# Telemedicine Facilitates CHF Home Health Care for Those with Systolic Dysfunction

Authors: Pennie S. Seibert; Tiffany A. Whitmore; Carin Patterson; Patrick D. Parker; Caitlin Otto; Jean Basom; Nichole Whitener; Christian G. Zimmerman
Journal: International Journal of Telemedicine and Applications
 (2008)

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## Abstract

An estimated 5 million Americans have congestive heart failure (CHF) and one in five over the age of 40 will develop CHF. There are numerous examples of CHF patients living beyond the years normally expected for people with the disease, usually attributed to taking an active role in disease management. A relatively new alternative for CHF outpatient care is telemedicine and e-health. We investigated the effects of a 6-week in-home telemedicine education and monitoring program for those with systolic dysfunction on the utilization of health care resources. We also measured the effects of the unit 4.5 months after its removal (a total of 6 months post introduction of the unit into the home). Concurrently, we assessed participants' perceptions of the value of having a telemedicine unit. Participants in the telemedicine group reported weighing more times a week with less variability than did the control group.  Telemedicine led to a reduction in physician and emergency department visits and those in the experimental group reported the unit facilitating self-care, though this was not significantly different from the control group (possibly due to small sample size). These findings suggest a possibility for improvement in control of CHF when telemedicine is implemented. Our review of the literature also supports the role of telemedicine in facilitating home health care and self-management for CHF patients. There are many challenges still to be addressed before this potential can be reached and further research is needed to identify opportunities in telemedicine.


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## Body

## 1. Introduction

The American Heart Association reports that
one in five Americans over the age of 40 will develop congestive heart failure
(CHF) [1]. This common clinical syndrome is among the top
diagnostic-related
groups (DRGs), and is a leading cause of hospitalizations and
rehospitalization in industrialized countries [2]. Outcomes related to heart
failure remain relatively poor, despite advances in pharmacological therapy and
medical care [3]. Caring for
CHF patients is particularly expensive because of high rates of
readmissions. As the vast baby boomer
population ages, all age-related illnesses will increase in prevalence [4].
CHF is no exception: its prevalence and high medical resource
consumption will continue to increase [5].CHF is a chronic condition
where appropriate disease management is critical [6]. Effective disease management requires the
patient to take an active role in his/her health. Indeed, CHF is an area where patient
empowerment medicine is of particular importance. Unfortunately, many with CHF do not
successfully manage their disease; thus, rehospitalization and high mortality
rates prevail. Frequent communication
between the patient and health care professionals, intensive education programs,
and home health monitoring can help reduce hospitalizations and mortality rates
[7]. Despite the dismal
prognosis, there are numerous examples of CHF patients living beyond the years
normally expected for people with the disease.
These successes are usually attributed to patients taking an active role
in disease management, facilitated by appropriate diet, exercise, daily
self-measurement (e.g., weight scales and blood pressure devices), medication
compliance, education, recognition of disease-related symptoms, and support
from health care professionals [8–11].Experts agree that
outpatient care is important in achieving the best possible outcomes for
patients with CHF, viable forms are currently being investigated and debated
[12]. Research has demonstrated that home health nurse visits following
discharge can improve CHF outcomes and reduce rehospitalizations. However, individualized care costs are high
[13]. Also, the numbers of qualified
nurses are diminishing while the need for nurses is growing exponentially. A relatively new alternative for CHF
outpatient care is telemedicine and e-health.
Studies show that this approach can achieve similar results to that of
home health nurse visits [14] by improving outcomes
[2, 15] and
quality of life [16], and potentially reducing readmission and
morbidity rates [17]. Telemedicine
offers the added benefit of reducing costs, without sacrificing the level of
care [2, 15].
Accordingly, we designed a home-monitoring program to investigate
the value added by having a 6-week in-home telemedicine unit for people
diagnosed with CHF systolic dysfunction.
We also measured the effects of the unit 4.5 months after its removal (a
total of 6 months post introduction of the unit into the home). We intended to find a significant difference
in the number of calls and visits to the physician, emergency department
visits, hospitalizations, and New York Heart Association (NYHA) classification
scores postintervention. We also
intended to find the home monitoring system increased the number of times the
patient weighed themselves per week, compared to the control group.Further, the potential for
telemedicine and e-health is particularly promising for those living in rural
areas where health care access is diminished [18]. Most communities in the state of Idaho
are considered
rural and could particularly benefit from telemedicine and e-health
programs. As is the case across the USA, Idaho
has a significant number of people with CHF who need assistance in managing
their disease.


