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Depression-Related Costs in Heart Failure Care
Mark Sullivan, MD, PhD;
Greg Simon, MD, MPH;
John Spertus, MD, MPH;
Joan Russo, PhD
Arch Intern Med. 2002;162:1860-1866.
ABSTRACT
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Background Behavioral factors may play a role in heart failure (HF) care costs
by increasing hospital readmission rates. This study sought to estimate the
effect of depression on health care costs for patients hospitalized for HF.
Methods A 3-year retrospective cohort study of a staff-model health maintenance
organization. Following a first hospitalization with a primary diagnosis of
HF, 1098 health maintenance organization patients were evaluated. Median annualized
health care costs for 3 depression groups were identified: (1) no depression
(n = 672; cost, $7474), (2) antidepressant prescription only (n = 312; cost,
$11 012), and (3) antidepressant prescription and depression diagnosis
recorded (n = 114; cost, $9550). Depression and HF status were determined
through diagnostic, laboratory, and pharmacy records. Actual utilization and
cost values were derived from administrative data.
Results After adjusting for age, sex, medical comorbidity, and length of stay
at index hospitalization (as proxy for HF severity), costs were 26% higher
in the antidepressant prescription only group and 29% higher in the antidepressant
prescription and depression diagnosis recorded group when compared with the
no depression group (both P<.001). Increased inpatient
and outpatient utilization contributed to the increased costs.
Conclusion Costs of care for patients hospitalized for HF are significantly higher
for patients with evidence of depression.
INTRODUCTION
AN ESTIMATED 4.9 million Americans have heart failure (HF). While mortality
from coronary artery disease is declining, mortality from HF is increasing.
This is due, in part, to the aging of our population. Each year, 400 000
Americans are diagnosed with HF, and 200 000 die from the disease. Heart
failure deaths have increased by more than 100% between 1979 and 1995. Heart
failure is now the leading cause for hospitalization in those older than 65
years and is the most costly cardiovascular disease in the United States,
with estimated total costs exceeding $20 billion in 1998.1
It is not clear what can be done to reduce HF costs. Attention has focused
on preventing hospital readmission since 40% to 50% of Medicare beneficiaries
are readmitted within 6 months of their first HF hospitalization.2 Recent advances in HF care, such as angiotensin-converting
enzyme inhibitors and  -blockers, have improved survival rates in clinical
trials.3 Several disease management programs
involving patient education, nurse follow-up, and home visits have been able
to reduce readmissions and costs,4-7
although others have not reduced costs.8 Krumholz
et al9 recently identified the following independent
clinical predictors of readmission for HF within 6 months: a previous admission
within the past year, prior HF, diabetes, and discharge creatinine level greater
than 2.5 mg/dL (221 µmol/L). Nonadherence to dietary and medication
regimens was not examined in the Krumholz et al9
study, but is thought to play a prominent role in hospital readmission.10 Vinson et al11 estimated
that half of HF readmissions are preventable; however, little research has
been done to identify the possible causes of this nonadherence. The general
issue of behavioral and psychological factors in HF utilization and costs
has not been well studied. We therefore studied the association between evidence
of depression and utilization and costs in health maintenance organization
(HMO) patients hospitalized for HF using computerized diagnosis, utilization,
pharmacy, and cost data. We hypothesized that depression would be associated
with increased utilization and costs in HF patients due to the challenges
of self-care for depressed HF patients.
PARTICIPANTS AND METHODS
STUDY SETTING
The Group Health Cooperative (GHC) of Puget Sound, Wash, is a large
staff-model HMO that serves approximately 450 000 residents of western
Washington. This HMO provides comprehensive care on a capitated basis. Members
typically receive their coverage through employer-subsidized plans. The GHC
includes approximately 45 000 Medicare members and 35 000 members
covered by Medicaid or Washington's Basic Health Plan, a state program for
low-income residents. Group Health Cooperative members are similar demographically
to Seattle-area residents, except that GHC members have a higher average educational
level and include fewer high-income residents. Approximately 80% of GHC members
make 1 or more primary care visits per year, with the average member making
approximately 4 visits. Over 90% of the primary care physicians and specialists
who provide services through GHC are certified by the appropriate specialty
boards. All general medical and mental health providers are paid by salary,
with no individual financial incentives tied to utilization or referral patterns.
