STROKE CARE AND OUTCOMES IN COMPLEX CONTINUING CARE AND LONG-TERM CARE IN ONTARIO, CANADA, 2010-2015
Bibliographic record
Abstract
Background: In Ontario, care provided to stroke survivors in Complex Continuing Care (CCC) and Long Term Care (LTC) has been largely unexamined. The 2018 Ontario Stroke Evaluation Report begins to address this knowledge gap by describing stroke survivor characteristics, clinical health status, outcomes and health care system journey, the provision of rehabilitation therapy, relevant stroke best practices and patient experience.Methods: Using an encrypted health card number, we identified stroke survivors within 180 days of their acute stroke hospitalization who were admitted to CCC and LTC in Ontario between April 2010 and March 2015. We report on stroke survivors with length of stay greater than 14 days, who had a full Resident Assessment based on the Resident Assessment Instrument u2013 Minimum Data Set (RAI-MDS) 2.0 from the CIHI- Continuing Care Reporting System.Results: Report findings for CCC and LTC settings include:- the proportion of stroke survivors >85 years, at risk for depression,twith severe cognitive impairment, requiring extensive assistance with ADLs, who experienced a fall,t who experienced pain, with communication limitations, who received 3 core rehabilitation therapies, who accessed inpatient rehabilitation prior to admissiontt- Mean minutes/day of PT, OT, SLPtt- Health Related Quality of life scorettConclusion: Stroke survivors in CCC and LTC represent a high burden of care and rehabilitation therapies available are limited. Ongoing efforts to increase access to inpatient rehabilitation for survivors of severe stroke are required. The findings of this report inform system planning and identify opportunities for quality initiatives and research within these settings.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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; 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".