Abstract
OBJECTIVES
Although congestive heart failure (CHF) is a common condition, the extent of disability and caregiving needs for those with CHF are unclear. We sought to determine: (1) prevalence of physical disability and geriatric conditions, (2) whether CHF is independently associated with disability, (3) rates of nursing home admission, and (4) formal and informal in-home care received in the older CHF population.
METHODS
We used cross-sectional data from the 2000 wave of the Health and Retirement Study. We compared outcomes among three categories of older adults: (1) no coronary heart disease (CHD), (2) CHD, without CHF, and (3) CHF. Compared to those without CHF, respondents reporting CHF were more likely to be disabled (P < 0.001) and to have geriatric conditions (P < 0.001). Respondents reporting CHF were more likely to have been admitted to a nursing home (P < 0.05). CHF respondents were more functionally impaired than respondents without CHF.
RESULTS
The adjusted average weekly informal care hours for respondents reporting CHF was higher than for those reporting CHD but without CHF and those reporting no CHD (6.7 vs 4.1 vs 5.1, respectively; P < 0.05). Average weekly formal caregiving hours also differed among the three groups (1.3 CHF vs 0.9 CHD without CHF vs 0.7 no CHD; P > 0.05).
CONCLUSIONS
CHF imposes a significant burden on patients, families, and the long-term care system. Older adults with CHF have higher rates of disability, geriatric conditions, and nursing home admission.
KEY WORDS: CHF, disability, formal and informal caregiving
INTRODUCTION
Congestive heart failure (CHF) is increasing in prevalence among older adults because of the aging of the US population and the greater survival of patients 1–4. Consequently, many people will be aging with CHF and its complications, leading to greater disability and greater need for home and community-based services as well as nursing home care 4. This substantial increase in the prevalence of CHF will generate additional burdens on older patients, their family members, and the health care system to provide the substantial daily care required by individuals with CHF 5–7. Although many aspects of CHF care have been extensively studied, we do not have good estimates of the extent of disability suffered by people with CHF nor their use of in-home caregiving. This study is the first to characterize disability in the older community-dwelling CHF population and the utilization of in-home services using a nationally representative sample. This information is essential in planning for the long-term care needs of this growing segment of the older adult population.
To assess the clinical and social impact of CHF on older Americans, we examined cross-sectional data from the 2000 wave of the Health and Retirement Study (HRS), comparing respondents who report CHF with those who report coronary heart disease (CHD) without CHF and those who report no CHD, to answer the following four research questions: (1) What is the extent of physical disability and geriatric conditions among older adults with CHF? (2) Is CHF independently associated with disability? (3) How much formal and informal in-home care is utilized by older adults with CHF? (4) What is the likelihood of nursing home admission among older adults with CHF? We hypothesized that older adults with CHF would be more disabled and require more in-home services than older adults with CHD alone and those without CHD.
MATERIALS AND METHODS
Data
We used cross-sectional data from the 2000 wave of the HRS, a biennial, longitudinal survey of a nationally representative cohort of US adults aged 50 years or older 8. The HRS 2000 cohort is representative of approximately 34.5 million adults in this age group in the USA. This survey provides detailed self-report information on chronic diseases, cognitive impairment, and task-specific disabilities. Interviews were conducted with all HRS respondents every 2 years, either by telephone or in person, with the latter mode used preferentially for those age 80 years or older. The interviews conducted in 2000 were conducted in 10,371 households (82% survey response rate; see the HRS website at http://hrsonline.isr.umich.edu for more information on the organization and design of the HRS).
Of the 19,850 respondents to the 2000 survey, our analysis was limited to the 11,093 respondents age 65 and above. Proxy respondents (n = 1,068, 9.3%: 8.3% [n = 669] of no CHD respondents, 10.1% [n = 309] of CHD, without CHF respondents, and 20.6% [n = 90] of CHF respondents) completed surveys in some cases when participants were unable to respond. Current nursing home residents (n = 240) were excluded from the analysis. Seventeen respondents had missing data for heart condition categories; thus, we excluded them from the analysis.
Classification of Heart Disease Categories
All respondents were asked: “Has a doctor ever told you that you had a heart attack, coronary heart disease, angina, congestive heart failure, or other heart problems?” Those who responded “yes” were further asked “Has a doctor told you that you have congestive heart failure in the last 2 years.” The responses from these two questions were used to sort respondents into three mutually exclusive heart problem categories: (1) no CHD, (2) CHD but without CHF, and (3) CHF.
