How Older Adults Mix Home and Community Services—and Why Dementia May Not Change Their Quality of Life

For millions of older adults who want to age in their own homes rather than move to a nursing facility, home- and community-based services, or HCBS, are the backbone of daily life. These programs span a bewildering range of supports: home healthcare visits, personal care assistance with bathing and dressing, homemaker services, non-medical transportation, adult day care, case management, and durable medical equipment such as walkers and hospital beds. Because the mix of services varies so widely from person to person, researchers have long struggled with a basic question: when it comes to judging how well these programs work, are we even comparing like with like? A new study published in BMC Geriatrics by Eric Jutkowitz of the University of Minnesota School of Public Health and colleagues tackles that question with an unusually direct approach, and its answer carries practical weight for how states evaluate and pay for long-term care.

The research team started from a simple observation. HCBS is not a single intervention but a bundle of distinct services, and older adults combine them in very different ways depending on their health, finances, and living situations. Rather than treating all HCBS consumers as one homogeneous group, the investigators used a statistical technique called hierarchical clustering to sort them into natural groupings based on their actual patterns of service use. Hierarchical clustering works by repeatedly merging individuals or groups whose service-use profiles are most similar, building a tree-like structure that reveals how many distinct consumer types genuinely exist in the data. This method, common in genomics and market research, is less familiar in health services research, which makes its application here notable.

The study population consisted of 775 Medicaid HCBS consumers in Minnesota aged 65 and older, drawn from data collected in 2017 and 2018. The researchers linked administrative claims data from the Minnesota Department of Human Services with responses from the National Core Indicators Adult Consumer Survey, a standardized instrument that asks service recipients directly about their experiences. This linkage is what gives the study its power: instead of relying on provider reports or administrative proxies, the quality-of-life measure comes from the consumers themselves, including those living with dementia.

Quality of life was measured using a validated index that captures three domains: care experiences, security, and autonomy. Care experiences reflect how people feel about the help they receive; security concerns safety and stability in daily life; and autonomy captures the ability to make choices and maintain independence. Together, these dimensions form a composite score that can be compared across individuals and groups. The team then used linear regression to test two things: whether mean quality-of-life scores differed between the consumer clusters, and whether, within each cluster, scores differed between people with dementia and people without it.

The clustering analysis identified four distinct groups of HCBS consumers, defined by different combinations of the seven service types tracked in the claims data: home healthcare, non-medical transportation, personal care assistance, case management, adult day care, durable medical equipment, and homemaker services. The clusters were not interchangeable. They differed in their racial and ethnic composition, in the proportion of members living with dementia, and in their levels of functional dependence—the degree to which people needed hands-on help with everyday activities. In other words, the statistical method surfaced real, socially meaningful segments of the HCBS population, not arbitrary mathematical artifacts.

Then came the finding that gives the study its punch. When the researchers compared mean quality-of-life scores across the four clusters, the differences were essentially nil. The regression coefficients ranged between 0.00 and 0.02 percentage points, and none approached statistical significance. Within each cluster, the comparison between consumers with dementia and those without told the same story: coefficient estimates between −0.01 and 0.04 percentage points, again with no significant differences. For a field that often assumes dementia fundamentally alters how people experience and evaluate their care, this null result is striking.

The authors draw a practical conclusion from these numbers: consumer-reported quality of life may serve as a valid quality indicator uniformly across all HCBS, regardless of whether a recipient has a dementia diagnosis. That matters because states increasingly use quality measures to manage Medicaid long-term care programs, set payment rates, and hold providers accountable. If quality-of-life scores had varied wildly between service-use patterns or between diagnostic groups, policymakers would need to interpret scores differently for different populations—a statistical headache that invites unfair comparisons. The Minnesota data suggest that a single yardstick can be applied across the board.

The findings also carry a subtler message about equity. Because the clusters differed in racial and ethnic composition and in dementia prevalence, one might have expected systematic gaps in how well the service system serves different groups. The absence of quality-of-life differences between clusters offers cautious reassurance that, at least on this consumer-reported dimension, the HCBS system in Minnesota was delivering comparable perceived value across very different client profiles. The authors frame this as evidence that service providers may be able to meet the unique needs of diverse client bases, though the cross-sectional design means the study cannot prove that services caused these outcomes—only that, at a single point in time, self-reported well-being looked similar across groups.

Several caveats deserve attention. The study covers a single state and a single program era, so generalizing to other Medicaid systems requires care. The data come from 2017 and 2018, before the disruptions of the COVID-19 pandemic reshaped home-based care delivery. And clustering, while powerful, depends on the service categories recorded in claims data; unmeasured supports—informal family caregiving above all—could shape quality of life in ways the analysis cannot capture. The research was supported by the National Institute on Aging under award numbers RF1AG069771 and R01AG069771, and the authors note that the sponsor had no role in the design or interpretation of the study.

Even with those limits, the study lands at a moment when the demographic math is unforgiving. Populations are aging rapidly, nursing home costs continue to climb, and states are under pressure to expand home-based alternatives. If consumer-reported quality of life proves to be a stable, comparable metric across the full spectrum of HCBS users—with and without dementia—then states gain a practical tool for monitoring a fragmented system with one consistent instrument. The next step, which the Minnesota team’s methodology makes feasible, is to track these clusters over time and test whether shifts in service mix actually move the needle on the well-being that older adults themselves report. For now, the message is quietly radical: in this large Medicaid sample, what mattered least was which services you used or whether you had dementia—what the system delivered, by its recipients’ own account, was a broadly similar quality of life.

Subject of Research: Patterns of home- and community-based service use and quality of life among older adults with and without dementia

Article Title: Clusters of home- and community- based service use and association with quality of life in older adults with and without dementia

Article References: Jutkowitz, E., Parikh, R. R., Wolf, J. M., Duan, Y., Langworthy, B. W., & Shippee, T. P. (2026). Clusters of home- and community- based service use and association with quality of life in older adults with and without dementia. BMC Geriatrics. https://doi.org/10.1186/s12877-026-08442-2

Image Credits: AI Generated

DOI: 10.1186/s12877-026-08442-2

Keywords: home- and community-based services, dementia, quality of life, Medicaid, older adults, hierarchical clustering, long-term care, geriatrics, health services research, Minnesota, personal care assistance, aging population