Abstract 3640: From Data to Action: Improving Knowledge Translation through Ontario's Stroke Report Cards
Bibliographic record
Abstract
Background: The Ontario Stroke Evaluation Program has been reporting on the quality of stroke care since 2005. This information has been used inconsistently by stakeholders outside the stroke system. Consultation with stakeholders revealed that a concise reporting tool was needed. In 2009, the Stroke Evaluation Quality Committee (SEQC) developed a one-page report card to communicate the performance of stroke care in Ontario regionally and provincially. Method: Through a series of internal reviews, and utilizing the Canadian Stroke Strategy 2008 Performance Measurement Manual, the SEQC selected 20 key performance indicators to be presented in the report card. The primary data sources for indicator calculation were the FY 2008/09 Ontario Stroke Audit and FY 2008/09 and 2009/10 Canadian Institute for Health Information acute and inpatient rehabilitation databases. Indicator benchmarks were calculated using the Achievable Benchmarks of Care methodology. Red, green and yellow colour bands were used to rate regional performance relative to the benchmark, red representing poor performance (below the fiftieth percentile), green indicating exemplary performance (within 5% of the benchmark), and yellow representing acceptable performance (at or above the fiftieth percentile but outside of 5% of the benchmark). Stroke directors distributed the report cards to their regional management teams. Feedback about the report card was collected through a focus group with the stroke directors, who provided their own opinions and shared feedback they had received from management teams. Thematic analysis was conducted on qualitative data. Results: Among the fourteen regions, eleven had 1 - 4 indicators exhibiting exemplary performance with minimal indicator overlap (4/11 shared the same indicator). Thematic analysis of focus group data revealed four main themes: 1) Process (strategy of dissemination), 2) Content (information and layout), 3) Utility (function) and 4) Results (management’s responses). Feedback indicated that the report cards were a valuable tool for planning and were helpful in facilitating communication between stroke directors and regional management teams. Stakeholders were satisfied with the content and process of the report cards as well as the potential they have for driving system change. Recommendations for future iterations of the report card, such as the timing of distribution, were also identified for process improvement purposes. Conclusions: The report card is a concise document that serves as a valuable stakeholder communication tool, allowing for consistent planning across the Ontario Stroke System (OSS). The report card and dissemination process has effectively engaged the Ontario stroke regions in dialogue relating to stroke system improvement.
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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 | 0.177 | 0.363 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".