Abstract TP355: Supporting and Sustaining Systems Change Through the Development of Common Standards of Stroke Care
Bibliographic record
Abstract
Background/Issues: The Stroke Flow initiative is a system-wide redesign of stroke services to enhance access to stroke best practices. Specifically, its focus is to ensure access to acute stroke units and timely and appropriate rehabilitation. To support this work, the Toronto Stroke Networks (TSNs) held forums with stroke nursing leaders (SNLs) within the Greater Toronto Area (GTA). Purpose: Through these forums, the purpose of this work was to develop evidenced-informed common standards of stroke care across the continuum and set priorities for implementation within the GTA. Methods: Six forums (from December 2011 to June 2012) were held for 43 SNLs from 16 acute and rehabilitation hospitals within the GTA. Using an appreciative inquiry approach, meetings focused on: 1) identifying common core elements (CCEs) for stroke care; 2) validating CCEs through consultation with interprofessional stroke teams; 3) forming consensus on CCEs; 4) identifying organizational priorities for implementation planning using thematic analysis; 5) integrating CCEs into existing processes of care; and 6) sustaining this work through the establishment of a stroke community of practice. Results: Through collaborative planning, CCEs were developed and reflect current and emerging best practices. Preliminary results from thematic analysis identified priorities related to: transitions of care, improved team communication processes, patient/family education, and integration of outcome measures across the care continuum. Conclusions: Common core elements of stroke care were collectively developed by the TSNs, stroke nursing leaders, and interprofessional teams to promote a standardization of stroke care that integrates best practices and identifies areas for improvement. Impact of this work has led to the development of CCE documents to support the integration and standardization of stroke care and the establishment of a stroke nursing community of practice. Final thematic analysis is currently underway to further identify priorities for implementation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".