Care Outcomes in Long-Term Care Facilities in British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVES: This study investigated whether for-profit (FP) versus not-for-profit (NP) ownership of long-term care facilities resulted in a difference in hospital admission and mortality rates among facility residents in British Columbia, Canada. RESEARCH DESIGN: This retrospective cohort study used administrative data on all residents of British Columbia long-term care facilities between April 1, 1996, and August 1, 1999 (n = 43,065). Hospitalizations were examined for 6 diagnoses (falls, pneumonia, anemia, dehydration, urinary tract infection, and decubitus ulcers and/or gangrene), which are considered to be reflective of facility quality of care. In addition to FP versus NP status, facilities were divided into ownership subgroups to investigate outcomes by differences in governance and operational structures. RESULTS: We found that, overall, FP facilities demonstrated higher adjusted hospitalization rates for pneumonia, anemia, and dehydration and no difference for falls, urinary tract infections, or DCU/gangrene. FP facilities demonstrated higher adjusted hospitalization rates compared with NP facilities attached to a hospital, amalgamated to a regional health authority, or that were multisite. This effect was not present when comparing FP facilities to NP single-site facilities. There was no difference in mortality rates in FP versus NP facilities. CONCLUSIONS: The higher adjusted hospitalization rates in FP versus NP facilities is consistent with previous research from U.S. authors. However, the superior performance by the NP sector is driven by NP-owned facilities connected to a hospital or health authority, or that had more than one site of operation.
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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 | 0.003 |
| 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 | 0.000 |
| 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".