Inappropriate use of clinical practices in Canada: a systematic review
Bibliographic record
Abstract
BACKGROUND: Inappropriate health care leads to negative patient experiences, poor health outcomes and inefficient use of resources. We aimed to conduct a systematic review of inappropriately used clinical practices in Canada. METHODS: We searched multiple bibliometric databases and grey literature to identify inappropriately used clinical practices in Canada between 2007 and 2021. Two team members independently screened citations, extracted data and assessed methodological quality. Findings were synthesized in 2 categories: diagnostics and therapeutics. We reported ranges of proportions of inappropriate use for all practices. Medians and interquartile ranges (IQRs), based on the percentage of patients not receiving recommended practices (underuse) or receiving practices not recommended (overuse), were calculated. All statistics are at the study summary level. RESULTS: = 9). INTERPRETATION: We have provided a summary of inappropriately used clinical practices in Canadian health care systems. Our findings can be used to support health care professionals and quality agencies to improve patient care and safety in Canada.
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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 | 0.085 | 0.458 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.017 |
| Insufficient payload (model declined to judge) | 0.010 | 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; both teacher heads agree on what is shown here.
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".