An Evaluation of a Community-Based, Integrated Crisis-Case Management Service
Bibliographic record
Abstract
This study presents findings of an evaluation of a community-based crisis service that used systems enhancement funding to modify services. In addition to developing timelier crisis services and increasing mobile capacity, the service adaptations focused on broadening the scope of the crisis service and addressing the follow-up needs of individuals served. While service development was guided by the research and best practice literature, there was little guidance available on how to address the latter two goals. The development of a transitional case management model integrated with crisis services was an innovation in service delivery. The evaluation used existing databases to compare crisis service delivery between two distinct periods (i.e., “old model” vs. “new model”). Study findings suggest that the new model did lead to the expected changes in service utilization patterns, specifically to increased service capacity, greater access to mobile crisis services, improved access to a broader community population, and more appropriate patterns of service delivery with respect to fewer days of crisis service and exit dispositions more consistent with crisis resolution. Rankings of acceptance of the new crisis service by the local service network varied greatly across service sectors, suggesting the need for more strategic community outreach efforts. The findings indicate that policy and funding opportunities within the mental health system need to be flexible and sensitive enough to address emerging issues in the field and to facilitate service innovations.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".