Delivering improved patient and system outcomes for hospitalized older adults through an Acute Care for Elders Strategy
Bibliographic record
Abstract
Acute care hospitals are widely recognized as potentially high-risk environments for older adults. In 2010, Mount Sinai Hospital conceived its Acute Care for Elders (ACE) Strategy as a multi-component intervention to improve the care of hospitalized older adults. In order to determine its effectiveness, we conducted a quasi-experimental time series analysis of 12,008 older patients admitted non-electively for acute medical issues over a 6-year period. Despite a 53% increase in annual admissions of older patients between 2009/2010 and 2014/2015, Mount Sinai decreased total lengths of stay and readmissions and reduced the direct cost of care per patient, leading to net savings of CDN$4.2 million in 2014/2015. This article presents Mount Sinai's ACE Strategy and discusses the benefits of implementing integrated evidence-based models across the continuum of care and how it is supporting the implementation of ACE Strategy models of care and care practices across Canada and beyond.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".