INNOVATIVE PROGRAMS CREATING OPPORTUNITIES FOR ONGOING STROKE RECOVERY IN THE COMMUNITY
Bibliographic record
Abstract
BackgroundOngoing rehabilitation post-stroke leads to further functional gains and prevents decline. Unfortunately accessing rehabilitation in the community can be challenging due in part to limited discharge destinations from outpatient programs. Adult Day Programs (ADPu2019s) are an underutilized component of stroke recovery that can support rehabilitation by providing opportunities to maximize function and socialization beyond the formal outpatient journey. MethodsBased on the successful OneCare Stroke ADP model in Clinton Ontario, the Southwestern Ontario Stroke Network (SWOSN) collaborated with partners and received funding from the South West Local Health Integration Network (SW LHIN) to spread Stroke ADPs across the region. Work included developing an implementation strategy, a site analysis based on demand modeling, and the creation of referral pathways and processes. The programs partnered with existing Community Stroke Rehabilitation Teams (CSRT) to enhance transitions, and support ADPs with best practices, standardization and evaluation.ResultsThis work led to the creation of 4 Stroke ADPs, improving geographical access and improved outcomes for patients by providing rehabilitation following formal outpatient services. Congregating stroke survivors on a specific day, allows for social integration, opportunities for peer/caregiver support, a focused opportunity for secondary stroke education, and a modified/specialized group exercise program catered to stroke survivor needs.ConclusionsWith limited funding, stakeholder partnerships led to the development of new programs that improve access, equity and outcomes, while providing an exit strategy from formal rehabilitation. Stroke ADP days support system flow, provide caregiver relief and enable stroke survivors to maintain independence and re-engage in their community.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".