Within GHC, the number of mental health visits allowed per year varies by
insurance group. At least 10 visits per year are allowed for everyone. Some
plans allow 20 visits, and some have no limit. Medication management visits
(ie, antidepressant prescription without psychotherapy) do not count against
this limit—they are unlimited for everyone. Primary care physicians
prescribe the vast majority of antidepressants at GHC.
The HMO computerized information systems include data on all inpatient
admissions at the HMO hospitals, all outpatient visits to clinics in the HMO,
and all outpatient prescriptions filled at pharmacies affiliated with the
HMO. Previous surveys of GHC members have found that more than 95% of prescriptions
filled by members, including those for antidepressant drugs, are filled at
pharmacies affiliated with the HMO.12 The formulary
policies concerning access to selective serotonin reuptake inhibitors (SSRIs)
at GHC were in transition during the study period (1993-1997). From 1993 to
1995 there was an official policy that tricyclic antidepressants should be
tried first with SSRIs (specifically fluoxetine) for those who had failed
treatment with tricyclics. However, this policy was not much enforced by 1995.
After 1996, formulary policy dictated that SSRIs could be used as first-line
treatment. Through 1997, the preferred first-line agent (based on price) was
fluoxetine.
SAMPLE SELECTION
Potential subjects were all GHC members, 18 years or older, receiving
a first hospitalization with a primary diagnosis of HF between January 1,
1993, and December 31, 1997. Subjects were selected at the time of their first
congestive heart failure (CHF) hospitalization to obtain a cohort at a similar
phase in their illness. Pharmacy data were assessed for angiotensin-converting
enzyme inhibitor, digoxin, and loop diuretic use for 3 months following the
index hospitalization to provide confirmation of HF diagnosis. Ejection fractions,
evidence of systolic vs diastolic dysfunction, or myocardial oxygen consumption
are not regularly collected on CHF patients in this HMO. Therefore, serum
creatinine levels, serum urea nitrogen levels, and sodium levels, as well
as length of stay at index hospitalization were assessed as measures of HF
severity.
The sampling window for cost information was from 2 years before this
hospitalization to 1 year after this hospitalization. This allowed for an
adequate period of cost assessment even for those subjects who died soon after
their index hospitalization. To assure complete availability of relevant data,
the sample was limited to those continuously enrolled during this sampling
window. Subjects who had evidence of receiving any care outside of GHC facilities
were excluded. Figure 1 describes
the process of sample selection.
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Figure 1. Sample selection procedure.
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To capture all those who might meet criteria for depression at the time
of this hospitalization, we assessed for any outpatient antidepressant prescription
or depression diagnosis from 6 months before to 1 year after this hospitalization
(excluding bupropion hydrochloride prescriptions for smoking cessation). We
included primary and secondary outpatient diagnoses of depression. Patients
were placed in the no depression group if they had no antidepressant prescriptions
or depression diagnoses recorded during the 3-year sampling window. If an
antidepressant prescription was filled, but no depression diagnosis was recorded
among the outpatient diagnoses during that period, a subject was placed in
the antidepressant prescription only group. If any diagnosis of depression
was made and an antidepressant prescription was filled, a subject was placed
in the antidepressant prescription and depression diagnosis recorded group.
Only 20 subjects in the cohort received a depression diagnosis without an
antidepressant prescription. Because this group was so small and was very
different from the other depression groups (much higher mental health costs
and lower medical costs), they were excluded from analyses. A random sample
of 50 charts in the antidepressant prescription only group were reviewed to
determine whether depression was mentioned as a reason for the prescription
in the chart notes.
