Models of shared care for the management of psychotic disorder after first diagnosis in Ontario
Bibliographic record
Abstract
OBJECTIVE: To describe the provision of care for young people following first diagnosis of psychotic disorder. DESIGN: Retrospective cohort study using health administrative data. SETTING: Ontario. PARTICIPANTS: People aged 14 to 35 years with a first diagnosis of nonaffective psychotic disorder in Ontario between 2005 and 2015 (N=39,449). MAIN OUTCOME MEASURES: Models of care, defined by psychosis-related service contacts with primary care physicians and psychiatrists during the 2 years after first diagnosis of psychotic disorder. RESULTS: During the 2-year follow-up period, 29% of the cohort received only primary care, 30% received only psychiatric care, and 32% received both primary and psychiatric care (shared care). Among the shared care group, 72% received care predominantly from psychiatrists, 20% received care predominantly from primary care physicians, and 9% received approximately equal care from psychiatry and primary care. Variation in patient and physician characteristics was observed across the different models of care. CONCLUSION: One in 3 young people with psychotic disorder received shared care during the 2-year period after first diagnosis. The findings highlight opportunities for increasing collaboration between primary care physicians and psychiatrists to enhance the quality of care for those with early psychosis.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".