient

motivation. Internet use, especially in the initial stage,

boosts older adults’ self-esteem. They realize their ability

to learn something new and feel they are up to date with their

children and their grandchildren. The Internet is so versatile;

it provides not only opportunities for education, but also for

frequent communication with families and friends, leisure

through playing games to stimulate and challenge the mind,

and can improve instrumental activity of daily living (IADL)

by participating in online shopping on drugs, books, and

even groceries. Mastering Internet technology, therefore,

improves the quality of life of older adults. Throughout this

process, emotional support from health care professionals is

important to keep the participants motivated until the time

that their illness prevents them from using the computer. Its

application to Internet use is described in the intervention

section of this study, and is illustrated in Figure 1.

The objectives of this study were to develop and test an

e-health intervention using a multidisciplinary approach to

improve health behavior and outcomes among older adults

with HF. Hypotheses in this study are that the treatment

group will: (1) adhere to the intervention program at a high

rate ( 75%)13; (2) improve in knowledge of HF and related

healthy behaviors; (3) reduce specific HF symptoms and

sick days, and improve blood pressure (BP), (4) improve

in perceived quality of life; and (5) reduce frequency

of emergency room visits and length of hospital stays.

Participants’ subjective evaluation of the program was also

sought. It included satisfaction/dissatisfaction, reasons for

the rating, benefit, improved or not improved HF, the most

liked/disliked part of the method, and suggestions for the

program.

Methods Study design The study employed a randomized controlled design with a

one-year intervention. Three assessments (baseline, and fol-

low-ups at six and 12 months) were conducted in participants’

homes. The control group received usual care. Usual care

for home-based patients in the US is a three-month regular

check up with their physicians. If they are hospitalized, they

may have nurse visits, physical or occupational therapists’

home care, and phone calls from their insurance company

to report their weight and blood pressure for three months.

None of the partisans were receiving nurse visits due to

hospitalization. The treatment group received the e-health

intervention in addition to usual care, and process measures

were collected daily.

Journal of Multidisciplinary Healthcare 2009:2 14

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Effects of e-health in patients with heart failure

Health care professional

Emotional support

Informational support

Instrumental Support

Appraisal support

E-Health

Precontemplation Contemplation Preparation Action Maintenance

Figure 1 Model toward optimal management of independence through technological adoption.

Subjects Individuals with HF were recruited from three hospitals and

two health insurance companies in Western New York using

a convenience sampling method. Inclusion criteria were those

who: (1) were living at home and 60 years of age or older;

(2) had at least one emergency room visit or overnight hospital

admission due to HF in the past year; and (3) met the New York

Heart Association (NYHA) Classification of Heart Failure for

Class II (Slight limitation of activity or dyspnea and fatigue

with moderate physical activity) or Class III (Marked limita-

tions of activity or dyspnea with minimal activity).14 Exclusion

criteria were individuals who: (1) were scheduled for any kind

of heart surgery and/or (2) had cognitive impairment (Mini

Mental State Exam [MMSE] 24).15

The sample size, determined by a power analysis to

achieve 80% of power at α 1

= 0.05 with a large effect size

(d = 0.90)16 was 15 in each group. Considering a high attrition

rate anticipated for the control group, 24 in the control group

and 16 in the treatment group were recruited. The sample

size flow-chart is included in Figure 2.

Intervention Technology Participants in the treatment group were provided a standard

PC with Internet access as well as basic computer training.

Publicly accessible and secured websites were created by a

multidisciplinary health care team of a health behaviorist,

a geriatric physician, a geriatric nurse, an occupational

therapist, a physical therapist, and an exercise physiologist.

We used the web creation guidelines published by the National

Institute on Aging and the National Library of Medicine.17

Four types of support (informational, instrumental, appraisal,

and emotional) at suitable stages of behavioral changes were

provided in this e-health intervention.

Informational support included online information on:

HF, drugs used to treat HF, effects of alcohol and smoking,

depression, prescribed home exercise, nutrition, weight

management, and exercise in general using the Flesch–

Kincaid Reading Grade level of eight on average. An exercise

instruction program (walking, breathing, stretching, range

of motion, upper and lower extremity strength training, and

stationary biking) was developed and delivered via streaming

video. This support was provided in the beginning of the

intervention period.

