A comparison of home care quality indicator rates in two Canadian provinces
Bibliographic record
Abstract
BACKGROUND: Home care is becoming an increasingly vital sector in the health care system yet very little is known about the characteristics of home care clients and the quality of care provided in Canada. We describe these clients and evaluate home care quality indicator rates in two regions. METHODS: A cross-sectional analysis of assessments completed for older (age 65+) home care clients in both Ontario (n = 102,504) and the Winnipeg Regional Health Authority (n = 9,250) of Manitoba, using the Resident Assessment Instrument for Home Care (RAI-HC). This assessment has been mandated for use in these two regions and the indicators are generated directly from items within the assessment. The indicators are expressed as rates of negative outcomes (e.g., falls, dehydration). Client-level risk adjustment of the indicator rates was used to enable fair comparisons between the regions. RESULTS: Clients had a mean age of 83.2 years, the majority were female (68.6%) and the regions were very similar on these demographic characteristics. Nearly all clients (92.4%) required full assistance with instrumental activities of daily living (IADLs), approximately 35% had activities of daily living (ADL) impairments, and nearly 50% had some degree of cognitive impairment, which was higher among clients in Ontario (48.8% vs. 37.0%). The highest quality indicator rates were related to clients who had ADL/rehabilitation potential but were not receiving therapy (range: 66.8%-91.6%) and the rate of cognitive decline (65.4%-76.3%). Ontario clients had higher unadjusted rates across 18 of the 22 indicators and the unadjusted differences between the two provinces ranged from 0.6% to 28.4%. For 13 of the 19 indicators that have risk adjustment, after applying the risk adjustment methodology, the difference between the adjusted rates in the two regions was reduced. CONCLUSIONS: Home care clients in these two regions are experiencing a significant level of functional and cognitive impairment, health instability and daily pain. The quality indicators provide some important insight into variations between the two regions and can serve as an important decision-support tool for flagging potential quality issues and isolating areas for improvement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".