UTILIZATION AND COST DATA
For each of the 1098 subjects, we examined use and cost of all health
care services covered by the GHC for the 2 years before and 1 year after each
patient's index HF hospitalization. Data were extracted from the HMO computerized
cost accounting system. This system tracks each unit of service, such as an
outpatient visit, a prescription, or an inpatient day that is provided or
paid for by the health plan. For services produced by the health plan, including
outpatient visits, diagnostic testing, and hospitalization at the HMO facilities,
the system estimates actual cost of production. Each service center, outpatient
clinic, laboratory, or pharmacy must allocate actual costs of operation to
each unit of service provided. Health plan administrative costs are distributed
proportionally across service centers. This system also accounts for patients
out-of-pocket contributions (copayments or coinsurance) so that the final
cost estimates reflect the health plan's actual expenses. In summary, data
from this system reflect the health plan's actual costs of providing health
care services, that is, cost from the insurer's perspective. All costs were
standardized to 1998 dollars.
For the present study, we assessed actual costs (the amount of money
expended by the health care system) and utilization (the number of contacts
between the patient and the health care system). These were allocated to 3
groups: inpatient, outpatient, and mental health. Inpatient costs include
all costs incurred during any hospitalization. Outpatient costs include primary
care, specialty care, emergency department, pharmacy (including antidepressants),
laboratory, and radiology costs. Mental health costs include all inpatient
admissions to mental facilities and outpatient specialty visits for mental
health and substance abuse treatment. Total costs include all of these plus
long-term care costs, ambulance, and home equipment costs. Inpatient utilization
includes number of admissions and total number of hospital days. Outpatient
utilization includes all primary care, specialty care, emergency department,
pharmacy, laboratory, and radiology visits. Total utilization is the sum of
all these contacts with the patient, counting a hospital day, a clinic visit,
or a pharmacy refill as 1 contact.
DATA ANALYSES
Data were analyzed using SPSS 8.0 for Windows (SPSS Inc, Chicago Ill).
Differences in sample characteristics between the 3 study groups were examined
using  2 tests for dichotomous variables and analyses of variance
for continuous ones. In the event of a significant result, planned post hoc
tests between the 3 groups were conducted. Actual health care costs are presented
as annualized means and medians. Due to the extreme nonnormality of the cost
and utilization data, median tests were performed between the groups. In the
event of significant results, pairwise median tests were performed. These
analyses do not adjust for relevant covariates. To allow for adjustment for
relevant covariates (using the analytic methods described by Diehr et al13), we applied a 1-stage linear regression model to
the data using the log transformations of the cost data for total, inpatient,
and outpatient costs. These analyses adjusted for age, sex, HF severity, medical
comorbidity, and length of assessment. In the case of the mental health cost
data, a 2-stage model was applied. The 2-stage model for mental health costs
consisted of a first-stage logistic regression model predicting the odds of
having at least 1 mental health visit after adjusting for covariates. The
second stage was a linear regression on the costs involving only individuals
with at least $1 in mental health care costs using the same set of covariates.
Length of assessment was 36 months for patients who did not die. For patients
who died, the minimum length of assessment was 24 months and the maximum was
36 months. The sample mean was 33 months of assessment with a 4-month SD.
Multivariate analyses were adjusted for HF severity and medical comorbidity.
As a proxy for HF severity and complications, we used length of stay for the
index hospitalization. Heart failure severity and complications explain only
a portion of the variance in length of stay, so this is an approximation14; however, it is likely to introduce a conservative
bias in estimates of the effect of depression on costs and utilization. Depression
is associated with increased length of stay, so adjusting for length of stay
will tend to minimize its effect. Medical comorbidity was rated by means of
the Chronic Disease Score, a technique developed at GHC for estimating chronic
medical illness burden using automated pharmacy data.15
The method classifies each patient according to the number of medications
typically used to treat chronic medical conditions and is therefore a measure
of recognized and treated medical illness. In prior research, the Chronic
Disease Score was correlated with physician ratings of physical disease severity
and predicted mortality. It is less affected by current psychological distress
than self-report measures of health status. For the current analyses, antidepressants
were excluded from the Chronic Disease Score. Diseases not treated with prescribed
medications, such as Alzheimer disease during the 1992 to 1997 time period,
are not reflected in the Chronic Disease Score.
