Developing a rapid-response program for health system decision-makers in Canada: findings from an issue brief and stakeholder dialogue
Bibliographic record
Abstract
BACKGROUND: There is currently no mechanism in place outside of government to provide rapid syntheses of the best available research evidence about problems, options and/or implementation considerations related to a specific health system challenge that Canadian health system decision-makers need to address in a timely manner. A 'rapid-response' program could address this gap by providing access to optimally packaged, relevant and high-quality research evidence over short periods of time (i.e. days or weeks). METHODS: We prepared an issue brief that describes the best available research evidence related to the problem, three broad features of a program that addresses the problem and implementation considerations. We identified systematic reviews by searching for organization-targeted implementation strategies in Health Systems Evidence ( www.healthsystemsevidence.org ) and drew on an existing analytical framework for how knowledge-brokering organizations can organize themselves to operationalize the program features. The issue brief was then used to inform a half-day stakeholder dialogue about whether and how to develop a rapid-response program for health system decision-makers in Canada. We thematically synthesized the deliberations. RESULTS: We found very few relevant systematic reviews but used frameworks and examples from existing programs to 1) outline key considerations for organizing a rapid-response program,, 2) determine what can be done in timelines ranging from 3 to 10 and 30 business days, and 3) define success and measure it. The 11 dialogue participants from across Canada largely agreed with the content presented in the brief, but noted two key challenges to consider: securing stable, long-term funding and finding a way to effectively and equitably manage the expected demand. Recommendations and suggestions for next steps from dialogue participants included taking an 'organic' approach to developing a pan-Canadian network and including jurisdictional scans as a type of product to deliver through the program (rather than only syntheses of research evidence). CONCLUSIONS: Dialogue participants clearly signalled that there is an appetite for a rapid-response program for health system decision-makers in Canada. To 'organically' build such a program, we are currently engaging in efforts to build partnerships and secure funding to support the creation of a pan-Canadian network for conducting rapid syntheses for health system decision-makers in Canada.
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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 | 0.215 | 0.357 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.019 |
| Science and technology studies | 0.030 | 0.011 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.006 | 0.016 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier 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".