Evolution of a Model : Creating Stroke Rehabilitation Quality in Community Settings
Bibliographic record
Abstract
Title: Evolution of a model: Creating stroke rehabilitation quality in community settingsAuthors: Jeanne Bonnell, Theresa GrantIntroduction: Numerous health report cards in Ontario highlight geographical inequities in relation to stroke rehabilitation access and outcomes. These gaps necessitate development and evaluation of care models that bring stroke rehabilitation closer to home for people living in smaller communities. The Champlain Local Health Integration Network has established a community-based stroke rehabilitation model to deliver specialized services in the Stormont, Glengarry, Dundas and Akwesasne (SDG-A) and more recently in Renfrew County (RC) where people had with no previous access to outpatient stroke rehabilitation. Methods: Specialized Interdisciplinary rehabilitation was delivered through a flexible model that allowed for both home and community clinic visits over a period of 8-12 weeks post hospital discharge. Operating procedures included regular team rounds, patient conferences and liaison with primary care. Innovations included the adoption of in-home technologies: Jintronix - a game-based platform in which a therapist recommends exercises and levels, and then can monitor performance and adjust programming remotely, and iPads - primarily used for Speech and Language home programming between visits but can also be used for remote visits in rural areas. Results: In SDG-A, a total of 76 patients were referred over 12 months and received 25 therapy sessions (mean) each. Between admission and discharge, mean Canadian Occupational Performance Measure (COPM) scores improved by 3 performance and 3 satisfaction points on a 10 point scale. Reintegration to Normal Living Index (RNLI) scores revealed a mean improvement of 11% on a 110 point scale. Depression screening with Patient Health Questionnaire 9 (PHQ-9) indicated that fewer patients were at risk of depression at discharge as indicated by a mean drop of 4 points on the 10 point scale. All outcomes surpassed clinically important difference values indicating a positive effect. Since expanding to RC in April 2018, 42% of all referrals have been diverted from in-patient rehab services, resulting in cost savings.Conclusion: This model of community based rehabilitation was found to be feasible to deliver, and effective. Prioritized next steps involve enhanced integration of hospital and community care stroke teams and expansion.
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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 | 0.048 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".