Instrumental support included availability of a secure,

simple, and short online recording system using Lotus

Notes Web Server 6.5. This support was provided after

participants became comfortable with the use of a computer

and Internet. Participants were asked to access the website

daily to record their vital signs and health behaviors. The

site asks questions about blood pressure, pulse, weight,

medication use, type and amount of exercise, levels of

fatigue, intake of salt, sugar, alcohol, and tobacco, health

changes, and HF-specific questions regarding swelling,

Journal of Multidisciplinary Healthcare 2009:2 15

Tomita et al

Assessed for eligibility (N = 262)

Enrolled

Excluded (n = 220)

• Not meeting inclusion criteria (n = 69)

• No response (n = 129)

• Refused to participate (n = 20) • Family’s refusal to participate

Allocated to control (n = 24) Allocated to intervention (n = 16)

Randomized (N = 40)

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Lost to follow-up (n = 5)

• Died (n = 2)

• Nursing home placement (n =2)

• Quit: too sick due to CHF (n = 1)

Lost to follow-up (n = 3)

• Died (n = 1)

• Moved to assistive living (n = 1)

• Noncompliant (n = 1)

Figure 2 Flow chart of sample sizes.

fatigue, and dyspnea. Additionally, a webpage containing

their past records with an automatic alerting function for

sudden weight gain was available. Any overnight gain of 3

lbs or more resulted in a red dot display in the record that

signaled participants to contact their physician.

Appraisal support was provided via email every month

from appropriate health care professionals in dealing with

subjects for the purpose of feedback for patients’ records.

This support was provided to encourage participant’s ongo-

ing actions for changing their health behaviors toward a

maintenance stage (beyond six months).

Emotional support was provided on an as needed basis

via email. Since no participants were depressed ( 15 Center

of Epidemiological Study- Disease18) at the time of initial

assessment, an online discussion group was not formed.

Dependent variables A knowledge questionnaire was developed for this study

consisting of 20 questions with a possible total score ranging

from 0 to 60 (all correct responses). Frequency of exercise

was captured on a nominal scale (every day, 2–3 times/week,

less than once/week, rarely and none) for breathing exercise,

Journal of Multidisciplinary Healthcare 2009:2 16

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Effects of e-health in patients with heart failure

stretching, walking, and mild exercise including stationary Table 1 Baseline demographic and health characteristics (N = 40)

biking, swimming, and golfi ng.

HF-specific symptoms (dyspnea during daily activities,

fatigue, and emotional function) were measured using the Con-

gestive Heart Failure Questionnaire (CHFQ).19 Higher scores

are indicators of better conditions. The psychometric of CHFQ

has been tested. It has good reproducibility for the total score

and the three subcategories and responsiveness for change.20

The responsiveness was found to be similar to the Minnesota

Living with Heart Failure21 and better then SF 12.22,23

Perceived quality of life (QOL) was assessed using

a 50-item age relevant questionnaire on diet, health care,

safety, social, communication, psychological health,

activities, and perceived aging, with a higher score indicating

a higher level of wellness.

Statistical methods An intention-to-treat analysis was conducted using mostly a

multivariate linear model. To explain the observed variability

in the data and test for differences within and between

groups, the model was fit to numeric endpoints via restricted

maximum likelihood methods, adjusting to the difference

for the severity of illness. To analyze health care use, actual

data of those whose data were available at follow-up 2, due

to nonnormal distributions, Friedman’s Tests for correlated

samples were used. A significance level of 0.05 was set for

each hypothesis test. SAS version 9.1.3 statistics software

(SAS Inc., Cary, NC) was used for all analyses.

Results Demographic and health information at baseline for

40 participants is summarized in Table 1. The two groups were

equivalent for all characteristics. An overall mean age was

76.2 years, 32.5% were males, 2.5% were Asian, 12.5% were

African American/Black, and 85.0% were Caucasian. Fifty-eight

percent had 12 years of education or less, 36.7% had between

13 and 16 years, and 5.4% had 17 years or more. Mean MMSE

score was 29 of 30. The mean number of comorbidity was

10 and medication taken was 8. The control group was comprised

of 79.2% of patients with NYNA Level II and 20.8% of Level

III while the treatment group had 75% and 25%, respectively.

Although statistically not significant, this difference was adjusted

in the multivariate linear approach. The control group had

5.1 years of HF while the treatment group, 3.6 years.

