Safety of Discharge of Seniors from the Emergency Department to the Community
Bibliographic record
Abstract
This study investigated the safety of discharge of seniors (aged 65 and over) from Quebec emergency departments (EDs) to the community. Data from a 2006 survey of key informants at 103 Quebec adult non-psychiatric EDs were linked to data on a sample of 172,927 seniors who were discharged home from one of the EDs during the period February 2004-January 2005. During the 30 days after the ED visit, 1.0% of patients died, 5.0% returned to the ED and were admitted to hospital, 16.0% returned to the ED but were not admitted and 29.2% were prescribed a potentially inappropriate medication. Larger, urban EDs treated a higher-risk patient population (older, greater co-morbidity), and these seniors had worse outcomes. A minority of EDs, regardless of their size and the characteristics of patients treated, systematically provided services to improve the safety of discharge. Resources and services need to be improved in EDs, particularly those that serve higher-risk populations (e.g., systematic approaches to the identification and management of high-risk seniors, with appropriate referrals to community services), in the hospital (e.g., increased accessibility to acute care beds) and in the community (e.g., increased accessibility to home care, outpatient geriatric assessment and primary medical care).
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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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".