Tests for heteroscedasticity of the log-transformed data were performed.
Heteroscedasticity may invalidate results of log-transformed analyses.16 Cost ratios of estimated median health care costs
adjusted for the covariates (with 95% confidence intervals) between the no
depression group and the other 2 groups were calculated by exponentiating
the regression coefficients representing the 2 subgroup comparisons.
RESULTS
Sample characteristics are displayed in Table 1. Subjects were elderly with a mean age of 75 years and slightly
fewer than half were men. Groups did not differ in age, serum creatinine levels,
serum urea nitrogen levels, sodium levels, or in rates of loop diuretic, angiotensin-converting
enzyme inhibitor, or digoxin prescription. Ninety percent of the sample had
received a prescription for a loop diuretic, angiotensin-converting enzyme
inhibitor, or digoxin within 3 months of their index hospitalization. The
depression groups were more often women and had a higher level of medical
comorbidity. The antidepressant prescription only group had greater Chronic
Disease Score (medical comorbidity) and a longer length of stay for the index
hospitalization (initial HF severity). On review of 50 random charts from
the antidepressant prescription only group, depression was mentioned as a
reason for the prescription in 28 charts. Anxiety or insomnia was mentioned
in another 19 charts. No reason could be identified for the antidepressant
prescription in 3 charts. Because of the range of diagnoses for which antidepressant
medications were prescribed, we interpreted this group as having significant
psychological distress but analyzed them separately from those with a submitted
diagnosis of depression. The antidepressant prescription and depression diagnosis
recorded group had a lower 1-year mortality rate than the antidepressant prescription
only group (23% vs 34%; P = .03), but the mortality
risk was no longer significantly different after accounting for differences
in age, sex, comorbidity, and antidepressant type (odds ratio, 0.66; 95% confidence
interval, 0.39-1.1). In the antidepressant prescription only group, 56% received
a tricyclic, 27% received an SSRI, and 17% received another type of antidepressant.
In the antidepressant prescription and depression diagnosis recorded group,
30% received a tricyclic, 47% received an SSRI, and 23% received another type
of antidepressant. These rates were significantly different (22,426 = 24.3; P<.001). The antidepressant
prescription only group received a median of 11 antidepressant prescriptions
(mean, 19; mode, 1) during the study period, while the antidepressant prescription
and depression diagnosis recorded group received a median of 22 antidepressant
prescriptions (mean, 32; mode, 6). These were significantly different (21,425 = 25.5; P<.001).
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Table 1. Sample Characteristics*
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Unadjusted annualized actual health care cost data are displayed in Table 2. Median costs are listed first
for each category, followed by mean costs and SDs. No patients had zero costs
in the inpatient or outpatient categories since all patients had an HF hospitalization.
All categories of cost show significant differences between the 3 groups using
the median tests (P<.001). Post hoc tests revealed
that for all costs, the antidepressant prescription only group had greater
median costs than the no depression group, and that the no depression and
antidepressant prescription and depression diagnosis recorded groups differed
in outpatient, mental health, and total costs, but not inpatient costs. The
2 depression groups only differed in mental health costs, with the antidepressant
prescription and depression diagnosis recorded group having significantly
greater average mental health costs than the antidepressant prescription only
group. Figure 2 displays total cost
differences for the 3 groups by breaking down the 3-year assessment period
into 6-month time periods. Although cost differences are most marked in the
6 months that include the index hospitalization, costs appear to be greater
in the depression groups for all the 6-month periods.
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Table 2. Average Annual Health Care Costs (in 1998 Dollars)*
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Figure 2. Depression group costs by 6-month
intervals. 1, No depression group; 2, antidepressant prescription only group;
and 3, antidepressant prescription and depression diagnosis recorded group.
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Annualized utilization data are displayed in Table 3. Median admissions, days, or visits are listed first, followed
by means and SDs. The median tests revealed that all categories of utilization
are higher in the groups with evidence of depression compared with the group
without.
