Postdischarge service utilisation and outcomes among Chinese and South Asian psychiatric inpatients in Ontario, Canada: a population-based cohort study
Bibliographic record
Abstract
Objective We sought to examine the short-term and long-term impacts of psychiatric hospitalisations among patients of Chinese and South Asian origin. Design Retrospective population-based cohort study using linked health administrative data. Setting We examined all adult psychiatric inpatients discharged between 1 April 2006 and 31 March 2014 in Ontario, Canada, who were classified as Chinese, South Asian and all other ethnicities (ie, ‘general population’) using a validated algorithm. We identified 2552 Chinese, 2439 South Asian and 127 142 general population patients. Primary and secondary outcome measures We examined psychiatric severity measures at admission and discharge and performed multivariable logistic regression analyses to examine 30-day, 180-day and 365-day postdischarge service utilisation and outcomes, comparing each of the ethnic groups with the reference population, after adjustment for age, sex, income, education, marital status, immigration status, community size and discharge diagnosis. Results Despite presenting to hospital with greater illness severity, Asian psychiatric inpatients had shorter lengths of hospital stay and greater absolute improvements in mental health and functional status at discharge compared with other inpatients. After hospitalisation, Chinese patients were more likely to visit psychiatrists and South Asian patients were more likely to seek mental healthcare from general practitioners. They were also less likely to have a psychiatric readmission or die 1 year following hospitalisation (adjusted ORChinese=0.87; 95% CI 0.79 to 0.97; adjusted ORSouth Asian=0.82, 95% CI 0.73 to 0.91). Findings were consistent across genders, psychiatric diagnoses and immigrant groups. Conclusion Once hospitalised, patients of Chinese and South Asian origin fared as well as or better than general population patients at discharge and following discharge, and had a positive trajectory of psychiatric service utilisation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".