CLINICAL AND ADMINISTRATIVE OUTCOMES DURING PUBLICLY-FUNDED INPATIENT STROKE REHABILITATION BASED ON A CASE-MIX GROUP CLASSIFICATION MODEL
Bibliographic record
Abstract
OBJECTIVES: To determine efficiency and efficacy of publicly-funded inpatient stroke rehabilitation based on a Case-Mix Group Classification Model, and to analyse the usefulness of this decisional aid in the refinement of rehabilitation services delivery needed to optimize accessibility to inpatient rehabilitation services for individuals with stroke in a publicly-funded healthcare system. DESIGN: Individuals with stroke (n=422) who received inpatient rehabilitation through the Montreal Rehabilitation Hospital Network were included in this retrospective study. Clinical (total, motor and cognitive-Functional Independence Measure (FIM) scores, percentage of discharge to community) and administrative outcomes (onset to rehabilitation interval, length of inpatient rehabilitation stay, length of stay efficiency) were measured. RESULTS: Across Case-Mix Groups, mean onset to rehabilitation days varied between 16.2 (5.7) and 32.0 (19.4) days whereas the mean length of stay fluctuated between 27.5 (13) and 77.0 (27) days. Best total (41.6 (21.4)) and motor-FIM (38.9 (19.0)) gains were observed in most severely disabled cases (114) whereas the Case-Mix Group 103 presented the best cognitive-FIM gain (5.8 (4.0)). Optimal mean total, motor and cognitive-FIM efficiency rates, found in moderately disabled stroke patients, were 0.668 (0.434), 0.634 (0.377) and 0.15 (0.136), respectively. Majority of patients returned home following rehabilitation in all Case-Mix Groups (63.6% to 96.4%) except for groups 112 and 108. CONCLUSION: Moderate to good length of stay efficiencies are observed among all Case-Mix Group following stroke rehabilitation. In fact, individuals with moderate disability present the best rate of recovery. Variations in length of stay efficiency suggest that the use of a Case-Mix Group Classification Model in stroke rehabilitation could represent an innovative approach, especially for program evaluation in publicly-funded and universal-access rehabilitation hospitals.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".