Models of Concurrent Disorder Service: Policy, Coordination, and Access to Care
Bibliographic record
Abstract
Background: Societal capacity to address the service needs of persons with concurrent mental health and substance-use disorders has historically been challenging given a traditionally siloed approach to mental health and substance-use care. As different approaches to care for persons with concurrent disorders emerge, a limited understanding of current models prevails. The goal of this paper is to explore these challenges along with promising models of coordinated care across Canadian provinces. Materials and methods: A scoping review of policies, service coordination and access issues was undertaken involving a review of the formal and grey literature from 2000-2018. The scoping review was triangulated by an analysis of provincial auditor general reports. Results: Models of concurrent disorders service were found to have evolved unevenly. Challenges related to the development of system-level networks that foster service coordination and policy accountability were found to inhibit integrated care. Conclusion: Emergent models of coordinated care were found to encompass regional networks, clinical information-sharing, cross-training, improved scope of care to include psychologists and align physician incentives with patient needs to better support patient 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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".