Abstract 7: The Impact of Post-Stroke Rehabilitation on 2-year Healthcare Costs in Ontario, Canada: Can Rehabilitation Save Us Money?
Bibliographic record
Abstract
Introduction: A substantial evidence base supports the positive benefits of post-stroke rehabilitation. The objective of this study was to evaluate the impact of inpatient rehabilitation on 2-year healthcare costs in Ontario, Canada. Methods: Acute patient data was drawn from the 2004 and 2008 Ontario Stroke Audits for 3439 patients with ischemic stroke discharged alive from an acute care hospital. Patients were assigned a propensity score using 15 demographic and clinical variables. Patients admitted to inpatient rehabilitation (Rehab) were then matched one-to-one with a patient not admitted to inpatient rehabilitation (No-Rehab) using propensity score and modified Rankin Scale (mRS) score. The cohort was stratified by mRS into three groups (mRS 0-2,3,4-5) and comparisons were drawn between Rehab and No-Rehab patients for 2-year mortality and government-billed healthcare costs (hospital, home care, and drug benefit costs). Results: No difference in mortality was noted between Rehab and No-Rehab patients with discharge mRS scores of 0-2 (p=0.39), but Rehab patients cost an average of $33,056 more over the 2 years (p<0.001) and $63 more per day survived (p<0.0001). Among patients with mRS 3, Rehab patients were significantly more likely to survive to 2 years (p<0.001), and cost an average of $22,394 more up to 2 years (p<0.001) and $5 more per day survived (p<0.0001). Rehab patients with mRS scores of 4-5 were significantly more likely to survive to 2-years (p=0.01), but cost an average of $6,607 less (p=0.24) and $29 less per day survived (p=0.07). Conclusions: Findings suggest that disability level plays an important role in the cost-effectiveness of inpatient rehabilitation. Among patients with milder disability, inpatient rehabilitation is significantly more costly with no demonstrated benefit in 2-year mortality. However among patients with moderate to severe disability, inpatient rehabilitation significantly reduces mortality rates and may actually reduce overall healthcare spending up to 2-years post stroke.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".