Independent Variables
The sociodemographic variables included in the analysis as independent variables were: age (65–74, 75–84, ≥85), race, gender, income, living arrangement (married, unmarried living with others, and unmarried living alone), household net worth 9, and level of education. Self-reported comorbid illnesses included were: hypertension, lung disease (asthma or chronic obstructive pulmonary disease), stroke, cancer, diabetes, and psychiatric problem. Geriatric conditions are defined as clinical conditions that are highly prevalent in older, particularly frail adults. Self-report of urinary incontinence, injury by fall, and dementia were the variables utilized in this analysis to capture geriatric conditions. The presence and severity of dementia for self-respondents was defined using a modified version of the Telephone Interview for Cognitive Status (TICS), a validated cognitive screening instrument patterned on the Mini-Mental State Examination, which is specifically designed for population-based studies 10–12. The TICS was not administered to those respondents represented by a proxy, but rather each proxy was asked questions to assess respondent’s overall memory and change in memory compared to prior waves. Based on prior validation studies, we defined a cutoff score of 8 (2 standard deviations below the mean) on the 35-point TICS scale as the level of cognitive impairment consistent with “dementia”13,14. Cognitive impairment consistent with dementia was defined based on a report of “fair or poor memory” as assessed by a proxy respondent 15.
Dependent Variables
We evaluated several dependent variables relevant to our research questions: activities of daily living (ADL) and instrumental activities of daily living (IADL) disability (using composite variables), the utilization of formal and informal in-home caregiving, and the number of hospital and nursing home admissions in the 2 years before the interview. A respondent was considered to have a disability in an ADL (bathing, dressing, eating, toileting, and walking) if they reported having difficulty performing the ADL or required assistance. Disability in an IADL (grocery shopping, preparing meals, taking medication, managing money, and making phone calls) was defined as having difficulty performing the IADL without help or not doing an IADL because of a health problem.
We classified respondents as receiving informal care if in-home care was provided by a relative (paid or not) or unpaid nonrelative with no organizational affiliation in the past month. Formal care was identified for those reporting in-home care performed by a paid nonrelative or someone with an organizational affiliation in the past 2 years 16. Presence or absence of formal and/or informal caregiving and the weekly hours of each were also evaluated.
The occurrence of a hospitalization for each heart disease category was determined by respondent self-report. Respondents were asked “In the last 2 years, have you been in the hospital overnight?” Prior residence in a skilled nursing facility or nursing home was identified if respondents answered “yes” to the following question: “In the last 2 years, have you been a patient overnight in a nursing home, convalescent home or other long-term health care facility?”
Data Analyses
The demographic, medical condition, and disability characteristics of the three heart disease groups (CHF, CHD without CHF, and no CHD) were compared using standard descriptive statistics including chi-square and chi-square test for statistical trend. The unadjusted disability rates were calculated for each heart disease category using survey-weighted values.
We used negative binomial regression with a three-level categorization of ADL (none, 1–3, and 4–6) and IADL (none, 1–3, and 4–5) disability to estimate unadjusted and adjusted incident rate ratios to determine if CHF is independently associated with disability. The model was adjusted for attributes known to be associated with disability: age, race, gender, level of education, net worth, living arrangement, and certain medical conditions. We used bootstrapping to estimate 95% confidence intervals for the incident rate ratios of ADL and IADL limitations.
To determine the association between heart disease category and type of caregiving, a multivariable logistic regression model was used. Because a substantial proportion of the respondents did not receive informal and formal care in the month before the administration of the survey and the distribution of informal and formal care hours among recipients was highly skewed, a two-part regression model was used for this analysis 17. In the first part of the two-part model, we used logistic regression to determine the likelihood of receiving informal and formal home care by estimating the association between each type of in-home care and the heart problem categories, controlling for other covariates. In the second part of the two-part model, ordinary least squares regression was utilized to examine the association between the natural log of informal and formal care hours and the heart disease category. The results from each part of the model were then combined to obtain an estimate of the average effect of the heart disease category on weekly hours of informal and formal in-home caregiving. Results were retransformed back into hours, the natural units. We used bootstrapping to estimate the confidence intervals for the predicted average weekly informal and formal hours 18.
We controlled for potentially confounding sociodemographic and health status attributes in the prediction of average formal and informal care hours by heart disease category. Among the three groups, we compared the probabilities of reported hospitalization and nursing home admission in the prior 2 years using descriptive methods and logistic regression, interpreting coefficients as proportions rather than odds ratios, for multivariate analysis. Multivariate analyses controlled for demographic and disease variables. These and all analyses used were weighted and adjusted for the complex sampling design of HRS using STATA 9.0 19.
