A STANDARD OF CARE FOR MOBILIZATION: STEPPING INTO THE FUTURE OF SENIOR-FRIENDLY CARE
Bibliographic record
Abstract
Low mobility during hospitalization is an under recognized epidemic leading to adverse outcomes. Early mobilization interventions have been shown to decrease length of stay and improve functional status. Sunnybrook Health Science Centres has a standard of care for mobility to ensure seniors maintain optimal function during hospitalization. The standard requires early and daily assessment of mobility status by the inter-professional health care team using an algorithm to create an individualized mobilization plan that promotes a minimum of 3 mobility activities daily. Mobility has been integrated into rounds, transfer of accountability and documentation. Patients meeting the mobility standard of care have increased from 16% to 81%, patients with documented mobility level from 29% to 96% and those with “out of bed” activities have increased from 35% to 71%. There has been a 5% increase in patients discharged home without support, no increase in injurious falls and LOS has remained stable.
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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 | 0.095 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.008 | 0.015 |
| Research integrity | 0.013 | 0.032 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".