Journal of the American Geriatrics Society · 2026
Utilization Patterns Among Heterogeneous Subgroups of Homebound Older Adults: A Latent Class Analysis.
СтатьяНаблюдательное исследованиеПоддержка исследования: вне правительства СШАПоддержка NIH: внешняя программаНазвание и аннотация: Перевод в очереди
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Young J Lee, Pomeroy Mary L, Charankevich Hanna, Ornstein Katherine A, Kinosian Bruce P
Аннотация
BACKGROUND: Homebound older adults represent a high-risk, high-needs population characterized by significant clinical and sociodemographic heterogeneity. Little is known about how such heterogeneity shapes care needs and utilization patterns. We characterized utilization patterns among distinct subgroups of homebound older adults and examined associations between levels of outpatient care and emergency department (ED) utilization.
PARTICIPANTS AND SETTING: We used nationally representative data from the National Health and Aging Trends Study (NHATS) linked to Medicare Fee-For-Service (FFS) claims from 2011 to 2019 and 2021-2023 to examine trends among homebound older adults ages 70 or older.
METHODS: In this retrospective observational study, we characterized utilization patterns among distinct subgroups of homebound older adults identified using latent class analysis (LCA). We then used multivariable regression to examine associations between level of outpatient utilization and probability of both any ED visit and any potentially avoidable ED visit identified using Ambulatory Care Sensitive Conditions (ACSC). We adjusted for other indicators of ED use and access to care (i.e., self-reported health, rurality, and disease burden).
RESULTS: There was a total of 2202 person-year observations across 1343 unique homebound individuals. The LCA identified four subgroups of homebound older adults: functional independence; dementia; multimorbidity; and dementia plus multimorbidity. There were significant differences in levels of ambulatory and acute care utilization between subgroups. Regression analyses did not show evidence to support the conventional wisdom that inability to access ambulatory care leads to more avoidable ED visits among the homebound older adult population.
CONCLUSIONS: Heterogeneity among the homebound older adult population shapes care needs that in turn influence utilization patterns. Understanding these dynamics is crucial to targeting interventions like home-based primary care to the highest risk groups while tailoring care to individual needs.
PARTICIPANTS AND SETTING: We used nationally representative data from the National Health and Aging Trends Study (NHATS) linked to Medicare Fee-For-Service (FFS) claims from 2011 to 2019 and 2021-2023 to examine trends among homebound older adults ages 70 or older.
METHODS: In this retrospective observational study, we characterized utilization patterns among distinct subgroups of homebound older adults identified using latent class analysis (LCA). We then used multivariable regression to examine associations between level of outpatient utilization and probability of both any ED visit and any potentially avoidable ED visit identified using Ambulatory Care Sensitive Conditions (ACSC). We adjusted for other indicators of ED use and access to care (i.e., self-reported health, rurality, and disease burden).
RESULTS: There was a total of 2202 person-year observations across 1343 unique homebound individuals. The LCA identified four subgroups of homebound older adults: functional independence; dementia; multimorbidity; and dementia plus multimorbidity. There were significant differences in levels of ambulatory and acute care utilization between subgroups. Regression analyses did not show evidence to support the conventional wisdom that inability to access ambulatory care leads to more avoidable ED visits among the homebound older adult population.
CONCLUSIONS: Heterogeneity among the homebound older adult population shapes care needs that in turn influence utilization patterns. Understanding these dynamics is crucial to targeting interventions like home-based primary care to the highest risk groups while tailoring care to individual needs.