RESULTS
Characteristics of the Study Population
The characteristics of the study population are shown in Table 1. Of the 10,626 respondents reporting heart problem status in the 2000 survey, 7,363 (69.3%) reported no CHD, 2,863 (26.8%) reported a CHD without CHF, and 400 (3.8%) reported CHF. Those with CHF were older, had lower levels of education, and were less likely to be married. In addition, those with CHF were more likely to be living alone and to have the lowest net worth of all three groups.
Table 1.
Characteristics of Respondents by Heart Disease Category (n = 10,626)
| Heart disease category | ||||
|---|---|---|---|---|
| Variable | No CHD (N = 7,363) | CHD, no CHF (N = 2,863) | CHF (N = 400) | P value |
| Age | <0.001 | |||
| 65–74 | 4,275 (57.7) | 1,271 (43.6) | 147 (36.8) | |
| 75–84 | 2,407 (33.7) | 1,156 (42.1) | 177 (45.3) | |
| ≥85 | 681 (8.6) | 436 (14.3) | 76 (18.0) | |
| Age: mean ± SD | 74.0 ± 0.1 | 76.4 ± 0.16 | 77.6 ± 0.43 | <0.001 |
| Gender | <0.001 | |||
| Men | 2,970 (39.6) | 1,443 (49.5) | 172 (42.2) | |
| Women | 4,393 (60.4) | 1,420 (50.5) | 228 (57.8) | |
| Race | 0.9 | |||
| White | 6,185 (88.3) | 2,423 (88.8) | 347 (88.5) | |
| Black | 989 (8.8) | 373 (8.4) | 45 (8.3) | |
| Other | 236 (3.0) | 85 (2.8) | 10 (2.6) | |
| Education (year) | <0.001 | |||
| <12 | 2,368 (29.6) | 1,058 (35.6) | 186 (46.6) | |
| 12 | 2,501 (35.0) | 918 (32.5) | 117 (29.0) | |
| ≥13 | 2,494 (35.4) | 887 (31.9) | 97 (24.4) | |
| Living arrangement | 0.01 | |||
| Married | 4,341 (56.4) | 1,658 (55.2) | 202 (47.5) | |
| Unmarried living with other | 907 (12.2) | 369 (13.9) | 66 (16.1) | |
| Unmarried living alone | 2,115 (31.3) | 836 (31.7) | 132 (36.4) | |
| Net worth | <0.001 | |||
| ≤49,200 | 1,615 (20.4) | 758 (25.4) | 108 (26.7) | |
| 49,201–151,000 | 1,823 (24.4) | 728 (25.2) | 137 (33.3) | |
| 151,001–370,000 | 1,893 (26.9) | 724 (26.1) | 86 (21.7) | |
| ≥370,001 | 2,003 (28.4) | 642 (23.4) | 69 (18.4) | |
| Medical conditions | ||||
| Hypertension | 3,711 (59.6) | 1,829 (63.0) | 293 (73.0) | <0.001 |
| Lung disease | 597 (8.0) | 385 (13.9) | 130 (31.8) | <0.001 |
| Stroke | 476 (6.3) | 391 (13.2) | 89 (22.7) | <0.001 |
| Cancer | 1,034 (14.4) | 495 (17.3) | 75 (19.1) | <0.001 |
| Psychiatric problem | 780 (10.5) | 466 (15.2) | 106 (28.3) | <0.001 |
| Arthritis | 610 (8.4) | 281 (10.0) | 66 (17.0) | <0.001 |
| Diabetes | 1,051 (13.5) | 622 (20.8) | 141 (33.3) | <0.001 |
| Geriatric conditions | ||||
| Urinary incontinence | 1,363 (18.7) | 652 (23.3) | 145 (36.1) | <0.001 |
| Injury by fall | 4,449 (60.2) | 2,018 (70.3) | 321 (78.3) | <0.001 |
| Dementia | 413 (5.0) | 227 (7.1) | 72 (17.3) | <0.001 |
Percentages (in parentheses) are weighted using the HRS respondent population weights to adjust for the complex sampling design of the HRS. Percentages are column percents, for example 36.8% of people with CHF are aged 65–74, but may not add to 100% because of rounding.
Individuals with CHF were more likely to report a history of hypertension, lung disease, diabetes, arthritis, cancer, stroke, and psychiatric issues. Geriatric conditions were more prevalent among those respondents with CHF; they were more likely to have injury by fall, urinary incontinence, and cognitive impairment consistent with dementia.
