Association of Alzheimer's Disease and Related Dementias (ADRD) With Days at Home Among Medicare Beneficiaries After a Heart Failure Hospitalization.

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Published in final edited form as: Circ Cardiovasc Qual Outcomes. 2025 Apr 30;18(6):e011246. doi: 10.1161/CIRCOUTCOMES.124.011246 Association of Alzheimer’s Disease and Related Dementias (ADRD) With Days at Home among Medicare Beneficiaries after a Heart Failure Hospitalization Hannah W Mitlak 1 , Cisco G Espinosa 1 , Michael P Thompson 2 , Kathleen A Ryan 3 , Deborah A Levine 4 , Na Sun 5 , Raya E Kheirbek 6 , Madeline R Sterling 1, * , Jason Falvey 5, 7, * Author information Article notes Copyright and License information 1 Department of Medicine, Weill Cornell Medicine, New York, NY 2 Department of Cardiac Surgery, University of Michigan Medical School, Ann Arbor, MI 3 Department of Medicine, University of Maryland School of Medicine 4 Department of Medicine, University of Michigan Medical School, Ann Arbor, MI 5 Department of Physical Therapy and Rehabilitation Science, University of Maryland School of Medicine 6 University of Maryland School of Medicine, Department of Medicine, Division of Geriatrics and Palliative Medicine 7 Department of Epidemiology and Public Health, University of Maryland School of Medicine * Authors contributed equally as senior authors ✉ Corresponding author : Madeline R Sterling, MD, MPH, MS, FAHA, Associate Professor of Medicine, Division of General Internal Medicine, Weill Cornell Medicine, 420 East 70 th Street, LH-357, New York, NY, 10021, mrs9012@med.cornell.edu Issue date 2025 Jun. PMC Copyright notice PMCID: PMC12173780  NIHMSID: NIHMS2069991  PMID: 40304047 The publisher's version of this article is available at Circ Cardiovasc Qual Outcomes Abstract Background: Older adults with concomitant heart failure (HF) and ADRD are at high risk for adverse outcomes, including healthcare utilization and mortality. Increasingly, adults with these conditions want to maximize quality of life and days at home (DAH). This study aimed to determine the association between ADRD and DAH following HF hospitalization. Methods: This retrospective cohort analysis draws from a 20% random sample of 2017–2019 Medicare claims of beneficiaries who survived HF hospitalization. The primary outcome was mean DAH six months post-hospitalization. Exposure was defined as presence of diagnosed ADRD, extracted from MBSF Chronic Conditions subfile. Multivariable negative binomial regression was used to examine the adjusted association between ADRD and DAH, with covariates selected in accordance with the Andersen model of healthcare utilization. Results: The 74,908 Medicare beneficiaries in the cohort had a mean age of 79.1 years (SD 11); half were men (50.0%) and 82.3% were non-Hispanic White. Overall, 18% (n=14,396) had ADRD. Beneficiaries with concomitant ADRD were older, more likely to be female, and more likely to have dual Medicaid/Medicare eligibility compared to those without ADRD. Although DAH in the six months preceding admission was similar, following hospitalization those with concomitant ADHD had less time at home (mean DAH 120.7 [65.9] for those with ADRD vs. 136.4 [59.7] for those without ADRD). When adjusting for patient characteristics, hospitalization course, and hospital and geographic-level fixed effects, this difference persisted: HF patients with ADRD spent an estimated 6% fewer DAH post-hospitalization (IRR=0.94, 0.93–0.95). In the six months post-hospitalization, 10.2% of HF patients with ADRD spent ≤7 DAH. The odds of spending ≤7 DAH were 24% higher for ADRD patients (OR=1.24, 95% CI 1.16–1.33). Conclusions: Following HF hospitalization, Medicare beneficiaries with ADRD spent significantly fewer DAH than those without ADRD. Identifying and addressing the unmet needs of this population after hospitalization is crucial. Keywords: Alzheimer’s Disease and Related Dementias, heart failure, days at home, transitions in care, patient-centered outcomes Introduction Heart failure (HF) affects 6.7 million people in the US and is associated with a high risk of morbidity, mortality, and poor quality of life. 1 , 2 HF is also associated with high healthcare utilization, including hospitalizations and readmissions. 3 A decline in physical function and the need for institution-based care after discharge (i.e., skilled nursing facilities [SNFs] and nursing homes) are also common after HF hospitalization. 4 This is of concern because many adults with HF may want to remain at home and maximize functional independence for as long as possible in order to “age in place.” 5 Adults with HF who also have Alzheimer’s disease or related dementias (ADRD) have worse outcomes than patients with HF alone. 6 – 9 Adults with HF are at a higher risk for cognitive impairment and ADRD compared to similarly aged patients without HF, which may reflect the underlying geriatric vulnerabilities of HF patients (i.e., multimorbidity and frailty) and the pathophysiology of HF itself, which can lead to decreased perfusion. 10 – 12 Notably, the prevalence of cognitive impairment in HF is high, ranging from 14 to 80% in the literature, 6 , 13 – 16 and the prevalence of ADRD in HF ranges between 12% and 21%. 7 , 8 , 17 – 19 Patients with concomitant HF and ADRD are at greater risk of mortality and hospitalization than patients with HF alone, 9 , 20 experience greater reductions in function and self-care, 6 , 7 and are at elevated risk for admission to SNFs. 21 – 23 However, less is known about the impact of ADRD on patient-centered outcomes after HF hospitalization. While hospitalizations, mortality, and readmissions are traditionally used to assess HF patients’ health and healthcare utilization, these metrics fail to account for the long-term impacts on patient function and quality of life, 24 – 26 and do not account for patient preferences. 27 In response, days at home (DAH) emerges as a valuable, patient-centered measure, reflecting successful aging in place. 