LONG-TERM CARE QUALITY IN ONTARIO AND BRITISH COLUMBIA: EXAMINING THE ROLE OF CHARITABLE DONATIONS, FINANCIAL VULNERABILITY, AND FACILITY CHARACTERISTICS
Bibliographic record
Abstract
For-profit ownership of long-term care homes has long been contentious in Canada and abroad, with concerns that excessive cost-cutting may negatively impact the quality of care. These concerns re-emerged during the COVID-19 pandemic, during which for-profit ownership was associated with larger outbreaks and more deaths in Canada. Existing international research on long-term care quality has suggested that for-profit homes provided worse quality based on multiple measures such as risk-adjusted health outcomes, staffing levels, process indicators, and inspections infractions. One potential explanation is the cost-cutting behaviours of for-profit homes, as they have been reported to provide fewer hours of direct care and substitute cheaper forms of nursing care. In Canada, an additional explanation may have been that not-for-profit homes and public homes had additional revenues such as municipal funding and charitable donations that were not available to most for-profit homes. Despite the controversies, few studies in Canada have examined whether long-term care home ownership status is associated with differences in quality metrics. Only one study from Ontario was identified that used a composite measure of risk-adjusted quality indicators and reported that for-profit homes and not-for-profit homes performed better than municipal homes. This study used data from Ontario and British Columbia, provinces with different funding models, to examine quality based on two outcomes consistent with the literature: the Canadian Institute for Health Information’s (CIHI) publicly reported risk-adjusted long-term care quality indicators, and infractions identified during inspections. There were therefore two main objectives. First, the study examined whether financial vulnerability and charitable donations were associated with differences in quality between private not-for-profit homes, leveraging tax data from the Canadian Revenue Agency. Second, the study examined whether ownership status and other facility characteristics were associated with differences in quality. Results suggested that neither financial vulnerability nor charitable donations were associated with differences in quality. Findings related to ownership status were inconsistent. Private for-profit and private not-for-profit ownership was associated with better performance on the CIHI quality indicators but were also associated with more inspection infractions and complaints compared to public homes. Further research is needed to better elucidate the mechanisms for differences in quality, and to examine whether the differences in CIHI indicator performance reflected true differences in quality or limitations of risk-adjustment.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".