ADL and IADL Impairments
Table 2 shows that CHF respondents were significantly more functionally impaired with more ADL and IADL impairments (P < 0.001, χ2 for trend) than respondents without CHF. Specifically, those with CHF were significantly more likely to have at least one and ≥ four ADL and IADL impairments.
Table 2.
Number and Specific Activities of Daily Living (ADLs) and Instrumental Activities of Daily Living (IADLs) Limitations, by Heart Disease Category (n = 10,626)
| Heart disease category | ||||
|---|---|---|---|---|
| Variable | No CHD (N = 7,363) | CHD, no CHF (N = 2,863) | CHF (N = 400) | P value |
| Number of ADLs impaired (M ± SD) | 0.43 ± 0.02 | 0.71 ± 0.03 | 1.49 ± 0.11 | <0.001a |
| 0 | 5,864 (80.3) | 1,930 (68.3) | 181 (45.7) | <0.001 |
| 1–3 | 1,222 (16.2) | 741 (25.2) | 148 (37.6) | |
| 4–6 | 277 (3.5) | 192 (6.5) | 71 (16.8) | |
| Type of ADL impairment | ||||
| Walking across a room | 961 (12.5) | 632 (21.1) | 169 (41.8) | <0.001 |
| Dressing | 669 (8.6) | 417 (14.2) | 119 (41.8) | <0.001 |
| Bathing | 531 (6.9) | 330 (11.6) | 107 (27.3) | <0.001 |
| Transferring | 528 (6.8) | 345 (11.3) | 105 (24.4) | <0.001 |
| Toileting | 376 (4.9) | 245 (8.7) | 74 (18.1) | <0.001 |
| Eating | 227 (2.9) | 133 (4.5) | 39 (8.8) | <0.001 |
| Number of IADLs impaired (M ± SD) | 0.26 ± 0.01 | 0.43 ± 0.03 | 1.05 ± 0.08 | <0.001a |
| 0 | 6,377 (87.0) | 2,249 (79.1) | 221 (55.2) | <0.001 |
| 1–3 | 814 (10.8) | 520 (17.7) | 133 (34.5) | |
| 4–5 | 172 (2.2) | 94 (3.2) | 46 (10.2) | |
| Type of IADL impairment | ||||
| Grocery shopping | 619 (8.1) | 424 (14.6) | 141 (35.6) | <0.001 |
| Managing money | 440 (5.7) | 249 (8.4) | 88 (22.4) | <0.001 |
| Cooking | 442 (5.7) | 275 (9.5) | 95 (23.2) | <0.001 |
| Taking medication | 229 (3.1) | 139 (4.8) | 51 (12.2) | <0.001 |
| Using the telephone | 298 (3.7) | 178 (5.6) | 58 (13.4) | <0.001 |
Percentages (in parentheses) are weighted using the HRS respondent population weights to adjust for the complex sampling design of the HRS.
aTest for trend
Table 2 also shows the specific ADL and IADL impairments associated with respondents by heart disease category. The most prevalent ADL limitation was “walking across a room” among 41.8% of respondents with CHF, 21.1% of respondents with CHD, no CHF, and 12.5% of respondents with no CHD. The most prevalent IADL limitation was “grocery shopping” among 35.6% of respondents with CHF, 14.6% of respondents with CHD, no CHF, and 8.1% of respondents with no CHD.
Table 3 describes the incident rate ratio (RR) of ADL and IADL limitations, by heart disease category. In the unadjusted analyses, CHF was associated with a greater number of ADL (incident RR 3.50; 95% confidence interval [CI], 3.05–4.01) and IADL (incident RR 3.99; 95% CI 3.39–4.69) limitations. Although the risk ratios were attenuated after adjustment for demographics and certain chronic diseases, CHF remained significantly independently associated with a higher risk of ADL and IADL limitations.
Table 3.
Incident Rate Ratio of the Association of ADL and IADL Limitations, by Heart Disease Category with 95% Confidence Intervals, Controlled for Covariates that are also Associated with Disability
| Heart disease category | ADL | IADL |
|---|---|---|
| Unadjusted | ||
| No CHD | Ref. | Ref. |
| CHD, no CHF (RR; 95% CI) | 1.68 (1.53–1.83) | 1.64 (1.49–1.80) |
| CHF (RR; 95% CI) | 3.50 (3.05–4.01) | 3.99 (3.39–4.69) |
| Adjusteda | ||
| No CHD (RR; 95% CI) | Ref. | Ref. |
| CHD, no CHF (RR; 95% CI) | 1.22 (1.1–1.39) | 1.21 (1.1–1.37) |
| CHF (RR; 95% CI) | 1.51 (1.33–1.71) | 1.67 (1.35–2.06) |
aAdjusted for age, gender, race, education, living arrangement and net worth, incontinence, blood pressure, cancer, stroke, arthritis, fall-injured, diabetes, lung disease, psychiatric problem, dementia, and nursing home and hospital admission
Patterns of In-home Caregiving
Of the 400 respondents with CHF, 42.2% received informal in-home care, while 13% received formal in-home care. In contrast, 18.3% of respondents with CHD without CHF received informal care and 3.9% of formal care. Those respondents with no CHD had the lowest rates of informal and formal care with 11 and 2.2%, respectively (Table 4).