Adherence to the program (Hypothesis 1) All participants in the treatment group visited the

publicly available website with a mean frequency of 3.5

Variable Control Treatment Difference

(n = 24) (n = 16) values

Age (years) M = 77.5 M = 74.2 t = 1.240

SD = 7.4 SD = 9.7 p = 0.223

Gender

Male 9 (37.5%) 4 (25.0%) χ2 = 0.624

Female 15 (62.5%) 12 (75.0%) p = 0.408

Race

Asian 0 1 (6.3%) χ2 = 1.544

African American/Black 3 (12.5%) 2 (12.5%) p = 0.462

Caucasian 21 (87.5%) 13 (81.3%)

Education

12 years 13 (54.2%) 9 (56.3%) χ2 = 0.430

13–16 years 8 (33.3%) 6 (37.5%) p = 0.806

17 yeas 3 (12.5%) 1 (6.3%)

Living status

Live alone 9 (37.5%) 8 (50.0%) χ2 = 0.614

Live with someone 15 (62.5%) 8 (50.0%) p = 0.433

Income

$10,000 4 (16.7%) 4 (25.5%) χ2 = 0.556

$10,000–$29,999 12 (50.0%) 8 (50.0%) P = 0.757

$30,000 8 (33.3%) 4 (25.0%)

Number of comorbidities M = 9.5 M = 8.7 t = 1.746

SD = 3.1 SD = 3.5 p = 0.099

Number of medications M = 8.4 M = 7.1 t = 1.358

SD = 2.5 SD = 2.9 p = 0.218

MMSE M = 28.9 M = 28.9 t = 0.228

SD = 1.5 SD = 1.3 p = 0.821

NYHA Class

II 19 (79.2%) 12 (75.0%) χ2 = 0.096

III 5 (20.8%) 4 (25.0%) p = 0.757

Years since diagnosed M = 5.1 M = 3.6 t = 1.273

SD = 4.3 SD = 3.0 p = 0.211

times a month and recorded daily vital signs and health

activities a mean of 85% of the days in one year which is

considered high.

The number of exercisers was analyzed using a nominal

binary scale: exercisers (exercising 2–3 times/week or

more) and nonexercisers (exercising 1 time/week or less).

The change in percentage of exercisers for three time

points for various exercises is summarized in Figure 3.

For any exercises, there were no significant changes for

the control group during the study while the treatment

group showed significant increases in all exercises

Journal of Multidisciplinary Healthcare 2009:2 17

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Tomita et al

12 mon.

100

90

80

70

60

50

40

30

20

10

0

Initial 6 mon.

Figure 3 Percent changes in exercisers (2–3/week or more). Abbreviations: C, the control group; T, the treatment group; Breath, breathing exercise;Walk, walking; Mild, mild exercise.

after one year. At 12 months the percentage of exercisers

increased to 92% for both breathing and stretching, 54%

for mild exercise, and 100% for walking. At 12 months,

significant differences were found between the two groups

for all exercises.

Knowledge of HF and related health behaviors (Hypothesis 2) At baseline, the control group had higher knowledge scores

than the treatment group, but at six months, the treatment

group increased their knowledge level surpassing the control

group, and maintained the trend at 12 months. At both six and

12 months, the treatment group was significantly higher than

the control group (both p 0.05). Descriptive statistics, change

scores, and p-values for within-group change and between

group differences for Hypotheses 2 through 5 are presented

in Table 2.

HF-specific symptoms and general health indicators (Hypothesis 3) For dyspnea, the control group, which initially scored better

(23.5) than the treatment group (18.5) worsened gradually.

The treatment group showed improvement with signifi cance

at six and 12 months (both p = 0.001). For fatigue, the control

group showed significantly lower levels of fatigue at six

months, then showed a significant increase at 12 months

(p = 0.011). The treatment group recorded greater fatigue at

C-Breath

T-Breath

C-Stretch

T-Stretch

C-Walk

T-Walk

C-Mild

T-Mild

six months but felt less tired at 12 months as compared to the

baseline (p = 0.002). These changes were both signifi cant.

For emotional function, the control group showed

significant gradual decrease over one year (p = 0.001),

while the treatment group exhibited signifi cant gradual

improvement (p 0.001).