28 – 30 Despite its growing use, few studies have applied DAH to understanding illness trajectory among HF patients with ADRD. 24 , 31 , 32 This gap underscores the need for research aimed at enhancing DAH and, by extension, the quality of life in this high-risk population post-discharge. Our study, therefore, seeks to elucidate the impact of ADRD on DAH following HF hospitalization among a national cohort of Medicare beneficiaries. To that end, we aimed to examine the impact of ADRD on DAH after a HF hospitalization among a national sample of Medicare beneficiaries. Methods The data, analytic methods, and study materials will not be made available to other researchers for purposes of reproducing the results or replicating the procedure, as these data can only be accessed after entering into data use agreements with the Center for Medicare and Medicaid Services. This study of Medicare claims data was deemed exempt by the University of Maryland Baltimore Institutional Review Board. Sample The sample was composed of a retrospective cohort of HF admissions among Medicare beneficiaries who survived at least 1 day following discharge, drawn from a 20% random sample of Medicare claims from 2017–2019. If a beneficiary had multiple hospitalizations for HF within any 6-month period, only data from the first hospitalization was included. Hospitalization course data (e.g., length of stay) was extracted from the Medicare Provider and Analysis Review (MEDPAR) file, nursing facility length of stay from the Minimum Data Set (MDS) 3.0, outpatient claims for hospital emergency departments and observation stays, and demographic information (e.g., age, sex) from the Master Beneficiary Summary Base File (MBSF). Methods used to combine Medicare data follow standard practices for health services research as recommended by Medicare Research Data Assistance Center. 33 For this study, we included beneficiaries with continuous Medicare Parts A and B coverage six months prior to and six months following the index HF hospitalization date (or until the date of death). Beneficiaries were excluded if they were admitted to the hospital from a long-stay nursing home or were discharged against medical advice. 34 Overall, the final analytic sample comprised 80,391 HF admissions from 74,908 survivors who were alive for at least 1 day post-discharge ( Supplemental Figure S1 ). Outcome: Days at Home (DAH) The measure of DAH was based on prior work that assessed “days alive and out of the hospital,” and subtracted days in the emergency room and days under hospital observation. 35 , 36 Specifically, the count of days spent at home in the 180 days following HF admission was calculated by subtracting the number of days in a hospital and/or rehabilitation facility (from MEDPAR files), nursing home (from MDS file), emergency department or hospital observation stay (Outpatient claims files), and days not alive (index HF admission day to date of death, if applicable, from the MBSF). ADRD Status A diagnosis of ADRD prior to HF hospitalization was the primary exposure of interest. ADRD diagnosis was extracted from the MBSF Chronic Conditions subfile, which uses a validated algorithm to identify claims with International Classification of Disease (ICD)-9 or ICD-10 codes listed on the Chronic Conditions Data Warehouse website. 37 Covariates We selected covariates according to the Andersen model of healthcare utilization, a multilevel model which incorporates both individual and contextual factors in assessing use of health services. 38 Following the model, covariates can be categorized as predisposing, enabling, need, and healthcare utilization factors. 39 Predisposing covariates, which comprise individual demographics consisted of age at time of hospitalization and sex. Enabling factors included dual eligibility status for Medicaid in any of the six months prior to HF admission (Yes/No) from the MBSF, index hospital bed size, and teaching status of the index hospital for each HF survivor, as well as contextual factors based in their county of residence that may influence DAH including rurality (determined by rural-urban continuum codes from the US Department of Agriculture) and the number of nursing home beds per 100,000 residents at the county level. Needs factors included multimorbidity, assessed using the Elixhauser index, a sum score of comorbidities (maximal range: 0 to 30) based on ICD-9 and ICD-10 diagnosis codes present in claims at the time of hospitalization and coded using a validated algorithm which was modified in this study to exclude ADRD. 40 Statistical Analysis The sample characteristics were compared by ADRD status using descriptive statistics. The unadjusted mean DAH was plotted in days over each of the six pre-hospitalization and six post-hospitalization months by ADRD status. To examine the adjusted association between ADRD and DAH among adults hospitalized for HF we used multivariable negative binomial regression, with a log-link function and adjustment for correlation between repeated observations of beneficiaries assuming an exchangeable correlation structure. The resultant incidence rate ratios (IRR) represent the relative difference in DAH between those with ADRD as compared to those without ADRD. Adjusted models included terms for age, dual eligibility status, Elixhauser score, DAH in the six months prior to hospitalization, intensive care unit stay (Yes/No), year of hospitalization, and contextual factors at the facility and geographic level including county level poverty rates from the American Community Survey, rurality, hospital teaching status, hospital bed size, and both number of nursing home beds and primary care availability at the county level per 100,000 population (tertiles). Predicted mean counts and 95% confidence intervals were then calculated from adjusted models to provide an estimate of absolute differences between HF patients with and without a diagnosis of ADRD. Beyond average recovery, we also modeled the associations between ADRD status and extremely short home times after HF admission – an important subgroup for whom rapid allocation of palliative and supportive care resources would be of high value. We defined ultra-short home time as seven or fewer days based on patient and care partner identified cut points defined in prior work with seriously ill older adults and their care partners. 