Table 4.
Receipt and Intensity of Caregiving and Proportion that were Hospitalized or Admitted to a Nursing Home, by Heart Disease Category
| Heart disease category | |||
|---|---|---|---|
| Characteristics | No CHD (N = 7,363) | CHD, no CHF (N = 2,863) | CHF (N = 400) |
| Receiving care (%) | |||
| Informal* | 11.0 | 18.3 | 42.2 |
| Formal* | 2.2 | 3.9 | 13.0 |
| Weekly informal care hours | |||
| Unadjusted (hours ± sd)**, a, c | 3.5 ± 0.23 | 5.0 ± 0.43 | 15.9 ± 1.45 |
| Adjusted (hours; 95% CI)**, a, b, c | 5.1 (4.4–5.9) | 4.1 (3.5–4.7) | 6.7 (5.5–7.9) |
| Weekly formal care hours | |||
| Unadjusted (hours ± sd)a, c | 0.5 ± 0.09 | 1.1 ± 0.21 | 3.8 ± 1.2 |
| Adjusted (hours; 95% CI)a, b, c | 0.7 (0.5–0.9) | 0.9 (0.6–0.2) | 1.3 (0.7–1.8) |
| Hospitalized in last 2 years | |||
| N (%) | 1,646 (22.1) | 1,231 (43.0) | 283 (69.5) |
| Unadjusted (probability ± sd)**, c | 0.221 ± 0.005 | 0.43 ± 0.01 | 0.695 ± 0.026 |
| Adjusted (probability; 95% CI)**, b, c | 0.234 (0.23–0.24) | 0.397 (0.38–0.14) | 0.605 (0.57–0.64) |
| Lived in a nursing home in last 2 years | |||
| N (%) | 118 (1.6) | 86 (3.1) | 36 (9.5) |
| Unadjusted (probability ± sd)**, c | 0.016 ± 0.001 | 0.031 ± 0.003 | 0.095 ± 0.015 |
| Adjusted (probability; 95% CI)**, b, c | 0.018 (0.016–0.021) | 0.026 (0.022–0.029) | 0.055 (0.044–0.067) |
Percentages for receipt of formal and informal caregiving and for hospital and nursing home admission are weighted using the HRS respondent population weights to adjust for the complex sampling design of the HRS.
*P < 0.001
**P < 0.05
aUsing the two-part model
bAdjusted for age, gender, race, education, living arrangement and net worth, incontinence, blood pressure, cancer, stroke, arthritis, fall-injured, diabetes, lung disease, psychiatric problem, dementia, and nursing home and hospital admission.
cUsing logistic regression with coefficients interpreted as probabilities
The unadjusted weekly hours of informal and formal care were also greatest for the CHF group. After adjustment for the other covariates, weekly informal in-home caregiving hours for those with CHF were significantly greater than those of the other two heart disease categories (P < 0.05; Table 4). However, there was no significant difference in formal in-home caregiving hours between the CHF group and the other two groups.
Hospital and Nursing Home Admission
Table 4 shows that 69.5% of individuals with CHF were hospitalized in the prior 2 years, as compared to 43% of those with CHD without CHF and 22.1% of those without CHD. Approximately 10.0% of respondents with CHF were in a nursing home in the prior 2 years, compared to 3.0% of respondents with CHD without CHF and 2% of those without CHD.
Additionally, Table 4 shows the unadjusted and adjusted hospitalization and nursing home admission rates by heart disease category. A higher proportion of CHF patients were hospitalized compared to respondents with CHD without CHF and no CHD. Adjustment for sociodemographics and health condition variables using logistic regression did not alter the differences in rates among the groups, which remained significant (P < 0.05). Nursing home admission was most common among those with CHF. After adjusting for sociodemographics and health condition using logistic regression, those with CHF still had significantly higher rates of nursing home admission (P < 0.05).
