Study Protocol and Baseline Comparisons for a Pan-Canadian Initiative to Reduce Inappropriate Use of Antipsychotics in Long-Term Care Homes
Bibliographic record
Abstract
Antipsychotic use in the absence of symptoms or diagnoses related to psychosis is generally regarded as an inappropriate approach to care of older adults in nursing homes. The Canadian Foundation for Healthcare Improvement (CFHI) launched a pan-Canadian intervention study to reduce antipsychotic use in long-term care based on promising pilot study results from the Winnipeg Regional Health Authority (WRHA). Data from the Continuing Care Report System (CCRS) managed by the Canadian Institute for Health Information (CIHI) were used to compare the characteristics of residents in intervention homes with control homes not in the study. The sample was comprised of 5,434 residents in 49 intervention homes compared with 123,781 residents in 1,193 control homes. Resident-level comparisons included demographic, diagnostic, and clinical indicators. Facility-level comparisons included nine risk-adjusted quality indicators. The main differences of note were in geographic representation (Ontario homes were underrepresented), access to rehabilitation, and discharge patterns (both of which were related to Ontario practice patterns). There were few substantial differences in quality indicator performance between homes by study participation prior to the onset of the intervention. The study protocol used in this pan-Canadian intervention was based on a successful, small-scale pilot undertaken in one province. Sites that participated in the intervention did not differ in substantively meaningful ways from control homes. Therefore, subsequent study findings after the intervention are unlikely to be attributable to differences between homes that existed prior to the study onset.
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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 | 0.032 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.052 | 0.006 |
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".