Monitoring Utilization of a Large Scale Addiction Treatment System: The Drug and Alcohol Treatment Information System (DATIs)
Bibliographic record
Abstract
Client-based information systems can yield data to address issues of system accountability and planning, and contribute information related to changing patterns of substance use in treatment and, indirectly, general populations. The Drug and Alcohol Treatment Information System (DATIS) monitors the number/types of clients treated in approximately 170 publicly-funded addiction treatment agencies in Ontario. The purpose of this study was to estimate the caseload of addiction treatment agencies, and describe important characteristics of clients, their patterns of service utilization and trends over-time from 2005 to 2010. In 2009-2010, 47,065 individuals were admitted to treatment. Since 2005-2006, there has been an increase in adolescents/youth in treatment, and a decrease in the male-female gender ratio. Alcohol problems predominated, but an increasing proportion of clients used cannabis and prescription opioids. DATIS is an evolving system and an integral component of Ontario's performance measurement system. Linkages with healthcare information systems will allow for longitudinal tracking of client health-related outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".