Postdischarge Care for Depression in Ontario
Bibliographic record
Abstract
OBJECTIVE: People hospitalized for depression are often discharged before the acute phase of their illness has resolved and need timely care transitions to prevent relapse. We examined 30-day postdischarge service use for Ontarians, aged 15 years or older, who were hospitalized for depression. We focused on a pattern consistent with guideline and policy directions: higher rates of physician visits, postdischarge, combined with lower rates of emergency department (ED) admissions or rehospitalization. METHODS: Administrative data for the fiscal year of 2005 were used to identify hospitalizations for depression and subsequent physician visits, ED admissions, or readmissions for depression within 30 days, postdischarge. Sex, age, income, and geographic location were examined along with the relation between health care resources (beds, EDs, and physicians) and postdischarge service use. RESULTS: Sixty-three percent of patients discharged for depression were followed, within 30 days, by a physician visit for depression. Twenty-five percent were either rehospitalized or visited an ED. Women and people from urban or high income areas were more likely to have postdischarge physician visits. Readmissions and ED visits were correlated with number of EDs, but postdischarge physician visits were not related to the number of general practitioners, family physicians, and psychiatrists in the local area. CONCLUSION: One-third of Ontarians hospitalized for depression did not receive recommended follow-up outpatient care within 30 days of discharge and one-quarter received follow-up through ED visits or readmissions, highlighting the need to improve coordination and integration across care settings for these patients. There are tested transitional and outpatient models that improve quality and outcomes of depression care that merit serious consideration.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".