Care by design: New model of coordinated on-site primary and acute care in long-term care facilities.
Bibliographic record
Abstract
PROBLEM ADDRESSED: A recently implemented model of care in long-term care facilities (LTCFs) called Care by Design addresses concerns about a previously uncoordinated care system, a reduction in family physician services, and high rates of ambulance transports to emergency departments. OBJECTIVE OF PROGRAM: Care by Design is designed to increase access to care and continuity and quality of care by family physicians, reduce unwanted and unnecessary transfers to the emergency department, and lessen the burden on care teams including physicians and nurses in LTCFs. PROGRAM DESCRIPTION: The core of Care by Design is a dedicated family physician for each LTCF floor, with regular on-site visits; physician on-call coverage, 24 hours a day, 7 days a week; and standing orders and protocols. Care by Design also includes a comprehensive geriatric assessment tool, an interdisciplinary team approach, access to a dedicated extended care paramedic program to respond to urgent care needs, and ongoing performance measurement. CONCLUSION: Care by Design aims to improve on-site care for LTCF residents and family physicians' experiences with providing care in several ways, including increased clinical efficiency, communication, and continuity, and appropriate support within the interdisciplinary team model.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".