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Table 3. Annualized Automated Utilization Data*
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Table 4 presents the adjusted
median cost ratios and 95% confidence intervals for the 3 groups. The results
show that patients with an antidepressant prescribed had significantly higher
costs than patients with no depression. The estimates of the increase in cost
ranged from 32% for outpatient costs to 26% for total and inpatient costs.
Although patients who are prescribed an antidepressant are 5 times more likely
to have mental health care costs, once costs were incurred, they did not differ
between the groups. Patients diagnosed with depression had significantly greater
costs than patients with no depression, ranging from 41% for outpatient costs
to 23% for inpatient costs. Total costs were 29% higher after controlling
for the covariates. Patients in the antidepressant prescription and diagnosis
recorded group were 13 times more likely to have at least some mental health
costs, but users of mental health services in the 2 depression groups did
not differ in amount of services used.
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Table 4. Adjusted Cost Ratios for Median Health Care Costs (1998 Dollars)
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COMMENT
This cohort study of HMO patients with a first hospitalization with
a primary diagnosis of HF demonstrates significantly increased costs and utilization
for those patients with some evidence of depression. These increased costs
were due to increased inpatient and outpatient medical utilization, not increased
mental health utilization. These differences were evident even after adjustment
for additional medical comorbidity. Contrary to the expectation that behavior-related
hospitalizations would produce the largest effects, outpatient costs showed
more robust differences between groups than inpatient costs. After adjustment
for covariates (age, sex, medical comorbidity, and length of stay for index
hospitalization), the depression groups had 26% to 29% greater costs over
a period of 3 years than the no depression group. Applying these cost ratios
to the $20 billion total costs for HF care for 199817
suggests that up to $5 billion of the cost of HF care may be associated with
depression and other psychological distress.
Based on review of a random sample of charts from the antidepressant
prescription only group, depression is mentioned as a reason for antidepressant
prescription in over half of this group. If prescriptions for anxiety and
insomnia are added to these, this accounts for over 90% of the antidepressant
prescriptions. To be conservative, we have analyzed the depression groups
separately; however, cost increases are very similar for the 2 depression
groups, suggesting similar effects on utilization for the groups. Mental health
costs for our sample are quite low, but are typical for an elderly and medically
ill group. Stigma and preoccupation with ongoing serious medical disorders
combine to keep mental health utilization very low in this group. Other studies
have showed similar rates of utilization in the elderly and medically ill
group.18 One additional reason our mental health
visit rates are low is that primary care physicians prescribe the vast majority
of antidepressants at GHC. Further studies with structured psychiatric interviews
will be needed to confirm our findings about these depression effects on HF
care costs.
There are a number of possible reasons why depression might be associated
with increased HF care costs. Depression could be a "marker" for more severe
heart disease. Depression could increase HF morbidity by impairing self-care.
Depression could affect symptom perception and health behavior, leading to
"excess" utilization. The neuroendocrine changes typical of depression could
exacerbate HF pathophysiology.19 Higher rates
of medical comorbidity not reflected in the Chronic Disease Score (eg, dementia),
or greater severity of HF not captured by our length of stay proxy for HF
severity may also account for these observations. Replication of our findings
with better depression assessment and HF characterization will be needed to
clarify these issues.
Though depression in coronary heart disease is increasingly well studied,
studies of depressive disorders and their effects in HF patients are much
more limited. Koenig20 assessed 107 hospitalized
patients with a primary or secondary diagnosis of CHF. Major depression was
present in 36% of those with CHF compared with 17% without CHF. Minor depression
was present in 21% of those with CHF compared with 17% without CHF. Those
who were depressed had more severe medical illnesses and more functional impairment
and were more likely to have a history of previous depression. Depressed CHF
patients made more outpatient visits over the next 3 months, but it was not
possible to determine if this was due to more severe medical illnesses. Few
depressed patients received treatment and 40% failed to remit over the following
year. Stressful life events and low social support, but not medical severity,
were associated with depression persistence. Krumholz et al21
recently showed that lack of emotional support for elderly patients hospitalized
with HF increased the risk of fatal and nonfatal cardiovascular events over
the next year. Jiang and colleagues22 recently
reported a prevalence rate of 14% for major depression and 35% for minor depression
among 374 patients hospitalized for HF. They found major depression was associated
with a doubling of 3- and 12-month mortality and readmission risk. Murberg
et al23 have reported similar findings.
