Journal of the American Geriatrics Society最新文献

Background: Whether cognitive and functional recovery in skilled nursing facilities (SNF) following hospitalization differs by delirium and Alzheimer's disease related dementias (ADRD) has not been examined.

Objective: To compare change in cognition and function among short-stay SNF patients with delirium, ADRD, or both.

Design: Retrospective cohort study using claims data from 2011 to 2013.

Setting: Centers for Medicare and Medicaid certified SNFs.

Participants: A total of 740,838 older adults newly admitted to a short-stay SNF without prevalent ADRD who had at least two assessments of cognition and function.

Measurements: Incident delirium was measured by the Minimum Data Set (MDS) Confusion Assessment Method and ICD-9 codes, and incident ADRD by ICD-9 codes and MDS diagnoses. Cognitive improvement was a better or maximum score on the MDS Brief Interview for Mental Status, and functional recovery was a better or maximum score on the MDS Activities of Daily Living Scale.

Results: Within 30 days of SNF admission, the rate of cognitive improvement in patients with both delirium/ADRD was half that of patients with neither delirium/ADRD (HR = 0.45, 95% CI:0.43, 0.46). The ADRD-only and delirium-only groups also were 43% less likely to have improved cognition or function compared to those with neither delirium/ADRD (HR = 0.57, 95% CI:0.56, 0.58 and HR = 0.57, 95% CI:0.55, 0.60, respectively). Functional improvement was less likely in patients with both delirium/ADRD, as well (HR = 0.85, 95% CI:0.83, 0.87). The ADRD only and delirium only groups were also less likely to improve in function (HR = 0.93, 95% CI:0.92, 0.94 and HR = 0.92, 95% CI:0.90, 0.93, respectively) compared to those with neither delirium/ADRD.

Conclusions: Among older adults without dementia admitted to SNF for post-acute care following hospitalization, a positive screen for delirium and a new diagnosis of ADRD, within 7 days of SNF admission, were both significantly associated with worse cognitive and functional recovery. Patients with both delirium and new ADRD had the worst cognitive and functional recovery.

Understanding patients' degree of frailty is crucial for tailoring clinical care for older adults based on their physiologic reserve and health needs ("frailty-guided clinical care"). Two prerequisites for frailty-guided clinical care are: (1) access to frailty information at the point of care and (2) evidence to inform decisions based on frailty information. Recent advancements include web-based frailty assessment tools and their electronic health records integration for time-efficient, standardized assessments in clinical practice. Additionally, database frailty scores from administrative claims and electronic health records data enable scalable assessments and evaluation of the effectiveness and safety of medical interventions across different frailty levels using real-world data. Given limited evidence from clinical trials, real-world database studies can complement trial results and help treatment decisions for individuals with frailty. This article, based on the Thomas and Catherine Yoshikawa Award lecture I gave at the American Geriatrics Society Annual Meeting in Long Beach, California, on May 5, 2023, outlines our group's contributions: (1) developing and integrating a frailty index calculator (Senior Health Calculator) into the electronic health records at an academic medical center; (2) developing a claims-based frailty index for Medicare claims; (3) applying this index to evaluate the effect of medical interventions for patients with and without frailty; and (4) efforts to disseminate frailty assessment tools through the launch of the eFrailty website and the forthcoming addition of the claims-based frailty index to the Centers for Medicare and Medicaid Services Chronic Conditions Data Warehouse. This article concludes with future directions for frailty-guided clinical care.

Introduction: Racial and ethnic disparities in potentially inappropriate medication (PIM) use among older adults with dementia are unclear.

Methods: Data were drawn from the baseline visits of participants who were ≥60 years old and diagnosed with dementia in the National Alzheimer's Coordinating Center Uniform Data Set (NACCUDS) recruited from National Institute on Aging (NIA)-funded Alzheimer's Disease Research Centers (ADCs) throughout the United States. PIM utilization was evaluated using the 2019 American Geriatrics Society Beers Criteria for PIM Use in Older Adults. We estimated the association between race and ethnicity and the following outcomes and estimation models: (1) any PIM use, any PIM in each drug class, and any PIM best avoided in dementia patients using logistic regression models, (2) total number of medications, total number of PIMs, and anticholinergic burden scale (ACBS) using Poisson or negative binomial regression models, and (3) proportion of total medications that were PIMs using generalized linear models (GLM).

