Abstract T P284: Trends in Ontario’s Stroke Report Cards
Bibliographic record
Abstract
Background: In 2011, the Ontario Stroke Evaluation and Quality Committee created Ontario’s Stroke Report Card, consisting of twenty indicators with potential to influence system performance and flow of stroke patients across the care continuum. The provincial report card and 14 regional report cards serve as a valuable stakeholder tool that allows for consistent planning across the province. Purpose: To evaluate stroke system performance at the provincial and regional level by comparing recent performance to previous three-year performance. Methods: Indicator performance was analyzed at the LHIN and provincial levels for 19 of 20 indicators with available data. Statistical significance was determined by comparing the most recent year’s performance to the combined average of the previous three years performance. A chi-square test, Wilcoxon rank-sum test, and Poisson and logistic regressions were used where appropriate. Eight indicators used FY2004/05, FY2008/09, FY2010/11 and FY2012/13 Ontario Stroke Audit of acute care facilities data and eleven used FY2009/10-FY2012/13 Canadian Institute for Health Information administrative databases and one used the Ontario Home Care Database, FY2008/09-FY2012/13. Results: In Ontario, 15 of 19 indicators showed statistically significant improvement from the previous 3 years. Only one indicator showed a statistically significant decline and the remaining three indicators improved but were non-significant (p > 0.05). Among the regional report cards, the number of indicators with statistical significant improvement ranged from 3-10 and 0-2 with statistical significant decline. Conclusion: The stroke report cards reflect steady improvement in stroke prevention, acute management and rehabilitation in Ontario. These improvements are in the absence of financial incentives such as pay for performance suggesting there is great capacity for the health system to improve using targeted performance reports.
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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".