Quality Changes after Implementation of an Episode of Care Model with Strict Criteria for Physical Therapy in Ontario's Long‐Term Care Homes
Bibliographic record
Abstract
OBJECTIVES: To describe the proportion of residents receiving rehabilitation in long-term care (LTC) homes, and scores on activities of daily living (ADL) and falls quality indicators (QIs) before and after change from fee-for-service to an episode of care model; and to evaluate the effect of the change on the QIs. DATA SOURCES: Secondary data were collected from all LTC homes in Ontario, Canada, between January 1, 2011 and March 31, 2015. Variables of interest were the proportion of residents per home receiving physical therapy (PT), and the scores on seven ADL and one falls QI. STUDY DESIGN: Retrospective, longitudinal study. DATA EXTRACTION: All data were extracted from the Resident Assessment Instrument Minimum Data Set. PRINCIPAL FINDINGS: Fewer residents received PT after the policy change (84.6 percent, 2011; 56.6 percent, 2015). The policy change was associated with improved performance on several ADL QIs. However, having a large proportion of residents receive no PT or little PT was associated with poorer performance on two of the QIs measuring improvement in ADLs [No PT: -0.029 (-0.043 to -0.014); -0.048 (-0.068 to -0.027). PT <45 minutes per week: -0.012 (-0.026 to -0.002); -0.026 (-0.045 to -0.007); p < .01]. CONCLUSIONS: While controversial, the policy and subsequent PT service delivery change appears to be associated with improved performance on several ADL QIs, except in homes where a large proportion of residents receive no PT and low time-intensive PT.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".