The mobile seniors’ clinic - an innovative transition of care for frail older adults
Bibliographic record
Abstract
BACKGROUND: This study aims to evaluate the impact of Quebec's first hospital-at-home-inspired mobile Seniors' Clinic, the "Clinique des Ainés (CDA)", on frail older adults' returns to the Emergency Department (ED), mortality, and hospital Length Of Stay (LOS) and rehospitalizations. METHODS: Design: Quasi-experimental pre-post implementation cohort study. POPULATION: Patients aged ≥ 75 years admitted to the short-term geriatric unit after an ED consultation (control) or included by the CDA (intervention). OUTCOMES: return to ED (RtoED), mortality, ED & hospital LOS, and rehospitalizations. STATISTICAL ANALYSES: Multivariable regression modelling. RESULTS: Overall, 891 patients were included. At the intervention site (CDA) (n = 437), RtoED were similar at 30 (17.5% & 19.5%, p = 0.58), 90 (34.4% & 37.3%, p = 0.46) and 180 days (47.2% & 54.0%, p = 0.07) in the pre and post-implementation phases. No mortality differences were found. The hospitalization LOS was significantly shorter (28.26 and 14.22 days, p < 0.01). At 90 days, rehospitalization LOS was decreased by 8.51 days (p = 0.02) and by 6.48 days at 180 days (p = 0.03). Compared to the control site (n = 454) in the post-implementation phase, RtoED was 54% at the intervention site compared to 44.1% (p = 0.02) at 180 days. The CDA had a lower adjusted probability of mortality at 90 days compared to the control site (4.8% VS 11.7%, p = 0.03). No rehospitalization LOS differences were noted. CONCLUSIONS: The Clinique des Ainés showed effectiveness in caring for frail older patients in their homes by decreasing their hospital LOS by half and 90 days mortality risk. It was a safe care trajectory without a clinically significant increase in ED returns or mortality.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".