A profile of older community-dwelling home care clients with heart failure in Ontario
Bibliographic record
Abstract
INTRODUCTION: The aging of the Canadian population is associated with a rising burden of heart failure (HF), a condition associated with significant morbidity, mortality and health service use. METHODS: We used data from the Ontario Resident Assessment Instrument-Home Care database for all long-stay home care clients aged 65 years or older to (1) describe the demographic and clinical characteristics of home care clients with HF and (2) examine service use among home care clients with HF to promote management at home with appropriate services. RESULTS: Compared with other home care clients, HF clients exhibit more health instability, take more medications, experience more comorbid conditions and receive significantly more nursing, homemaking and meal services. They are hospitalized more frequently, have significantly more emergency department visits and use more emergent care. DISCUSSION: HF clients are a more complex group than home care clients in general. Patient self-care must be tailored to the clinical characteristics, patterns of service use and barriers to self-care of the client. This is particularly true for older, frail and medically complex HF patients, many of whom require home care services. This work provides a background upon which to base initiatives to help these higher-needs clients manage their HF at home with appropriate support and services.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".