DISCUSSION
As the US population ages, the prevalence of CHF among older Americans is anticipated to increase significantly. Our study demonstrates a significantly greater burden of illness in geriatric conditions, functional limitations, in-home caregiving needs, and nursing home admission among older adults with CHF, as compared to those with CHD without CHF and those without CHD in a community-dwelling, nationally representative cohort. This analysis sheds greater light on the extent of disability in this highly vulnerable group.
The substantial burden of noncardiac comorbid illness in the CHF population has been well described by other investigators 20–23. Our study documents that, in addition, there is a high prevalence of geriatric conditions among older adults with CHF including, urinary incontinence, injury by fall, and dementia. Each of these conditions suggests the presence of a high degree of disability and often requires a multifaceted approach to effectively manage. For example, it is well known that dementia has an important impact on function, an older patient’s need for informal and formal support, and nursing home entry 13,24. A multidisciplinary approach to dementia care management and care coordination across healthcare delivery systems has been shown to improve patient care and caregiver support as well as delay institutionalization 25,26. The presence of CHF in a cognitively impaired individual further increases CHF-related morbidity and affects functional outcomes and the need for institutional care 27–29. A clinician’s failure to recognize cognitive deficits in a CHF patient could directly affect their clinical outcomes and quality of care.
To our knowledge, our study is the first to explicitly characterize the pattern of care utilized by the older CHF population and the significant time commitment that it imposes on family members. Families spend a substantial amount of time addressing the daily needs of this disabled population. Similarly, this population is also utilizing formal or paid sources of care; however, there was no statistically significant difference between the weekly hours of formal care compared to the other heart problem categories. This finding could be explained by two primary factors. First, compromised access to such services likely occurred because of the reduction in public spending for home- and community-based services in the late 1990s. The use of informal care by the CHF population in the setting of limited availability of formal services may represent substitution of informal services to address an unmet need. Second, physicians and other members of the healthcare team who participate in home care service referrals may be missing opportunities to refer eligible older patients 30,31. Improved methods to appropriately identify patients for home-based services and promote sound care coordination for older adults are likely needed.
Our study has some limitations that warrant comment. The proportion of respondents with CHF in our cohort was approximately 4%, which contrasts with other epidemiologic studies estimating the prevalence of CHF in older adults at 9–12% 32,33. Our low estimate could be explained by misclassification of respondents by heart disease category because of recall bias or the lack of full understanding of the CHF question by respondents. Although respondents were specifically asked if a physician had told them they had CHF, it is conceivable that respondents could have been misclassified by heart disease category because of a lack of familiarity with the diagnosis 34. CHF diagnoses were not confirmed by medical records of symptoms, medical therapy, or ejection fraction. Additionally, the CHF respondents captured in this HRS cohort may represent those with the greatest disease severity and, therefore, greater functional limitations. For all of these reasons, self-report of CHF as a diagnosis in this cohort likely represents a lower bound of the true prevalence; thus, our estimates of disability, caregiving, and other health outcomes could be over- or understated.
To date, the HRS survey questions concerning heart disease diagnoses have not been validated as a reliable means of identifying patients with CHF. Adjudication by an expert panel is considered to be the gold standard for establishment of CHF as a diagnosis 4. Prior work by Tisnado et al. 35 reported fair concordance between self-report of CHF and ambulatory managed care records, but no clinical databases have been used with the HRS to date. Nevertheless, self-report data such as our HRS data is an important data source for monitoring patient and caregiver experiences and perceptions, which are not routinely found in clinical databases. Future work is needed to compare the self-reported prevalence of CHF with the prevalence derived from Medicare data using HRS data linked to Medicare administrative files once available for public use.
Our study documents that older adults reporting CHF have a significantly higher prevalence of geriatric conditions, caregiving needs, and nursing home admission compared to those in the other heart disease categories. Additionally, CHF is independently associated with disability, even when other comorbidities are taken into account. These data suggest that the current approach of disease-specific care, for example a CHF disease management clinic, may be insufficient to care for this medically complex, frail population 21,23,36. Promoting care delivery systems that provide a coordinated, multidisciplinary approach to older adults with high medical complexity, like those with CHF, will be necessary to optimize care.
Acknowledgments
The National Institute on Aging (NIA) provided funding for the HRS (U01 AG09740), data from which were used for this analysis. The HRS is performed at the Institute for Social Research at the University of Michigan. Dr. Langa was supported by grants from the NIA (K08 AG19180) and R01 AG027010 and a Paul Beeson Physician Faculty Scholars in Aging Research award. Dr. Gure was supported by the VA Center for Practice Management and Outcomes Research and the RWJ Clinical Scholars Program. Dr. Blaum was supported by an NIA grant (R01 AG021493) and the Ann Arbor Veterans Affairs Geriatric Research, Education and Clinical Center (GRECC). The authors would like to thank Drs. Eve Kerr, Laurence McMahon, and Megumi Okumura for their thoughtful review of earlier versions of this manuscript.
