Discharge Outcomes in Seniors Hospitalized for More than 30 Days
Bibliographic record
Abstract
Hospitalization is a sentinel event that leads to loss of independence for many seniors. This study of long-stay hospitalizations (more than 30 days) in seniors was undertaken to identify risk factors for not going home, to characterize patients with risk factors who did go home and to describe 1-year outcomes following home discharge. Using Manitoba's health care databases, the likelihood of death in hospital, discharge to a nursing home, and transfer to another hospital was determined for a set of risk factors in seniors with long-stay hospitalizations in Winnipeg's acute hospitals. Of the 17,984 long-stay hospitalizations during 1993-2000, 45 per cent were discharged home, 20 per cent died, and 30 per cent were discharged to a nursing home or another hospital. Seniors who received home care prior to hospitalization were more likely to be discharged to a nursing home or die in hospital than to go home. Stroke and cognitive impairment increased the likelihood of discharge to a nursing home. Seniors with neoplasms, multiple co-morbidities, and length-of-stay more than 120 days were more likely to die in hospital. Long-stay patients with risk factors who did go home had few co-morbidities. Within 1 year of home discharge, 20 per cent of seniors died, 5-15 per cent were admitted to a nursing home or long-term care institution, and 26-35 per cent of persons were re-hospitalized from home. A full 37 per cent experienced none of these outcomes. Our findings point to opportunities to improve discharge outcomes and plan support services for seniors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".