41 We assessed crude differences in the rates of spending ≤7 days at home versus ≥8 days at home. Subsequently, we employed a generalized linear mixed model, assuming a binomial distribution and implementing an exchangeable correlation structure, to accommodate repeated measurements from the same individuals. We then utilized the adjusted models to estimate the marginal probabilities, which allowed us to assess the absolute differences in rates of extremely short home stay durations between individuals with and without ADRD when all covariates were set to their mean values. Only 1.4% of observations were missing data, thus adjusted analyses considered complete case data. All analyses were completed using SAS 9.4 software (SAS Institute, Cary, NC). Results The final analytic sample included 80,391 HF admissions contributed by 74,908 beneficiaries who survived an index HF admission. The mean age of the sample was 79.1 years (SD 11.0), half were men (50.0%), 82.3% were non-Hispanic White, and 22.3% were dual Medicaid/Medicare eligible ( Table 1 ). Overall, 18% (n=14,503) of adults hospitalized for HF had concurrent ADRD. As compared to those without ADRD, HF patients with ADRD were older, more likely to be female, and more likely to have dual Medicaid/Medicare eligibility. Those with ADRD had similar comorbidity burden, hospital length of stays, but higher rates of discharge to a facility (36% vs 23%) compared to those without ADRD ( Table 1 ). The rate of six-month mortality after HF admission was 33% (n=4,728/14,396) of those with ADRD, as compared with 25% (n=16,214/65,995) of those without ADRD. Table 1. Characteristics of Heart Failure (HF) Admissions Among Medicare Beneficiaries by the Presence of Alzheimer’s Disease and Related Dementias (ADRD) Overall Sample Presence of ADRD Diagnosis prior to HF Admission Date No ADRD Diagnosis ADRD Diagnosis N (%) N (%) N (%) Total 80,391 (100.00) 65,995 (82.09) 14,396 (17.91) Mean ± SD Mean ± SD Mean ± SD Age at HF Admission Date 79.13 ± 11.04 78.14 ± 11.15 83.73 ± 9.24 Elixhauser Comorbidity Index 6.20 ± 1.85 6.18 ± 1.85 6.28 ± 1.83 DAH, Prior Six Months 171.58 ± 13.89 172.03 ± 13.37 169.48 ± 15.89 Hospital Length of Stays, Days 4.88 ± 4.23 4.87 ± 4.31 4.91 ± 3.89 N (%) N (%) N (%) Sex (Female) 40,158 (49.99) 32,006 (48.50) 8,179 (56.81) Race / Ethnicity * Non-Hispanic White 66,148 (82.28) 54,299 (82.28) 11,849 (82.31) Black 10,059 (12.51) 8,328 (12.62) 1,731 (12.02) Other 2,510 (3.12) 2032 (3.07) 478 (3.33) Hispanic 1,225 (1.52) 929 (1.41) 296 (2.06) Medicaid-Medicare Dual Eligible 18,040 (22.34) 14,147 (21.34) 3893 (26.92) ICU Admission/ Stay 5,870 (7.27) 4,947 (7.46) 923 (6.38) Discharge Disposition (Home or Home Health Care) 60,243 (74.60) 51,001 (76.92) 9,242 (63.92) Teaching Hospital Status (Teaching Hospital) 42,781 (52.97) 35,162 (53.03) 7,619 (52.69) Bed Size, Tertiles † <232 26,759 (33.29) 21,966 (33.28) 4,793 (33.29) 232–435 26,795 (33.33) 21,877 (33.15) 4,918 (34.16) >435 26,811 (33.35) 22,128 (33.53) 4,683 (32.53) Rurality ‡ Urban 64,403 (79.75) 52,395 (79.11) 12,008 (83.09) Rural, Urban Adjacent 10,889 (13.48) 9,256 (13.98) 1633 (11.30) Rural, Not Urban Adjacent 5,386 (6.67) 4,576 (6.91) 810 (5.61) Percentage of Residents Living Below the Poverty Line (Tertiles) § <11.9% 26,812 (33.35) 22,003 (33.34) 4,809 (33.41) 11.9% – 16.4% 26,748 (33.27) 22,073 (33.45) 4,675 (32.47) >16.4% 26,750 (33.27) 21,846 (33.10) 4,904 (34.07) Number of Primary Care Physicians per 100,000 People (Tertiles) || < 58.9 26,613 (33.10) 22,235 (33.69) 4,378 (30.41) 58.9 – 85.0 26,716 (33.23) 21,610 (32.74) 5,106 (35.47) >85.0 26,741 (33.26) 21,865 (33.13) 4,876 (33.87) County-Level Nursing Home Beds # < 698 26,474 (32.93) 22,337 (33.85) 4,137 (28.74) 698– 2845 26,476 (32.93) 21,834 (33.08) 4,642 (32.25) >2845 26,486 (32.95) 21,002 (31.82) 5,484 (38.09) Open in a new tab * Race/Ethnicity unknown or missing in N=455 (0.56%) † Hospital bed size unknown or missing in N=26 (0.03%) ‡ Rurality unknown or missing in N=81 (0.10%) § Percent of residents living below the federal poverty line unknown or missing in N=81 (0.10%) || Number of primary care physicians per 100,000 people unknown or missing in N=321 (0.40%) # Number of nursing home beds per 100,000 people unknown or missing in N=955 (1.19%) HF: Heart Failure, ADRD: Alzheimer’s Disease and Related Dementias, DAH: Days at Home In the 180 days following HF hospitalization, Medicare beneficiaries had a mean (SD) DAH of 133.6 (61.2) compared to 171.6 (13.9) DAH six months prior to admission. While unadjusted DAH were marginally lower among those with ADRD as compared to those without ADRD during the six-months pre-hospitalization (169.5 [15.9] vs 171.6 [13.9]), the differences were larger during the six months following hospital discharge (mean DAH 120.7 [65.9] for those with ADRD vs. 136.4 [59.7] for those without ADRD) ( Figure 1 ). Approximately 61% of the disparity in days at home (DAH) between persons with and without ADRD was due to differences in mortality. Differences in facility time were mostly driven by increased use of SNFs among HF survivors with ADRD as compared to those without ADRD ( Figure 2 ). Figure 1. Days at home (DAH) After Heart Failure (HF) Hospitalization by Alzheimer’s Disease and Related Dementias (ADRD) status. Open in a new tab Line graphs comparing mean days at home (DAH) for patients included in the sample (n=80,391) with ADRD (n=14,369) and without ADRD (n=65,995) and alive at each time point. The number of days in each month period ranged from 0 to 30. Figure 2. Days Not at Home Among Heart Failure (HF) Survivors By Alzheimer’s Disease and Related Dementias (ADRD) Status. Open in a new tab Bar graph illustrating the number of days spent away from home following the index heart failure hospitalization, categorized by the type of facility and stratified by ADRD status. For clarity, days associated with mortality are excluded from this graph – notably, HF survivors living with ADRD had a higher average number of mortality days (36.9 vs. 27.3 days). HF: Heart Failure, ADRD: Alzheimer’s Disease and Related Dementias, SNF; Skilled nursing facility, LTC: Long term care, ED: Emergency department In a fully adjusted model, the