Use of health care services by patients with co-occurring severe mental illness and substance use disorders
Bibliographic record
Abstract
BACKGROUND: To better respond to the health care needs of people with co-occurring mental illness and substance use disorders, it is vital to understand their itinerary through the health care system. AIM: To describe the characteristics of service utilization among patients with co-occurring disorders in a large urban area. METHOD: = 5467) constituted from administrative and clinical databases. Those identified as having substance use disorders and psychoses were followed over 12 months with respect to their utilization of medical services. A descriptive analysis of the data and a two-step cluster analysis were undertaken. RESULTS: Our analyses revealed a relatively high utilization of emergency services, outpatient clinics, private practices and hospitalization among patients with co-occurring disorders of severe mental illness and substance use. The two-step cluster analysis produced four heterogeneous groups in terms of service utilization. CONCLUSIONS: This study demonstrates the need to develop strategies for organizing health care and services that are adapted to various sites of service utilization and to diverse profiles of patients with co-occurring mental illness and substance use disorders.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".