## 2. Materials and Methods

This study investigated the
efficacy of a 6-week in-home telemedicine monitoring program, as well as
measured whether the program would retain effectiveness during a 6-month period
by comparing health care utilization scores.
The utilization of health care was determined by the number of times
participants contacted and visited physicians, emergency department visits, and
hospitalizations. The patients were also
assessed based on the number of times they weighed themselves per week, and
NYHA scores pre and post experimental period.
In addition, participants' perceptions of the value of having a
telemedicine unit were also obtained.Patients
who met the criteria (refer to Table1) and agreed to participate were
interviewed by a research nurse at which time the project, confidentiality
measures, and informed consent were presented.
Each patient was provided a copy of the
Learning to Live with Heart Failure Self-Care Handbook, an
educational booklet describing the disease, possible medications, dietary
restrictions, exercise suggestions, therapies, and local support groups.
Participants were then assigned to either the telemedicine or control group and
given study identification numbers. The
control group's active participation ended until the 6-month follow-up survey
to calculate the health care utilization score.
The experimental group participated in a 6-week monitoring period and
answered a follow-up survey 4.5 months after the monitoring period was completed
(i.e., 6 months from the start of their participation).Table 1
Selection criteria.
Inclusion criteriaExclusion criteriaDocumented CHF due to systolic dysfunctionCHF was caused by diastolic dysfunctionIs on renal dialysisCHF with a New York heart classification (NYHC) of II–IVHas dementia or another uncontrolled psychiatric disorder that can interfere with his/her ability to participateDocumented EF (ejection fraction) <40% by echo, nuclear medicine, or CCL within 6 months of enrollmentAnticipated survival from a non-CHF cause is less than 6 monthsCan read and speak EnglishParticipated in another heart failure research protocol within the previous 6 monthsHas an active phone line in his/her homeCurrently receives home health nursing servicesHas had a heart transplantIs able to give his/her own informed consentIf pregnant or of child-bearing age and is trying to become pregnantLives at home; is 18 years or olderIs blind, unable to use his/her upper extremities,
or has any physical condition that
may inhibit him/her from viewing and/or using a computer screenParticipants
in the telemedicine group were instructed to complete a monitoring session each
morning for the 6-week period. A daily
monitoring session included weighing on
a scale and answering a health questionnaire. If there was a weight gain or
loss of≥3
pounds overnight, or a weight gain or loss of
≥5 pounds over one week, the participant was prompted to contact their
physician. Likewise, alerts were
incorporated into the health questionnaire to notify the participant of signs
and symptoms that should be reported. No
participant weights or responses to the health questions were sent from the
monitoring system to the research team.
The research team only tracked whether or not the participant interacted
with the monitor on a daily basis. The
participants were also instructed to call the research nurse if he/she would be
unable to complete monitoring sessions for more than 2 days. Queries obtained from the
telemedicine unit highlighted participants who had not completed monitoring for 3 or more
days. These patients were contacted to
determine why monitoring was not completed.
Following the 6-week program the equipment was removed from the home and
the participant completed a telemedicine satisfaction survey with the research
staff.A chart review was conducted and a phone interview was completed by the research
team 6 months from initial start date.
Information was obtained regarding the number of times the patient
contacted the physician's office, was seen by the physician, was seen in the
emergency department, and/or admitted to the hospital. Further information was obtained regarding
the number of times a patient weighed themselves a week.The
telemedicine unit was ViTel Net's DataGate system, which included a notebook
PC, a touch-screen monitor, and a scale. The notebook PC dimensions were
approximately 9.3 inches by 6.9 inches by 2 inches. The monitor dimensions were
approximately 12 inches by 9 inches by 3 inches. The A&D LifeSource MD
Digital Scale UC-321PL scale was used to measure the weight in 1/10 pound
increments, up to a maximum of 450 pounds. The weight value was sent via the
RS232 port.The PC
unit connected to a standard electrical wall outlet. The system was very
user friendly, including a 12 inch color touch screen with simple
point-and-click buttons for presenting educational material, audio prompts, and
custom workflow sequences (ViTel Net Description). Once the telemedicine unit was installed in
the participant's home, they received the telemedicine participant information
packet, which contained instructions for use and care of the equipment, a
troubleshooting guide, and research contact information (names and phone
numbers) for the research nurse, principal investigator, and project
manager. The participant received
instruction on the equipment and then was asked to demonstrate appropriate use
of the equipment to complete the training session.