Elevated BP was observed in both groups during the

year. The control group’s systolic BP decreased signifi cantly

initially, but rebounded to significantly higher levels at

12 months relative to baseline readings (p = 0.003). While

initially much higher than the control group, the treatment

group’s systolic BP significantly decreased by six months

and remained lower at 12 months (p = 0.010). Regarding

diastolic BP, both groups decreased signifi cantly.

For the treatment group, the number of people who

were sick less than one week in the past six months was

significantly increased at six months and 12 months.

QOL (Hypothesis 4) Although both groups increased the QOL scores signifi cantly for

the first six months and maintained for another six months, the

treatment group had greater gains at both follow-ups, resulting

in significant between groups differences (p 0.05).

Health care utilization (Hypothesis 5) For the control group, health care use did not change. For

the treatment group, the number of visits to an emergency

Journal of Multidisciplinary Healthcare 2009:2 18

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Effects of e-health in patients with heart failure

Table 2 Change over one year in heart failure-related symptoms, blood pressure, and weight

Outcome Baseline M and (SD) Changes score Change score p-values for estimated p-values for difference measure in six months in 12 months change for six and between the two groups

12 months at six and 12 months

Knowledge

Control 35.5 (14.0) 1.9 (4.4) 1.5 (5.7) 6: 0.021 6: 0.027

12: 0.022

Treatment 32.6 (12.5) 10.9 (11.0) 13.8 (8.8) 6: 0.001 12: 0.012

12: 0.001

CHFQ

Dyspnea

Control 20.9 (6.6) 1.2 (4.6) 1.4 (5.6) 6: 0.004 6: 0.721

12: 0.004

Treatment 20.3 (6.1) 3.7 (6.2) 4.4 (4.8) 6: 0.001 12: 0.942

12: 0.001

CHFQ

Fatigue

Control 16.2 (3.4) 0.05 (2.3) −0.32 (3.1) 6: 0.009 6: 0.482

12: 0.014

Treatment 15.6 (2.9) −0.13 (3.1) 0.77 (4.0) 6: 0.007 12: 0.446

12: 0.003

CHFQ

Emotion

Control 31.4 (5.3) −0.35 (4.0) −0.79 (4.9) 6: 0.001 6: 0.305

12: 0.001

Treatment 31.8 (4.4) 0.75 (4.6) 2.0 (4.5) 6: 0.001 12: 0.032

12: 0.001

Blood Pressure (mmHg)

Systolic

Control 123.9 (26.9) −0.85 10.6 6: 0.001 6: 0.512

(16.6) (24.0) 12: 0.001

Treatment 136.9 (22.8) −8.7 −10.3 6: 0.001 12: 0.391

(12.8) (15.5) 12: 0.002

Diastolic

Control 76.9 (16.0) −3.7 −6. 5 6: 0.001 6: 0.803

(10.22) (21.2) 12: 0.001

Treatment 83.2 (23.4) −7.6 −13.9 6: 0.001 12: 0.609

(19.53) (23.0) 12: 0.001

QOL

Control 196.0 (18.5) 1.05 6.8 6: 0.005 6: 0.019

(10.7) (22.1) 12: 0.003

Treatment 202.7 (23.6) 9.1 14.2 6: 0.001 12: 0.247

(15.2) (15.3) 12: 0.001

Notes: For weight, McNemar Test was used.The last column presents Z-score and p-value.

Journal of Multidisciplinary Healthcare 2009:2 19

Tomita et al

Table 3 Health care utilization

Baseline Six months 12 months Difference (for six months) (for six months) (for six months) p-value

Emergency Room Use (times)

Control 1.05 ± 1.72 0.58 ± 1.43 0.79 ± 1.32 (0.541)

Treatment 1.31 ± 1.80 0.23 ± 0.60 0.31± 0.63 (0.015)

Hospital Stay (days)

Control 10.74 ± 21.38 0.84 ± 1.89 2.42 ± 5.07 (0.232)

Treatment 6.85 ± 11.83 1.00 ± 2.45 1.23 ± 2.55 (0.040)

room and the length of hospital stay decreased signifi cantly

at six months; this was maintained at 12 months.

Participants’ evaluation of the e-health program At the end of the study period, 100% of the treatment group

reported that they were confident in dealing with HF due to

the e-health program and said that they would recommend

the program to other people who have similar conditions.

Furthermore, 84.6% said that they were very satisfi ed with

the system, 15.4% were satisfied, and 92.3% thought that

their HF was better than one year before. The most often

cited reason for satisfaction was “Monitoring myself for

increased awareness.” The second and third reasons were

“Better health” and “Support from health care providers.”

