Home and Community-Based Service Utilization Patterns for Seniors with Alzheimer's Disease and Related Dementias
Bibliographic record
Abstract
Background: Half a million Canadians are living with Alzheimer’s disease and related dementias. Approximately half these individuals live in the community, supported by informal caregivers. In this population, utilization of formal services is low and patterns of utilization are not well understood. Previous studies examining predictors of service use have examined services in isolation however, often multiple services are utilized, with little coordination between services. Purpose: The purpose of this study was to provide a better understanding of the community-based services utilized concurrently by seniors with dementia and their caregivers. Methods: Administrative data were utilized to conduct a secondary analysis. Using latent class analysis, cases were categorized into patterns of home and community-based health and support service use. Multinomial logistic regression was employed to identify predictors of identified service use patterns. Results: A broad range of services were utilized by seniors with dementia in this sample. Services supporting patients’ functional needs were utilized most frequently, while services addressing patients’ medical needs, rehabilitation and caregiver relief were used less often. Utilization of all services, except nursing and occupational therapy, varied by level of cognitive impairment. Seven unique patterns of home and community-based service use were identified. Key patient and caregiver characteristics impacting service use patterns included living arrangement, functional impairment, location of care, cognitive impairment, age, continence, and caregiver relationship. Conclusions: The majority of community-based seniors with dementia did not access formal services. For those who did access formal services, availability of informal caregivers, living arrangement, caregiver relationship and location of care impacted the pattern of service use. A proactive approach to supporting caregivers and reducing the impact of functional limitations is recommended. Further research is needed to understand caregivers’ decision-making processes affecting service utilization and to assess the impact of patterns of service utilization on both patient and caregiver outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".