## 3. Results

Of the 23 participants, 13
people received the telemedicine program (age 50–81, mean 66.08; 8 male, 5
female; 69% married; 100% Caucasian) and 10 people (age 55–90, mean 71.00; 8
male, 2 female; 80% married; 100% Caucasian) were in the control group. As was our intention, the two groups were similar
in age, sex, marital status, years of education, and NYHA classification scores (refer to Table2).Table 2
Participant information (means).
TelemedicineControlAge66±9.171±13Years of education13.6±313.8±1.7Martial statusSingle20Married98Divorced10Widowed12New York heart classification, start of study3.5±0.73.11±0.8New York heart classification, end of study3.6±0.73±0.7


### 3.1. Comparisons: Telemedicine Group Versus Control Group

We compared telemedicine and control group health
care utilization scores using t-tests and chi-square
according to variable type and
found no statistical significance.
Descriptive statistic analysis revealed a pattern of data that suggests
the possibility of reaching statistical significance if the sample size were
greater. For example, examination of
percentages of contacts to physician, physician visits, and emergency
department visits conveyed a pattern of higher scores (though not statistically
reliable) for the control group (refer to Figure1 and
Table 3). Additionally, people in the telemedicine
group reported weighing more times a week with less variability (standard
deviation) than did the control group (refer to Table 3). An unexpected result was the higher rate of
hospitalizations in the telemedicine group (refer to Table 3). A possible explanation could increase
awareness and observation of CHF symptoms, though this was not directly
assessed.Table 3
Control and telemedicine patient utilization of healthcare services.
Control groupTelemedicine groupContact physicianNumber of visitsPercentageNumber of  visitsPercentage037.5 Percentage038.5125.0 Percentage138.5212.5 Percentage47.7312.5 Percentage57.71312.5 Percentage97.7Visit physicianNumber of  visitsPercentageNumber of  visitsPercentage112.5 Percentage016.7 Percentage237.5 Percentage125.0 Percentage312.5 Percentage233.3 Percentage412.5 Percentage38.3 Percentage612.5 Percentage58.3 Percentage912.5 Percentage78.3 PercentageEmergency departmentNumber of  visitsPercentageNumber of  visitsPercentage128.6 Percentage115.4 PercentageHospitalizedNumber of  timesPercentageNumber of  timesPercentage214.3 Percentage123.1 Percentage——223.1 PercentageWeigh per weekMean = 3.81Mean = 4.94Standard deviation = 3.69Standard deviation = 2.31Figure 1
Percent of patients who contacted
their physician (CP), visited their physician (PV), utilized
the emergency department (ED), and/or were hospitalized (Hos).