Two participants reported that the most disliked part of the

program was “Feel guilty when I have to record that I did

not exercise, so I had to do exercise.” Two suggestions were

“Expand the program to diabetes” and “Create a way to fi nd

out how other study participants are doing, so that I know

my relative status.”

Discussion This randomized controlled study tested a e-health method

of self-management of HF for one year in home-based older

adults. Four types of support were delivered via Internet by a

team of multidisciplinary health care professionals. Although

this e-health method may not be effective for all HF patients,

it was beneficial for HF patients with NYHA Class II or III

with respect to increasing knowledge of HF and related health

behaviors, exercise time, emotional function, and quality of

life, and reducing levels of dyspnea, fatigue, blood pressure,

and sick days. The result of exercise was parallel to the fi nding

of the meta analysis by Wantland and colleagues.7 It was also

effective in decreasing the number of emergency room visits

and length of hospital stays. Limitation of the study was that

it did not calculate cost effectiveness of the e-health method,

which is necessary for its practical application. Also many

between-group comparisons were not statistically signifi cant

mainly due to the small sample size. On the other hand, with

this small sample size, most of within-group comparisons

were significant, which is a strong indicator that the interven-

tion was effective. With a larger sample size, it is expected

that many between-group comparisons would be statistically

significant. Vigorous studies with geographical and ethnical

diversity are also needed in the future. Nevertheless, this

study provided evidence that the effective e-health method

in changing health behaviors and improving health outcomes

takes an interdisciplinary approach since changing one’s

health behaviors covers various health care disciplines.

Major e-health strategies that lead to successful health

behavior change identified in this study are that: (1) relevant

information should be provided using easy-to-understand

language in an easy-to-see format; (2) a simple recording

system for vital signs and health behaviors should be available

to allow patients to be aware of their behaviors; (3) patients

should be aware that their health activities are monitored by

a health professional; and (4) feedback should be provided

for continued health behavior change. The strategy was

supported by a conceptual framework, M-TOMITA, which

applied a concept of human social support to the Internet use

by strategically placing the types of support in the stages of

health behavioral change. In this model, a multi disciplinary

team is necessary at the initial stage but once the program is

in place, a nurse may be able to run the program with input

from the team for appraisal. In this study we convened a

regular distance team meeting every month for appraisal

support, but this frequency should be further investigated for

its validity. For a comprehensive self-management program,

it is strongly recommended to include a pharmacist to check

interactions of multiple medication intake and a nutritionist

for better diet.

In this study, emotional support was not independent of

appraisal and instrumental support, but was not provided in

Journal of Multidisciplinary Healthcare 2009:2 20

Effects of e-health in patients with heart failure

a specific manner, such as forming a discussion/chat group.

For patients who are not depressed or believe that they have

control over their illness, the level of emotional support

provided in this study may be sufficient. However, especially

for patients who are depressed, the Internet-based method

has been utilized and its effectiveness has been reported.24,25

Subjective evaluation of this program found that some par-

ticipants wished to know their health behaviors in relation

to other participants’. Providing an average of aggregated

data of all study participants can be easily done via the

Internet. TTM describes a process of behavioral change

called social liberalization as the person’s realization of

changes of social norms. E-health may be able to create a

social norm among study participants and allow them to see

how it is changing.

Finally, evidenced by a very high adherence to the

program, 85% of 355 days (Internet was not available for

10 days), an e-health approach utilizing a multidisciplinary

health care team can be accepted as a tool for self-management

of HF and other chronic diseases in the near future when

technology is more advanced, computer costs are reduced,

and older adults become more computer literate.

Disclosure This study was funded by the National Institute on Aging,

USA.

Reference 1. American Heart Association. Heart Failure. Heart and stroke Statistical

Update [updated 2007]. Cited on Oct 31, 2008. Available from: http:// www.americanheart.org/presenter.jhtml?identifi er=1486.

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3. The Joint Commission; The Joint Commission’s Annual Report on Quality. Heart Failure. Improving American’s Hospitals [updated 2007]. Cited on Oct 31, 2008. Available from: http//www.jointcommissionreport. org/conditions/heartfi lure.aspx.

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Journal of Multidisciplinary Healthcare 2009:2 21

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