association between ADRD and fewer DAH persisted. In this adjusted model, ADRD diagnosis among HF survivors was associated with an estimated 6.0% fewer DAH (IRR=0.94, 0.93–0.95), representing a predicted mean difference of 7.8 days (mean adjusted estimate of DAH, ADRD: 125.8, 95% CI: 124.7–127.0; without ADRD:133.6, 95% CI 133.2–134.1). In addition to average differences in DAH, we also estimated the associations between ADRD status and ultra-short home time. Of our sample, 7.1% (n=5,736/80,391) had ultra-short home time after discharge – this crude rate was more than 50% greater for those with ADRD as compared to those without ADRD (10.2% [n=1,473/14,396] with ADRD vs 6.5% [4,263/65,995] without ADRD). Nearly 38% (n=2,166/5,736) of those with ultra-short home time died within 7 days of hospital discharge. In the fully adjusted model, the odds of spending ≤7 DAH over six months following discharge were 24% higher on a relative scale for those with ADRD as compared to those without ADRD (OR=1.24, 95% CI 1.16–1.33). The predicted probability of spending ≤7 DAH was 7.0% (95% CI 6.6 to 7.4) for those with ADRD and 5.7% (95% CI 5.5 to 5.9) for those without ADRD. Discussion In this national study, we found that following HF hospitalization, Medicare beneficiaries with ADRD spent significantly fewer DAH than those without ADRD, and the magnitude of this difference was clinically meaningful. 41 Additionally, nearly 1 in 10 older adults with ADRD and hospitalized for HF spent less than 7 DAH after discharge. While some of this disparity was due to differences in mortality, most of this time away from home among non-decedents was spent in SNFs, which may not always be aligned with patient-centered goals for this group. Interventions to meet the needs of this patient population, including those that may improve short-term transitions and long-term care needs, are needed. There are many mechanisms by which ADRD can disproportionately impact HF patients and lead to poor outcomes. HF often results in inadequate brain perfusion due to cerebrovascular hemodynamic and structural changes, which can lead to cognitive impairment. 42 ADRD, a more severe form of cognitive impairment, interferes with global and executive function, which are critical for HF self-care. 43 Prior studies have shown that HF hospitalizations themselves are associated with acute and long-term declines across specific cognitive domains. 44 These declines are likely to further limit physical and cognitive function for HF patients, and, in turn, DAH, especially for those with ADRD. Reduced independence and limited self-care efficacy add to caregiver burden, and may limit DAH post-discharge, and increase likelihood of discharge to a SNF. Recent estimates suggest that 75% of older adults want to age in place, and claims-based measures of home time may be one way to assess how successfully health systems and providers are supporting this priority on a population level, and help evaluate where in the recovery process may be most appropriate to intervene. 45 , 46 Our study adds to the literature on the use of DAH as a patient-centered outcome, offering additional data to support discharge decision making for patients with HF and comorbid ADRD and their care partners. 47 For example, DAH can help to inform goals of care conversations and expectations for patients and their caregivers following discharge. More practically, DAH can be employed to aid in resource planning to ensure successful transition and long-term success for patients at home, including timely post-discharge ambulatory follow-up and connection with home services as needed. 48 , 49 While DAH is a useful construct in weighing treatment decisions, it is important to note that the terminology and definitions regarding time spent at home as a patient-centered outcome are still being defined, particularly around differences in observation periods and inclusion of mortality. 24 , 29 , 31 It is also unclear to what extent different DAH thresholds would be useful in communicating prognosis to patients with HF and ADRD following hospitalization – while a 7-day cutoff used in the current research is grounded in current literature, additional validation research specific to the needs for patients with HF is needed to evaluate concurrent validity with other functional classifications (e.g., New York Heart Association), health markers, and quality of life for both patients and care partners. 41 , 50 Further investigating patient preferences can help standardize these metrics and ensure interventions are evaluated concordantly. To achieve a standardized definition of DAH, a consensus-building process involving a multidisciplinary panel of experts, patients, and caregivers is recommended. This process should aim to establish clear guidelines on observation periods, the inclusion of mortality, and the qualitative aspects of time spent at home versus time in different healthcare settings. The observed gap in DAH immediately following hospitalization, along with the increased early use of SNFs among those with ADRD, points to the importance of optimizing care transitions for this group. High rates of healthcare utilization and discharge to low quality SNFs have been well-established. 51 , 52 While prior efforts have focused on this for HF patients, given the time spent in SNF by ADRD patients, special attention is needed to ensure patient needs are met. 53 , 54 To do this, more comprehensive interventions may be required across the care continuum – starting in the inpatient setting, through post-acute care, and especially during transition to the community from both of these settings. For example, increased ambulation and physical therapy services, supporting improvements in functional status, during hospitalization is associated with lower readmission risk and improved clinical outcomes for HF patients. 