Results: Compared to White participants, Black, Hispanic, and Asian participants reported taking fewer total medications (incidence rate ratio [IRR] ± standard error[SE] = 0.903 ± 0.017, 0.875 ± 0.021, and 0.912 ± 0.041, respectively, all p < 0.01). Asian participants were less likely to be exposed to any PIM (odds ratio [OR] ± SE = 0.619 ± 0.118, p < 0.05). Compared to White participants, Black participants were less likely to be exposed to benzodiazepine (OR ± SE = 0.609 ± 0.094, p < 0.01) and antidepressant (OR ± SE = 0.416 ± 0.103, p < 0.001) PIMs, but greater antipsychotic (OR ± SE = 1.496 ± 0.204, p < 0.01), cardiovascular (OR ± SE = 2.193 ± 0.255, p < 0.001), and skeletal muscle relaxant (OR ± SE = 2.977 ± 0.860, p < 0.001) PIMs. Hispanic participants were exposed to greater skeletal muscle relaxant PIMs and had lower anticholinergic burden. Asian participants were exposed to fewer benzodiazepine PIMs.

Discussion: Significant racial and ethnic disparities in exposure to PIMs and PIMs by medication category in dementia research participants who have access to dementia experts found in the study suggest that disparities may be wider in the larger community.

Background: Residents of assisted living facilities (ALF) transfer to a nursing home when they require a higher level of care, but limited research has examined risk factors for transfer to a nursing home. The aims of this study were to identify (1) baseline factors associated with transfer to a nursing home and (2) time-varying factors associated with transfer to a nursing home over 8 years, using a national dataset from the National Health Aging Trends Study (NHATS).

Methods: NHATS participants were included in this study if they: (1) resided in ALF from Round 1 (2011) through Round 8 (2018); (2) completed the sample person (SP) interview at baseline; (3) were admitted to ALF at age 65 years or older. We conducted Cox proportional hazards regression to examine candidate predictors (difficulty with basic activities of daily living (ADL), chronic conditions, hospitalization, sleep disturbances, mental health, physical performance, self-reported health, participation in social and physical activity, and sociodemographic) associated with transfer to a nursing home. Employing backward elimination, we built parsimonious final models for analysis.

Results: The analytic sample included 970 participants of whom 143 transferred to nursing homes over 8 years. Those who had a better physical performance at baseline (HR = 0.83, 95% CI = 0.79-0.88) and were college educated (HR = 0.58, 95% CI = 0.36-0.92) demonstrated a significantly lower risk for transfer to a nursing home over 8 years. Residents who maintained physical activity (HR = 0.56, 95% CI = 0.37-0.86), better physical performance (HR = 0.87, 95% CI = 0.80-0.94), and difficulty with fewer basic ADLs (HR = 1.13, 95% CI = 1.02-1.26) were at lower risk for transfer to a nursing home over 8 years.

Conclusions: Our findings can be used to identify older adults in ALFs at risk of transfer to a nursing home. Strategies to promote physical function and physical activity could avoid/delay the need to transfer. Helping older residents to age in place will have important health and economic benefits.

Background: Hospital at home (HaH) delivers hospital-level care to acutely ill patients at home as a substitute for brick-and-mortar hospital care. The clinician and program characteristics of HaH programs worldwide are relatively unknown. We sought to describe the world's HaH clinicians and their programs' characteristics.

Methods: We analyzed a survey administered to all attendees of the 2023 World Hospital at Home Congress. Clinician characteristics included age, years worked in HaH, profession, burnout, and experience. Program characteristics included location, daily census, types of care delivery, and clinical capabilities.

Results: Of 670 attendees, about 305 were clinicians and 129 responded (42% response rate for clinicians). The majority of clinicians were 30-49 years old (65.1%), new to the field (70.5% worked less than 10 years), and part-time (18% dedicated >74% effort to HaH). Clinicians reported overall satisfaction with their job and low burnout. About half of programs were in Europe (52.1%), newly operational (44.7% less than 5 years), mostly operated in urban environments (87.2%), and mostly had a daily census of less than 25 patients (62.8%). Most programs operated 7-days per week (88.3%), performed intermittent or continuous remote monitoring (81.4%), used video communication (63.8%), and had some advanced capabilities such as in-home imaging (47.9%) and advanced procedures (23.4%). Visit frequencies to the patient's home were variable: most programs had physicians visit the home, nearly all had nurses visit the home, and fewer performed virtual visits.

Conclusions: HaH clinicians and programs have significant similarities but also a fair number of divergent practices, much like brick-and-mortar hospital care. Further standardization of the care model will help to unify the field across the globe.