Are chronically ill patients high users of homecare services in Canada?
Bibliographic record
Abstract
OBJECTIVES: Chronically ill patients often need healthcare and supportive services, with formal homecare services an important source of community-based assistance. Although people diagnosed with 1 or more chronic diseases are thought to be the most common homecare clients, and perhaps the highest users of homecare services, few studies have analyzed homecare services utilization by specific clients. A study was done to determine if a relationship exists between chronic illness and homecare services utilization. STUDY DESIGN: Descriptive-comparative, secondary analysis of population homecare data. METHODS: Three years (2003-2004, 2004-2005, and 2005-2006) of complete homecare client and services utilization data for 1 Canadian province were obtained and tested using 5 definitions of chronic illness to determine which clients among all 149,378 were high users in terms of annual homecare hours and service visits or episodes. RESULTS: Two definitions revealed clients with a disproportionately large share of homecare hours and service episodes: a) clients classified by homecare case managers as "long-term" and b) clients with service spans of ≥90 days. Definitions involving medical diagnoses and International Classification of Diseases, Ninth Revision, Clinical Modification codes or chapters did not reveal high users. Age and gender also did not predict services utilization. CONCLUSIONS: The comprehensive pre-service assessment completed by homecare case managers was the most successful at distinguishing people with substantial homecare service needs-people who could then be described as chronically ill. This assessment should be studied to develop a standardized minimum data tool for consistent and fair assessments.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".