### 3.2. Reports from the Telemedicine Group

We analyzed information
regarding the experience of being in the telemedicine group and found that
despite nearly half (46%) of the participants reporting no previous experience
with computing systems, all but one of the participant reports were positive. The person who did not have a positive
experience indicated that “the telemedicine unit made her worry too much about
her condition so it stressed her heart.”
When asked the open-ended question of what participants liked best about
having the telemedicine unit in their home, the majority indicated that the
unit helped them be aware of factors important for managing their disease and
helped them to control and be more aware of their weight. Seventy-five percent of participants
indicated they would like to continue using the unit. Though we are unsure why
25% did not wish to continue, some reported complaints were
“repetitive lessons,” “redundant questions,” and
“would be more effective if interaction was involved.”  The data analysis revealed numerous ways by which the
telemedicine unit facilitated self-care. Spearman's rho correlation revealed
significant correlates between improved self-care and usage of the telemedicine
unit. For example, those who believed that having the telemedicine unit in their home will help them take better care of  themselves in the future were highly correlated with better understanding their
conditions,rs=.854, P<.001; and with identifying
important symptoms, rs=.753, P<.001. Those who believed that the unit helped them
better understand their condition were highly correlated with taking their
medications daily, rs=.952, P<.001; and limiting their intake of salt,
rs=.762, P<.001. Also, those who would recommend use of the
telemedicine unit were highly correlated with staying healthier,
rs=.855, P<.001; taking medications daily,
rs=.999, P<.001; and calling to seek help,
rs=.852, P<.001. For all correlations concerning facilitation
of self-care and perspectives regarding the telemedicine unit, see
Tables 4 and 5, respectively.Table 4
Facilitation of self-care correlates.
VariablesSpearman's rhoHelped take better care of selfLiked unit in home0.752(a)Will help take care of self in the future0.887(a)Better understand condition0.665(b)Recommend telemedicine unit0.795(a)Taking medications daily0.827(a)Important symptoms0.760(a)Use unit again0.751(b)Will help take care of self in the futureLiked unit in home0.911(a)Better understand condition0.854(a)Recommend telemedicine unit0.924(a)Limit salt0.712(a)Taking medications daily0.934(a)Important symptoms0.753(a)Call to seek help0.739(a)Stay healthier0.753(a)Use unit again0.777(a)Better understand conditionLiked unit in home0.722(a)Recommend telemedicine unit0.928(a)Limit salt0.762(a)Taking medications daily0.925(a)Important symptoms0.622(b)Call to seek help0.868(a)Stay healthier0.870(a)Use unit again0.707(b)(a)P<.001;(b)P<.05Table 5
Correlates: perspectives regarding the telemedicine unit.
VariablesSpearman's rhoLiked unit in homeHelped take better care of self0.752(a)Satisfied with training0.738(a)Will help take care of self in the future0.911(a)Better understand condition0.722(a)Recommend unit0.890(a)Limit salt0.648(b)Taking medications daily0.891(a)Important symptoms0.775(a)Call/seek help0.771(a)Stay healthier0.724(a)Use unit again0.818(a)Recommend unitHelped take better care of self0.795(a)Will help take care of self in the future0.924(a)Better understand condition0.928(a)Limit salt0.741(a)Taking medications daily0.999(a)Important symptoms0.714(a)Call/seek help0.852(a)Stay healthier0.855(a)Use unit again0.811(a)(a)P<.001;(b)P<.05


## 3.1. Comparisons: Telemedicine Group Versus Control Group

We compared telemedicine and control group health
care utilization scores using t-tests and chi-square
according to variable type and
found no statistical significance.
Descriptive statistic analysis revealed a pattern of data that suggests
the possibility of reaching statistical significance if the sample size were
greater. For example, examination of
percentages of contacts to physician, physician visits, and emergency
department visits conveyed a pattern of higher scores (though not statistically
reliable) for the control group (refer to Figure1 and
Table 3). Additionally, people in the telemedicine
group reported weighing more times a week with less variability (standard
deviation) than did the control group (refer to Table 3). An unexpected result was the higher rate of
hospitalizations in the telemedicine group (refer to Table 3). A possible explanation could increase
awareness and observation of CHF symptoms, though this was not directly
assessed.Table 3
Control and telemedicine patient utilization of healthcare services.
Control groupTelemedicine groupContact physicianNumber of visitsPercentageNumber of  visitsPercentage037.5 Percentage038.5125.0 Percentage138.5212.5 Percentage47.7312.5 Percentage57.71312.5 Percentage97.7Visit physicianNumber of  visitsPercentageNumber of  visitsPercentage112.5 Percentage016.7 Percentage237.5 Percentage125.0 Percentage312.5 Percentage233.3 Percentage412.5 Percentage38.3 Percentage612.5 Percentage58.3 Percentage912.5 Percentage78.3 PercentageEmergency departmentNumber of  visitsPercentageNumber of  visitsPercentage128.6 Percentage115.4 PercentageHospitalizedNumber of  timesPercentageNumber of  timesPercentage214.3 Percentage123.1 Percentage——223.1 PercentageWeigh per weekMean = 3.81Mean = 4.94Standard deviation = 3.69Standard deviation = 2.31Figure 1
Percent of patients who contacted
their physician (CP), visited their physician (PV), utilized
the emergency department (ED), and/or were hospitalized (Hos).


