The Quality in Acute Stroke Care (QASC) global scale-up using a cascading facilitation framework: A qualitative process evaluation
Bibliographic record
Abstract
Abstract Background Variation in stroke care among hospitals is problematic. The Quality in Acute Stroke (QASC) Australia trial demonstrated reductions in death and disability through supported implementation of nurse-led, evidence-based protocols to manage fever, hyperglycaemia (sugar) and swallowing (FeSS Protocols) following stroke. We conducted a pre-test/post-test study to evaluate the effect of supported implementation on FeSS Protocol uptake into acute stroke wards in 64 hospitals in 17 European countries. Implementation across countries was underpinned by a cascading facilitation framework of multi-stakeholder’s support involving academic partners and a not-for-profit health care initiative. The aim of this a priori qualitative process evaluation was to identify factors that influenced the implementation of the international up-scale of the FeSS Protocols using a cascading facilitation framework. Methods The sampling frame for interviews was: 1) Executives/Steering Committee members from academic and industry partners (from the Angels Initiative, a not-for-profit arm of industry) some of whom comprised the senior project team, 2) Angel Team leaders (managers of Angel Consultants), 3) Angel Consultants (responsible for assisting facilitation of FeSS Protocols into multiple hospitals) and 4) Country Co-ordinators (senior stroke nurses with country and hospital-level responsibilities for facilitating the introduction of the FeSS Protocols). A semi-structured interview elicited participant views on factors influencing engagement, preparation for FeSS Protocol upscale and implementation. Interviews were recorded, transcribed verbatim and analysed inductively within NVivo. Results Individual (n=13) and three group interviews (3 participants in each group) were undertaken. Three main themes were identified with sub-themes: readiness for change; roles and relationships and managing multiple changes. These themes illustrate the factors that enabled multi-country FeSS Protocol scale-up through a cascading facilitation model based on a collaboration between evidence producers (academics), knowledge brokers (not-for-profit arm of industry), and evidence adopters (stroke clinicians). Conclusion A cascading facilitation model involving academic, clinical and industry partners overcame multiple challenges involved in international evidence translation. Capacity to manage, negotiate and adapt to multi-level changes, a shared goal of optimal stroke care and strategic engagement of different stakeholders supported adoption of nurse-initiated stroke protocols within Europe. This model has promise for other large-scale evidence translation programs.
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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 | 0.134 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".