Financial disclosures No financial disclosures were declared.
Authors’ contribution Dr. Gure was involved in developing the study concept, design, analysis and interpretation of the data, and the preparation of the manuscript. Mr. Kabeto was involved in developing the study design, analysis and interpretation of the data, and the preparation of the manuscript. Dr. Blaum was involved in developing the study concept, design, analysis and interpretation of the data, and preparation of the manuscript. Dr. Langa was involved in developing the study concept, design, analysis and interpretation of the data, and preparation of the manuscript.
Sponsor’s role No sponsor’s role was declared.
Conflict of interest None disclosed.
References
- 1.American Heart Association. Congestive Heart Failure. Heart Disease and Stroke Statistics, 2007.
- 2.O’Connell JB, Bristow MR. Economic impact of heart failure in the United States: time for a different approach. J Heart Lung Transplant. 1994;13(4):S107–12. (Jul–Aug). [PubMed]
- 3.Galbreath AD, Krasuski RA, Smith B, et al. Long-term healthcare and cost outcomes of disease management in a large, randomized, community-based population with heart failure. Circulation. 2004;110(23):3518–3526. (07 Dec). [DOI] [PubMed]
- 4.Mathew ST, Gottdiener JS, Kitzman D, Aurigemma G. Congestive heart failure in the elderly: the Cardiovascular Health Study. Am J Geriatr Cardiol. 2004;13(2):61–8. (Mar–Apr). [DOI] [PubMed]
- 5.Kemper P. The use of formal and informal home care by the disabled elderly. Health Serv Res. 1992;27(4):421–51. (Oct). [PMC free article] [PubMed]
- 6.McKinlay JB, Crawford SL, Tennstedt SL, McKinlay JB, Crawford SL, Tennstedt SL. The everyday impacts of providing informal care to dependent elders and their consequences for the care recipients. J Aging Health. 1995;7(4):497–528. (Nov). [DOI] [PubMed]
- 7.Guralnik JM, Alecxih L, Branch LG, et al. Medical and long-term care costs when older persons become more dependent. Am J Public Health. 2002;92(8):1244–5. (Aug). [DOI] [PMC free article] [PubMed]
- 8.Myers GC, Juster FT, Suzman RM. Asset and Health Dynamics Among the Oldest Old (AHEAD): initial results from the longitudinal study. Introduction. J Gerontol B Psychol Sci Soc Sci. 1997;52(Spec No):v–viii. (May). [PubMed]
- 9.Juster FT, Suzman R. An overview of the Health and Retirement Study. J Hum Resour. 1995;30:S7–56. [DOI]
- 10.Brandt J, Spencer M, Folstein M. The telephone interview for cognitive status. Neuropsychiatry Neuropsychol Behav Neurol. 1988;1:111–7.
- 11.Welsh KA, Breitner JCS, Magruder-Habib KM. Detection of dementia in the elderly using telephone screening of cognitive status. Neuropsychiatry Neuropsychol Behav Neurol. 1993;6:103–10.
- 12.Plassman BL, Newman T, Welsh KA, Breitner JCS. Properties of the telephone interview for cognitive status. Application in epidemiological and longitudinal studies. Neuropsychiatry Neuropsychol Behav Neurol. 1994;7:235–41.
- 13.Langa KM, Chernew ME, Kabeto MU, et al.. National estimates of the quantity and cost of informal caregiving for the elderly with dementia. J Gen Intern Med. 2001;16(11):770–8. (Nov). [DOI] [PMC free article] [PubMed]
- 14.Herzog A, Wallace RB, Herzog A, Wallace RB. Measures of cognitive functioning in the AHEAD Study. J Gerontol B Psychol Sci Soc Sci. 1997;52(Spec No):37–48. (May). [DOI] [PubMed]
- 15.Langa KM, Larson EB, Wallace RB, et al. Out-of-pocket health care expenditures among older Americans with dementia. Alzheimer Dis Assoc Disord. 2004;18(2):90–8. (Apr–Jun). [DOI] [PubMed]
- 16.Norgard TM, Rodgers WL. Patterns of in-home care among elderly black and white Americans. J Gerontol B Psychol Sci Soc Sci. 1997;52(Spec No):93–101. (May). [DOI] [PubMed]
- 17.Manning WG. The logged dependent variable, heteroscedasticity, and the retransformation problem. J Health Econ. 1998;17(3):283–95. [DOI] [PubMed]
- 18.Efron B. The jacknife: The bootstrap and other resampling plans. Philadelphia: Society for Industrial and Applied Mathematics; 1982.