## 3.2. Reports from the Telemedicine Group

We analyzed information
regarding the experience of being in the telemedicine group and found that
despite nearly half (46%) of the participants reporting no previous experience
with computing systems, all but one of the participant reports were positive. The person who did not have a positive
experience indicated that “the telemedicine unit made her worry too much about
her condition so it stressed her heart.”
When asked the open-ended question of what participants liked best about
having the telemedicine unit in their home, the majority indicated that the
unit helped them be aware of factors important for managing their disease and
helped them to control and be more aware of their weight. Seventy-five percent of participants
indicated they would like to continue using the unit. Though we are unsure why
25% did not wish to continue, some reported complaints were
“repetitive lessons,” “redundant questions,” and
“would be more effective if interaction was involved.”  The data analysis revealed numerous ways by which the
telemedicine unit facilitated self-care. Spearman's rho correlation revealed
significant correlates between improved self-care and usage of the telemedicine
unit. For example, those who believed that having the telemedicine unit in their home will help them take better care of  themselves in the future were highly correlated with better understanding their
conditions,rs=.854, P<.001; and with identifying
important symptoms, rs=.753, P<.001. Those who believed that the unit helped them
better understand their condition were highly correlated with taking their
medications daily, rs=.952, P<.001; and limiting their intake of salt,
rs=.762, P<.001. Also, those who would recommend use of the
telemedicine unit were highly correlated with staying healthier,
rs=.855, P<.001; taking medications daily,
rs=.999, P<.001; and calling to seek help,
rs=.852, P<.001. For all correlations concerning facilitation
of self-care and perspectives regarding the telemedicine unit, see
Tables 4 and 5, respectively.Table 4
Facilitation of self-care correlates.
VariablesSpearman's rhoHelped take better care of selfLiked unit in home0.752(a)Will help take care of self in the future0.887(a)Better understand condition0.665(b)Recommend telemedicine unit0.795(a)Taking medications daily0.827(a)Important symptoms0.760(a)Use unit again0.751(b)Will help take care of self in the futureLiked unit in home0.911(a)Better understand condition0.854(a)Recommend telemedicine unit0.924(a)Limit salt0.712(a)Taking medications daily0.934(a)Important symptoms0.753(a)Call to seek help0.739(a)Stay healthier0.753(a)Use unit again0.777(a)Better understand conditionLiked unit in home0.722(a)Recommend telemedicine unit0.928(a)Limit salt0.762(a)Taking medications daily0.925(a)Important symptoms0.622(b)Call to seek help0.868(a)Stay healthier0.870(a)Use unit again0.707(b)(a)P<.001;(b)P<.05Table 5
Correlates: perspectives regarding the telemedicine unit.
VariablesSpearman's rhoLiked unit in homeHelped take better care of self0.752(a)Satisfied with training0.738(a)Will help take care of self in the future0.911(a)Better understand condition0.722(a)Recommend unit0.890(a)Limit salt0.648(b)Taking medications daily0.891(a)Important symptoms0.775(a)Call/seek help0.771(a)Stay healthier0.724(a)Use unit again0.818(a)Recommend unitHelped take better care of self0.795(a)Will help take care of self in the future0.924(a)Better understand condition0.928(a)Limit salt0.741(a)Taking medications daily0.999(a)Important symptoms0.714(a)Call/seek help0.852(a)Stay healthier0.855(a)Use unit again0.811(a)(a)P<.001;(b)P<.05