55 – 58 Preparing HF patients, especially those with high functional needs, for discharge home from hospital stays also includes a careful assessment of unmet needs (e.g., durable medical equipment, caregiver training) and coordinating with community partners to ensure these supports, both formal and informal, can be delivered in a timely way. 58 Prior work suggests that better connections with formal home care and mental health services may better support community discharge and home time among older adults, including patients living with HF and ADRD. 49 , 59 , 60 For a subset of patient in our study with ultra-short home time, it is possible these mobilizing these supports more rapidly during home discharges may support home time, but further research is needed in this important area. However, ultra-short home time may also signal substantial health vulnerability or mortality risk that would benefit from accelerated referrals for palliative and hospice care. These services, when delivered in a timely way, support patient and caregiver needs, and regularly counseling on these options may help improve equity in end-of-life care utilization. 61 Finally, given the degree to which family caregivers of patients with concomitant HF and ADRD experience strain, addressing their needs is also critical. Owing to this, in 2023, CMS introduced the Guiding an Improved Dementia Experience (GUIDE) Model, a proposed framework for improving care coordination and reducing caregiver strain through caregiver education, support, and respite services. 62 The framework provides for unpaid caregiver training and reimbursement to alleviate the financial burden and strain, as well as measures to align financial incentives with longitudinal care through per-beneficiary monthly payments. 63 Additional research is needed to see how this model impacts outcomes for ADRD patients with chronic conditions, like HF and how ADRD patient and caregiver priorities differ during recovery from serious illness. 64 Strengths and limitations This study has several strengths. First, is its large, representative sample size, afforded by Medicare claims data. Second, DAH is a patient-centered measure that was operationalized according to literature and prior studies. Finally, covariates were carefully selected and informed using a conceptual model. Limitations, however, are notable. The study sample was defined by HF diagnosis and stratified by ADRD status, which introduces possible selection bias as ADRD is historically underdiagnosed. 65 Another limitation lack of representation, as the sample is primarily composed of non-Hispanic White beneficiaries, reflective of the current Medicare population. The homogeneity of this sample compared to the population likely understates the effect of dual HF ADRD diagnosis on the ability for patients to successfully age at home. 66 The effects of combined HF and ADRD will likely have a greater impact than this study found, especially as the aging population becomes more diverse. Additionally, while Medicare claims data accounts for presence of HF and ADRD, it lacks the ability to detect disease severity, which may impact outcomes and discharge disposition. Similarly, while DAH represents a more patient-centric outcome, it does not capture quality of life or symptom burden at home, which may be particularly relevant in care of patients with ADRD. Finally, we did not investigate formal use of home health care services, which a third of HF patients receive at home after hospitalization and may impact DAH. 67 Future studies are necessary to investigate the impact these factors, while also investigating the lived experiences (via qualitative research) of patients with HF and ADRD to provide a more robust understanding of quality home time, and further guide clinical management and policies. Conclusion In a nationally representative cohort of older adults recovering from HF hospitalization, Medicare beneficiaries with ADRD spent significantly fewer DAH than those without ADRD, a difference that was clinically meaningful. Notably, beneficiaries spent similar DAH pre-HF hospitalization, suggesting that ADRD patients may be particularly vulnerable in the post-discharge period. Further research is warranted to develop and implement targeted interventions for patients with ADRD and HF who want to remain at home after a HF hospitalization event. Supplementary Material RECORD checklist NIHMS2069991-supplement-RECORD_checklist.pdf (1.1MB, pdf) Fig S1 NIHMS2069991-supplement-Fig_S1.pdf (131.8KB, pdf) What is known: Older adults with heart failure (HF) are at risk for high healthcare utilization and poor clinical outcomes; those with comorbid Alzheimer’s Disease and Related Dementias (ADRD) are even more vulnerable. Days at home (DAH) is a novel, patient-centered outcome that is well suited to this patient population and is important to investigate given its alignment with patient preferences following hospitalization. What the study adds: This retrospective national cohort analysis of Medicare beneficiaries found that preceding HF hospitalization older adults had similar DAH regardless of ADRD status, but following discharge after a HF hospitalization, Medicare beneficiaries with comorbid HF and ADRD had significantly fewer DAH. In addition to fewer DAH, ADRD patients were at increased risk of spending less than 7 DAH following HF hospitalization. DAH is an important and clinically meaningful measure that can be operationalized to understand patient preferences and tailor interventions in the post-discharge period to improve outcomes. Funding Dr. Sterling is supported by the National Heart, Lung, and Blood Institute (K23HL150160 and R01HL169312), both related to this work. Dr. Falvey is supported by the National Institute on Aging (K76AG074926). Dr. Levine is supported by the NIH. Dr. Thompson receives funding from the Agency for Healthcare Research and Quality and Blue Cross Blue Shield of Michigan. We acknowledge the support of the University of Maryland Baltimore, Institute for Clinical & Translational Research (ICTR) and the National Center for Advancing Translational Sciences (NCATS) Clinical Translational Science Award (CTSA) (1UL1TR003098) in helping secure Medicare data and providing support for analysis. Abbreviations HF Heart Failure ADRD Alzheimer’s Disease and Related Dementias DAH Days At Home SNF Skilled Nursing Facilities Footnotes Disclosures None Supplemental Material Figure S1 . Exclusion Cascade of Sample References 1. Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, et al. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation. 2023;147:e93–e621. doi: 10.1161/cir.0000000000001123 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 2. Heidenreich PA, Bozkurt B, Aguilar D, Allen LA, Byun JJ, Colvin MM, Deswal A, Drazner MH, Dunlay SM, Evers LR, et al. 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. J Am Coll Cardiol. 2022;79:e263–e421. doi: 10.1016/j.jacc.2021.12.012 [ DOI ] [ PubMed ] [ Google Scholar ] 3. Agarwal MA, Fonarow GC, Ziaeian B. National Trends in Heart Failure Hospitalizations and Readmissions From 2010 to 2017. JAMA Cardiol. 2021;6:952–956. doi: 10.1001/jamacardio.2020.7472 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 4. Bueno H, Ross JS, Wang Y, Chen J, Vidán MT, Normand SL, Curtis JP, Drye EE, Lichtman JH, Keenan PS, et al. Trends in length of stay and short-term outcomes among Medicare patients hospitalized for heart failure, 1993–2006. Jama. 2010;303:2141–2147. doi: 10.1001/jama.2010.748 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 5. Ratnayake M, Lukas S, Brathwaite S, Neave J, Henry H. Aging in Place:: Are We Prepared? Dela J Public Health. 2022;8:28–31. doi: 10.32481/djph.2022.08.007 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 6. Lovell J, Pham T, Noaman SQ, Davis MC, Johnson M, Ibrahim JE. Self-management of heart failure in dementia and cognitive impairment: a systematic review. BMC Cardiovasc Disord. 2019;19:99. doi: 10.1186/s12872-019-1077-4 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 7. Jensen MS, Cenzer I, Kelley AS, Covinsky KE. Heart failure with comorbid dementia: Association with clinical characteristics and outcomes. J Am Geriatr Soc. 2023. doi: 10.1111/jgs.18467 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 8. Gilstrap L, Cohen A, Ouellet GM, Goyal P, Gladders B, Flint D, Skinner J. The association between beta-blockers and outcomes in patients with heart failure and concurrent Alzheimer’s disease and related dementias. J Am Geriatr Soc. 2023;71:404–413. doi: 10.1111/jgs.18086 [ DOI ] [ PubMed ] [ Google Scholar ] 9. Ren QW, Katherine Teng TH, Tse YK, Tay WT, Li HL, Tromp J, Yu SY, Hung D, Wu MZ, Chen C, et al. Incidence, Clinical Correlates, and Prognostic Impact of Dementia in Heart Failure: A Population-Based Cohort Study. JACC Asia. 2023;3:108–119. doi: 10.1016/j.jacasi.2022.09.016 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 10. Scherbakov N, Doehner W. Heart-brain Interactions in Heart Failure. Card Fail Rev. 2018;4:87–91. doi: 10.15420/cfr.2018.14.2 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 11. Doehner W, Ural D, Haeusler KG, Čelutkienė J, Bestetti R, Cavusoglu Y, Peña-Duque MA, Glavas D, Iacoviello M, Laufs U, et al. Heart and brain interaction in patients with heart failure: overview and proposal for a taxonomy. A position paper from the Study Group on Heart and Brain Interaction of the Heart Failure Association. Eur J Heart Fail. 2018;20:199–215. doi: 10.1002/ejhf.1100 [ DOI ] [ PubMed ] [ Google Scholar ] 12. Tazzeo C, Rizzuto D, Calderón-Larrañaga A, Roso-Llorach A, Marengoni A, Welmer AK, Onder G, Trevisan C, Vetrano DL. Multimorbidity patterns and risk of frailty in older community-dwelling adults: a population-based cohort study. Age Ageing. 2021;50:2183–2191. doi: 10.1093/ageing/afab138 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 13. Sterling MR, Jannat-Khah D, Bryan J, Banerjee S, McClure LA, Wadley VG, Unverzagt FW, Levitan EB, Goyal P, Peterson JC, et al. The Prevalence of Cognitive Impairment Among Adults With Incident Heart Failure: The “Reasons for Geographic and Racial Differences in Stroke” (REGARDS) Study. J Card Fail. 2019;25:130–136. doi: 10.1016/j.cardfail.2018.12.006 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 14. Vogels RL, Scheltens P, Schroeder-Tanka JM, Weinstein HC. Cognitive impairment in heart failure: a systematic review of the literature. Eur J Heart Fail. 2007;9:440–449. doi: 10.1016/j.ejheart.2006.11.001 [ DOI ] [ PubMed ] [ Google Scholar ] 15. Hajduk AM, Kiefe CI, Person SD, Gore JG, Saczynski JS. Cognitive change in heart failure: a systematic review. Circ Cardiovasc Qual Outcomes. 2013;6:451–460. doi: 10.1161/circoutcomes.113.000121 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 16. Debette S, Bauters C, Leys D, Lamblin N, Pasquier F, de Groote P. Prevalence and determinants of cognitive impairment in chronic heart failure patients. Congest Heart Fail. 2007;13:205–208. doi: 10.1111/j.1527-5299.2007.06612.x [ DOI ] [ PubMed ] [ Google Scholar ] 17. Wolters FJ, Segufa RA, Darweesh SKL, Bos D, Ikram MA, Sabayan B, Hofman A, Sedaghat S. Coronary heart disease, heart failure, and the risk of dementia: A systematic review and meta-analysis. Alzheimers Dement. 2018;14:1493–1504. doi: 10.1016/j.jalz.2018.01.007 [ DOI ] [ PubMed ] [ Google Scholar ] 18. Adelborg K, Horváth-Puhó E, Ording A, Pedersen L, Sørensen HT, Henderson VW. Heart failure and risk of dementia: a Danish nationwide population-based cohort study. Eur J Heart Fail. 2017;19:253–260. doi: 10.1002/ejhf.631 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 19. Manemann SM, Chamberlain AM, Bielinski SJ, Jiang R, Weston SA, Roger VL. Predicting Alzheimer’s Disease and Related Dementias in Heart Failure and Atrial Fibrillation. Am J Med. 2023;136:302–307. doi: 10.1016/j.amjmed.2022.11.010 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 20. Manemann SM, Knopman DS, St Sauver J, Bielinski SJ, Chamberlain AM, Weston SA, Jiang R, Roger VL. Alzheimer’s disease and related dementias and heart failure: A community study. J Am Geriatr Soc. 2022;70:1664–1672. doi: 10.1111/jgs.17752 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 21. Callahan CM, Arling G, Tu W, Rosenman MB, Counsell SR, Stump TE, Hendrie HC. Transitions in care for older adults with and without dementia. J Am Geriatr Soc. 2012;60:813–820. doi: 10.1111/j.1532-5415.2012.03905.x [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Rørth R, Clausen MF, Fosbøl EL, Mogensen UM, Kragholm K, Jhund PS, Petrie MC, Torp-Pedersen C, Gislason GH, McMurray JJV, et al. Initiation of domiciliary care and nursing home admission following first hospitalization for heart failure, stroke, chronic obstructive pulmonary disease or cancer. PLoS One. 2021;16:e0255364. doi: 10.1371/journal.pone.0255364 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 23. Allen LA, Hernandez AF, Peterson ED, Curtis LH, Dai D, Masoudi FA, Bhatt DL, Heidenreich PA, Fonarow GC. Discharge to a skilled nursing facility and subsequent clinical outcomes among older patients hospitalized for heart failure. Circ Heart Fail. 2011;4:293–300. doi: 10.1161/circheartfailure.110.959171 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 24. Greene SJ, O’Brien EC, Mentz RJ, Luo N, Hardy NC, Laskey WK, Heidenreich PA, Chang CL, Turner SJ, Yancy CW, et al. Home-Time After Discharge Among Patients Hospitalized With Heart Failure. J Am Coll Cardiol. 