Case Management in an Acute-Care Hospital: Collaborating for Quality, Cost-Effective Patient Care
Bibliographic record
Abstract
Case management has recently been advanced as a valuable component in achieving quality patient care that is also cost-effective. At St. Michael's Hospital, in Toronto, Ontario, case managers from a variety of professional backgrounds are central to a new care initiative--Rapid Assessment and Planning to Inform Disposition (RAPID)--in the General Internal Medicine (GIM) Unit that is designed to improve patient care and reconcile high emergency department volumes through "smart bed spacing." Involved in both planning and RAPID, GIM's case managers are the link between patient care and utilization management. These stewards of finite resources strive to make the best use of dollars spent while maintaining a commitment to quality care. Collaborating closely with physicians and others across the hospital, GIM's case managers have been instrumental in bringing about significant improvements in care coordination, utilization management and process redesign.
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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 | 0.022 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".