## 4. Discussion

Despite finding no statistically significant results when comparing the experimental and control
groups for health care utilization rates, we are encouraged by the reports from
those in the telemedicine group indicating the unit facilitated self-care
(refer to Figure2 and Table 5). These
reports and our review of the literature support the role of telemedicine in
facilitating home health care and self-management for CHF patients. We present these findings in hopes of
strengthening future research efforts in telemedicine.Figure 2
Percent of patients' overall
satisfaction with the telemedicine unit and satisfaction in the unit's
assistance in managing CHF.The inclusion/exclusion criteria used in this study resulted in a sample that was probably too small to
glean statistically reliable results.
For example, we had 105 referrals for participation. Of those, 23 enrolled, 61 were excluded
because of not meeting inclusion criteria, and 21 were deceased either before
enrollment or before completing the study.
Numerous others who would have met the inclusion/exclusion criteria were
too ill to participate. Of the 23
enrolled in the study, two were deceased before the study period ended and two
more died within a month of ending the study.
Of the 61 who did not meet inclusion criteria, most were due to an EF of
greater than 40%, CHF was not due to systolic dysfunction, or did not have an echo
within six months.This study was conducted in Idaho, USA,
which is considered a rural state and where we hope to better promote the use
of telemedicine in rural communities.
Though telemedicine seeks to benefit this demographic, distance, and
physical disabilities complicate travel, and to hinder research efforts. Due to software limitations, only
English speaking patients were included.
Additionally, our study consisted of only white participants. Although Idaho
is predominately English speaking and
white, an accurate model would include other ethnicities.


## 5. Future Recommendations

The largest challenge in  many telemedicine studies is obtaining study participants. The difficulties that are achieving adequate enrollment for statistically reliable comparisons indicate that future research designs may benefit from less stringent inclusion and
exclusion criteria. Obtaining more patients in less advanced stages of a
disease may be one way to improve enrollment.
People in all stages of a chronic condition may benefit from home
monitoring and increased education. Comparisons of telemedicine's effects at
various stages in the disease process may improve data on the efficacy of
telemedicine. For example, people in the
early stages of a disease may particularly benefit from an early telemedicine
intervention, as proper self-care may slow the disease process.A central goal of telemedicine is to improve delivery of health services to underserved areas.
However,  enrollment difficulties are exacerbated in studies focusing on rural
residents. Chronic conditions inhibit
travel and mobility for all patients, regardless of residency location. Therefore, expansion of study demographics to
include both urban and rural participants may be another way to facilitate
improved enrollment. Future research can
also be strengthened with the addition of a multilingual version of the software.
This will prevent any biases from restricting the study population. In a future home monitoring project,
regarding diabetes management, we will use upgraded equipment from the current
study and plan to work with clinics in both rural and urban areas to obtain a
larger sample size. This study will provide an opportunity to examine
differences and similarities between rural and urban populations in the health
benefits achieved through the use of telemedicine.Having decreased
hospitalization as a primary metric and goal may not accurately convey efficacy
of telemedicine. It is possible that
greater awareness prevented delays in necessary hospital admission; thus,
better responsiveness occurred. If so,
this would be a positive factor rather than an indication that the telemedicine
program was unsuccessful. We recommend
this issue to be considered in future research designs.While home monitoring and
education for chronic conditions facilitates improved self-care, people still
need increased access to specialty services.
In many cases, people in rural areas or people with decreased mobility
may not receive care that could improve health.
Telemedicine applications that allow specialists to view and communicate
with patients remotely may help improve outcomes. Hybrid models of health care delivery,
including home monitoring and education, telemedicine access to specialists,
and in-person visits may improve patient care and outcomes and help alleviate
the problems associated with physician shortages.



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