2018;71:2643–2652. doi: 10.1016/j.jacc.2018.03.517 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 25. Gupta A, Fonarow GC. The Hospital Readmissions Reduction Program: Evidence for Harm. JACC Heart Fail. 2018;6:607–609. doi: 10.1016/j.jchf.2018.02.012 [ DOI ] [ PubMed ] [ Google Scholar ] 26. Wadhera RK, Joynt Maddox KE, Kazi DS, Shen C, Yeh RW. Hospital revisits within 30 days after discharge for medical conditions targeted by the Hospital Readmissions Reduction Program in the United States: national retrospective analysis. Bmj. 2019;366:l4563. doi: 10.1136/bmj.l4563 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 27. Fried TR, Bradley EH, Towle VR, Allore H. Understanding the treatment preferences of seriously ill patients. N Engl J Med. 2002;346:1061–1066. doi: 10.1056/NEJMsa012528 [ DOI ] [ PubMed ] [ Google Scholar ] 28. Groff AC, Colla CH, Lee TH. Days Spent at Home - A Patient-Centered Goal and Outcome. N Engl J Med. 2016;375:1610–1612. doi: 10.1056/NEJMp1607206 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 29. Burke LG, Orav EJ, Zheng J, Jha AK. Healthy Days at home: A novel population-based outcome measure. Healthc (Amst). 2020;8:100378. doi: 10.1016/j.hjdsi.2019.100378 [ DOI ] [ PubMed ] [ Google Scholar ] 30. Lee H, Shi SM, Kim DH. Home Time as a Patient-Centered Outcome in Administrative Claims Data. J Am Geriatr Soc. 2019;67:347–351. doi: 10.1111/jgs.15705 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 31. Pandey A, Keshvani N, Vaughan-Sarrazin MS, Gao Y, Fonarow GC, Yancy C, Girotra S. Evaluation of Risk-Adjusted Home Time After Hospitalization for Heart Failure as a Potential Hospital Performance Metric. JAMA Cardiol. 2021;6:169–176. doi: 10.1001/jamacardio.2020.4928 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 32. Dalmau-Bueno A, García-Altés A, Amblàs J, Contel JC, Santaeugènia S. Determinants of the number of days people in the general population spent at home during end-of-life: Results from a population-based cohort analysis. PLoS One. 2021;16:e0253483. doi: 10.1371/journal.pone.0253483 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 33. Report to the Congress: promoting greater efficiency in Medicare. 2007. [ Google Scholar ] 34. Goodwin JS, Li S, Zhou J, Graham JE, Karmarkar A, Ottenbacher K. Comparison of methods to identify long term care nursing home residence with administrative data. BMC Health Serv Res. 2017;17:376. doi: 10.1186/s12913-017-2318-9 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 35. Fanaroff AC, Cyr D, Neely ML, Bakal J, White HD, Fox KAA, Armstrong PW, Lopes RD, Ohman EM, Roe MT. Days Alive and Out of Hospital: Exploring a Patient-Centered, Pragmatic Outcome in a Clinical Trial of Patients With Acute Coronary Syndromes. Circ Cardiovasc Qual Outcomes. 2018;11:e004755. doi: 10.1161/circoutcomes.118.004755 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 36. Fonarow GC, Liang L, Thomas L, Xian Y, Saver JL, Smith EE, Schwamm LH, Peterson ED, Hernandez AF, Duncan PW, et al. Assessment of Home-Time After Acute Ischemic Stroke in Medicare Beneficiaries. Stroke. 2016;47:836–842. doi: 10.1161/strokeaha.115.011599 [ DOI ] [ PubMed ] [ Google Scholar ] 37. Chronic Conditions. Chronic Conditions Data Warehouse. https://www2.ccwdata.org/condition-categories-chronic . 38. Babitsch B, Gohl D, von Lengerke T. Re-revisiting Andersen’s Behavioral Model of Health Services Use: a systematic review of studies from 1998–2011. Psychosoc Med. 2012;9:Doc11. doi: 10.3205/psm000089 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 39. Andersen R, Newman JF. Societal and individual determinants of medical care utilization in the United States. Milbank Mem Fund Q Health Soc. 1973;51:95–124. [ PubMed ] [ Google Scholar ] 40. Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, Saunders LD, Beck CA, Feasby TE, Ghali WA. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43:1130–1139. doi: 10.1097/01.mlr.0000182534.19832.83 [ DOI ] [ PubMed ] [ Google Scholar ] 41. Auriemma CL, Butt MI, Silvestri JA, Halpern SD, Courtright KR. Stakeholder Perspectives on Minimum Clinically Important Difference and Noninferiority Margin for Hospital-Free Days to Assess Interventions. JAMA Intern Med. 2023;183:739–742. doi: 10.1001/jamainternmed.2023.0918 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 42. Goh FQ, Kong WKF, Wong RCC, Chong YF, Chew NWS, Yeo TC, Sharma VK, Poh KK, Sia CH. Cognitive Impairment in Heart Failure-A Review. Biology (Basel). 2022;11. doi: 10.3390/biology11020179 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 43. Hugo J, Ganguli M. Dementia and cognitive impairment: epidemiology, diagnosis, and treatment. Clin Geriatr Med. 2014;30:421–442. doi: 10.1016/j.cger.2014.04.001 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 44. Hammond CA, Blades NJ, Chaudhry SI, Dodson JA, Longstreth WT Jr., Heckbert SR, Psaty BM, Arnold AM, Dublin S, Sitlani CM, et al. Long-Term Cognitive Decline After Newly Diagnosed Heart Failure: Longitudinal Analysis in the CHS (Cardiovascular Health Study). Circ Heart Fail. 2018;11:e004476. doi: 10.1161/circheartfailure.117.004476 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 45. Davis MR. ​Despite Pandemic, Percentage of Older Adults Who Want to Age in Place Stays Steady. https://www.aarp.org/home-family/your-home/info-2021/home-and-community-preferences-survey.html . 2021. 