Successful management of HF often requires major lifestyle modifications
by patients and their families. Medication regimens, dietary changes, daily
weights, activity modifications, and symptom monitoring all require diligence
and psychological adjustment. Rates of noncompliance with medications in HF
range from 20% to 58%. Studies suggest that the majority of early rehospitalizations
for CHF are associated with medication noncompliance.10
Depression is known to decrease rates of adherence to medication24
and exercise regimens25 in patients with heart
disease. Depression has been shown to be strong predictor of an inability
to quit smoking over a 9-year period.26 Self-efficacy
has strong links to depression and may be the principal means by which depression
affects adherence to self-care regimens.27
Despite the recognition of depression as an independent predictor of
dependence in activities of daily living after hospitalization in acutely
ill older persons,28 and as a driver of increased
health care costs for elderly medical comorbidity,29-30
depression has not been well evaluated in studies of HF patients. Medical,
behavioral (eg, noncompliance), and social (eg, living alone) predictors of
hospitalization in HF have been examined in prospective studies, but psychological
predictors have not been included.31 Multidisciplinary
interventions ranging from home monitoring32
to home visits33 to intensive education and
medical follow-up have been shown to decrease rates of rehospitalization.34 But these interventions have neither monitored nor
targeted depression, so it is not known how much depression treatment might
reduce health care utilization rates in CHF. Given the magnitude of depression-related
costs suggested by the present study, depression treatment may be an inexpensive
way to decrease CHF-related health care utilization and improve the quality
of life of patients with CHF.
All the subjects in our present study did receive at least 1 antidepressant
prescription. Thus, it may appear that this is a sample with treated depression.
But previous studies at GHC have demonstrated that fewer than half of patients
receiving antidepressants receive adequate dose or duration of treatment according
to Agency for Healthcare Research and Quality guidelines. Treatment adequacy
is much worse than this in the elderly and the medically ill.35
It is therefore not possible, based on our data, to rule out the reversibility
of these depression-associated costs.
Some limitations of the present study should be noted. Primary among
these is the use of only automated claims data. These data have limited information
on depression diagnosis and HF severity. Further clinical studies, using structured
psychiatric interviews and detailed assessment of HF severity, are needed
to confirm our findings.
In conclusion, our study suggests that depression and other conditions
requiring the use of antidepressant medications may be contributing significantly
to direct medical costs for HF care. This effect is not limited to rehospitalization
risk, but extends throughout the spectrum of HF care. Because we rely upon
automated data proxies for standardized medical and psychiatric diagnoses,
our results should be interpreted with caution. In randomized trials, disease
management programs have generally been able to decrease costs and improve
some outcomes in HF care; however, none of these programs have targeted depression.
Our study suggests that depression treatment should be tested to determine
if it can become a cost-effective component of HF disease management programs.
AUTHOR INFORMATION
Accepted for publication January 17, 2002.
This research was supported by grant K01 MH01351 from the National Institutes
of Health, Bethesda, Md (Dr Sullivan).
We thank Nimi Sandhu, MPH, and Jane Grafton, BA, for programming with
the administrative data.
Corresponding author and reprints: Mark Sullivan, MD, PhD, Department
of Psychiatry and Behavioral Sciences, University of Washington, Box 356560,
Seattle, WA 98195 (e-mail: sullimar{at}u.washington.edu).
From the Department of Psychiatry and Behavioral Sciences, University
of Washington, Seattle (Drs Sullivan and Russo); the Center for Health Studies,
Group Health Cooperative, Seattle (Dr Simon); and the Mid-America Heart Institute,
University of Missouri–Kansas City (Dr Spertus).
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