Chartbook: Shining a Light on the Quality of Healthcare in Canada
Bibliographic record
Abstract
This paper provides a reflection on the findings of Canada's first-ever chartbook on the quality of healthcare in Canada. Quality of Healthcare in Canada: A Chartbook was published in 2010 by the Canadian Health Services Research Foundation in partnership with the Canadian Institute for Health Information and the Canadian Patient Safety Institute, and with support from Statistics Canada. This paper, by the chartbook authors (Sutherland and Leatherman) and colleagues (Law, Verma and Petersen), presents selected key findings and lessons from the chartbook and aims to serve as a catalyst for ideas and discussion in the papers that follow. The chartbook identified a lack of common language and indicators on quality across Canada's provinces and territories, underscoring the need to create and coordinate core measures. The Canadian chartbook and this issue of Healthcare Papers provide an update on the existing quality measures and the state of healthcare quality in Canada, and create the opportunity for jurisdictions to learn from one another and to contemplate the steps required to improve quality across the country.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.028 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.021 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".