- 19.StataCorp. Stata 9.0 ed. College Station, TX: StataCorp; 2005.
- 20.Wolff JL, Starfield B, Anderson G. Prevalence, expenditures, and complications of multiple chronic conditions in the elderly. Arch Intern Med. 2002;162(20):2269–76. (Nov 11). [DOI] [PubMed]
- 21.Braunstein JB, Anderson GF, Gerstenblith G, et al. Noncardiac comorbidity increases preventable hospitalizations and mortality among Medicare beneficiaries with chronic heart failure. J Am Coll Cardiol. 2003;42(7):1226–33. (Oct 1). [DOI] [PubMed]
- 22.Wolff JL, Boult C, Boyd C, Anderson G. Newly reported chronic conditions and onset of functional dependency. J Am Geriatr Soc. 2005;53(5):851–5. (May). [DOI] [PubMed]
- 23.Zhang JX, Rathouz PJ, Chin MH. Comorbidity and the concentration of healthcare expenditures in older patients with heart failure. J Am Geriatr Soc. 2003;51(4):476–82. (Apr). [DOI] [PubMed]
- 24.Banaszak-Holl J, Fendrick AM, Foster NL, et al. Predicting nursing home admission: estimates from a 7-year follow-up of a nationally representative sample of older Americans. Alzheimer Dis Assoc Disord. 2004;18(2):83–9. (Apr–Jun). [DOI] [PubMed]
- 25.Brodaty H, Green A, Koschera A, Brodaty H, Green A, Koschera A. Meta-analysis of psychosocial interventions for caregivers of people with dementia. J Am Geriatr Soc. 2003;51(5):657–64. (May). [DOI] [PubMed]
- 26.Mittelman MS, Ferris SH, Shulman E, et al. A family intervention to delay nursing home placement of patients with Alzheimer disease. A randomized controlled trial. JAMA. 1996;276(21):1725–31. (Dec 4). [DOI] [PubMed]
- 27.Almeida OP, Flicker L. The mind of a failing heart: a systematic review of the association between congestive heart failure and cognitive functioning. Intern Med J. 2001;31(5):290–5. (Jul). [DOI] [PubMed]
- 28.Trojano L, Antonelli Incalzi , Acanfora D, et al. Cognitive impairment: a key feature of congestive heart failure in the elderly. J Neurol. 2003;250(12):1456–63. (Dec). [DOI] [PubMed]
- 29.Zuccala G, Marzetti E, Cesari M, et al. Correlates of cognitive impairment among patients with heart failure: results of a multicenter survey. Am J Med. 2005;118(5):496–502. (May). [DOI] [PubMed]
- 30.Bowles KH, Naylor MD, Foust JB, Bowles KH, Naylor MD, Foust JB. Patient characteristics at hospital discharge and a comparison of home care referral decisions. J Am Geriatr Soc. 2002;50(2):336–42. (Feb). [DOI] [PubMed]
- 31.Naylor MD, Brooten D, Campbell, et al. Comprehensive discharge planning and home follow-up of hospitalized elders: a randomized clinical trial. JAMA. 1999;281(7):613–20. (Feb 17). [DOI] [PubMed]
- 32.Gillum RF. Epidemiology of heart failure in the United States. Am Heart J. 1993;126(4):1042–7. (Oct). [DOI] [PubMed]
- 33.Kitzman DW, Gardin JM, Gottdiener JS, et al. Importance of heart failure with preserved systolic function in patients ≥65 years of age. CHS Research Group. Cardiovascular Health Study. Am J Cardiol. 2001;87(4):413–9. (Feb 15). [DOI] [PubMed]
- 34.Horowitz C, et al. A story of maladies, misconceptions and mishaps: effective management of heart failure. Soc Sci Med. 2004;58(3):631–43. (Feb). [DOI] [PMC free article] [PubMed]
- 35.Tisnado DM, Adams JL, Liu H, et al. What is the Concordance Between the Medical Record and Patient Self-Report as Data Sources for Ambulatory Care? Med Care. 2006;44(2):132–40. (Feb). [DOI] [PubMed]
- 36.Rich MW. Heart failure disease management programs: efficacy and limitations. Am J Med. 2001;110(5):410–2. (Apr 1). [DOI] [PubMed]