ESTABLISHING THE EFFECTIVENESS OF AN ACUTE CARE FOR ELDERS (ACE) STRATEGIC DELIVERY MODEL
Bibliographic record
Abstract
The Acute Care for Elders (ACE) Strategy recognizes the high-risk environment of the acute care hospital setting to all persons aged 65+. This population accounts for 42% of hospital admissions and 58% of overall hospital days in Ontario. We wanted to determine the effectiveness of a multi-component ACE Strategy to impact patient and system outcomes for older adults admitted to the general medicine wards from April 1, 2009 to March 31, 2014. A quasi-experimental time series analysis was conducted on the outcomes of 9,595 patient admissions. Results showed there was a 27.8% decrease in mean length of stay, 23.8% decline in the ALOS/ELOS ratio, and a 13.4% decline in readmissions with an 11% increase in the number of older patients being able to return home after discharge. This Strategy demonstrates the benefits from linking multiple evidence-informed models across the continuum of care in achieving patient and system outcomes.
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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 | 0.047 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".