46. Quinn TJ, Dawson J, Lees JS, Chang TP, Walters MR, Lees KR. Time spent at home poststroke: “home-time” a meaningful and robust outcome measure for stroke trials. Stroke. 2008;39:231–233. doi: 10.1161/strokeaha.107.493320 [ DOI ] [ PubMed ] [ Google Scholar ] 47. Parekh A New quality measure designed by researchers quantifies time spent at home in good health. In: MedCityNews. 2020. [ Google Scholar ] 48. Coppa K, Kim EJ, Oppenheim MI, Bock KR, Conigliaro J, Hirsch JS. Examination of Post-discharge Follow-up Appointment Status and 30-Day Readmission. J Gen Intern Med. 2021;36:1214–1221. doi: 10.1007/s11606-020-06569-5 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 49. Murtaugh CM, Deb P, Zhu C, Peng TR, Barrón Y, Shah S, Moore SM, Bowles KH, Kalman J, Feldman PH, et al. Reducing Readmissions among Heart Failure Patients Discharged to Home Health Care: Effectiveness of Early and Intensive Nursing Services and Early Physician Follow-Up. Health Serv Res. 2017;52:1445–1472. doi: 10.1111/1475-6773.12537 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 50. Ferguson MT, Kusre S, Myles PS. Minimal clinically important difference in days at home up to 30 days after surgery. Anaesthesia. 2022;77:196–200. doi: 10.1111/anae.15623 [ DOI ] [ PubMed ] [ Google Scholar ] 51. Kamdar N, Syrjamaki J, Aikens JE, Mahmoudi E. Readmission Rates and Episode Costs for Alzheimer Disease and Related Dementias Across Hospitals in a Statewide Collaborative. JAMA Netw Open. 2023;6:e232109. doi: 10.1001/jamanetworkopen.2023.2109 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 52. Kosar CM, Mor V, Werner RM, Rahman M. Risk of Discharge to Lower-Quality Nursing Homes Among Hospitalized Older Adults With Alzheimer Disease and Related Dementias. JAMA Netw Open. 2023;6:e2255134. doi: 10.1001/jamanetworkopen.2022.55134 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 53. Resnick B Management of Heart Failure in Skilled Nursing Facilities: Why Does it Matter? In: Professional Heart Daily: American Heart Association; 2015. [ Google Scholar ] 54. Orr NM, Boxer RS, Dolansky MA, Allen LA, Forman DE. Skilled Nursing Facility Care for Patients With Heart Failure: Can We Make It “Heart Failure Ready?”. J Card Fail. 2016;22:1004–1014. doi: 10.1016/j.cardfail.2016.10.009 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 55. Kakutani N, Fukushima A, Kinugawa S, Yokota T, Oikawa T, Nishikawa M, Nakamura R, Tsukada T, Mori S, Yoshida I, et al. Progressive Mobilization Program for Patients With Acute Heart Failure Reduces Hospital Stay and Improves Clinical Outcome. Circ Rep. 2019;1:123–130. doi: 10.1253/circrep.CR-19-0004 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 56. Fleming LM, Zhao X, DeVore AD, Heidenreich PA, Yancy CW, Fonarow GC, Hernandez AF, Kociol RD. Early Ambulation Among Hospitalized Heart Failure Patients Is Associated With Reduced Length of Stay and 30-Day Readmissions. Circ Heart Fail. 2018;11:e004634. doi: 10.1161/circheartfailure.117.004634 [ DOI ] [ PubMed ] [ Google Scholar ] 57. Patel BK, Wolfe KS, Patel SB, Dugan KC, Esbrook CL, Pawlik AJ, Stulberg M, Kemple C, Teele M, Zeleny E, et al. Effect of early mobilisation on long-term cognitive impairment in critical illness in the USA: a randomised controlled trial. Lancet Respir Med. 2023;11:563–572. doi: 10.1016/s2213-2600(22)00489-1 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 58. Falvey JR, Burke RE, Malone D, Ridgeway KJ, McManus BM, Stevens-Lapsley JE. Role of Physical Therapists in Reducing Hospital Readmissions: Optimizing Outcomes for Older Adults During Care Transitions From Hospital to Community. Physical Therapy. 2016;96:1125–1134. doi: 10.2522/ptj.20150526 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 59. Simning A, Orth J, Wang J, Caprio TV, Li Y, Temkin-Greener H. Skilled Nursing Facility Patients Discharged to Home Health Agency Services Spend More Days at Home. Journal of the American Geriatrics Society. 2020;68:1573–1578. doi: 10.1111/jgs.16457 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 60. Simning A, Orth J, Temkin-Greener H, Li Y, Simons KV, Conwell Y. Skilled Nursing Facility-to-Home Trajectories for Older Adults With Mental Illness or Dementia. Am J Geriatr Psychiatry. 2022;30:223–234. doi: 10.1016/j.jagp.2021.06.013 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 61. Jones CD, Moss A, Sevick C, Roczen M, Sterling MR, Portz J, Lum HD, Yu A, Urban JA, Khazanie P. Factors Associated With Mortality and Hospice Use Among Medicare Beneficiaries With Heart Failure Who Received Home Health Services. J Card Fail. 2024;30:788–799. doi: 10.1016/j.cardfail.2023.11.019 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 62. Services CfMM. Guiding an Improved Dementia Experience (GUIDE) Model. https://www.cms.gov/priorities/innovation/innovation-models/guide . 2023. [ DOI ] [ PMC free article ] [ PubMed ] 63. Ramesh T, Kadakia K, Moura L. Transforming Value-Based Dementia Care—Implications for the GUIDE Model. JAMA Internal Medicine. 2024;184:237–239. doi: 10.1001/jamainternmed.2023.7669 [ DOI ] [ PubMed ] [ Google Scholar ] 64. Geng F, McGarry BE, Rosenthal MB, Zubizarreta JR, Resch SC, Grabowski DC. Preferences for Postacute Care at Home vs Facilities. JAMA Health Forum. 2024;5:e240678–e240678. doi: 10.1001/jamahealthforum.2024.0678 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 65. McCarthy EP, Chang CH, Tilton N, Kabeto MU, Langa KM, Bynum JPW. Validation of Claims Algorithms to Identify Alzheimer’s Disease and Related Dementias. J Gerontol A Biol Sci Med Sci. 2022;77:1261–1271. doi: 10.1093/gerona/glab373 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 66. Li J, Ha J, Hoffman G. Unaddressed functional difficulty and care support among White, Black, and Hispanic older adults in the last decade. Health Aff Sch. 2023;1:1–8. doi: 10.1093/haschl/qxad041 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 67. Sterling MR, Kern LM, Safford MM, Jones CD, Feldman PH, Fonarow GC, Sheng S, Matsouaka RA, DeVore AD, Lytle B, et al. Home Health Care Use and Post-Discharge Outcomes After Heart Failure Hospitalizations. JACC Heart Fail. 2020;8:1038–1049. doi: 10.1016/j.jchf.2020.06.009 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. 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