Substance Use Disorder Presentations and Referral Patterns for an Emergency Department in a Northern Ontario City
Bibliographic record
Abstract
Objectives: Substance use, both alcohol and opioids, is higher in Sudbury, Ontario than in the remainder of the province and the numbers increased during COVID-19. In response to increased use during the pandemic, the hospital developed the Addictions Medicine Consult Service (AMCS) to complement the existing addiction services. After a full year of operation, a program evaluation was completed to determine the effectiveness and gaps of the AMCS, to enact changes for service improvement. Methods: A retrospective chart review was conducted. Analysis of the characteristics and frequency of people presenting with substance use to the emergency department, along with referrals to addiction services, was undertaken. Results: Fewer than seven percent of patients presenting with substance use in the emergency department were referred to the AMCS. The majority used alcohol and were housed, followed by those who used fentanyl who were unlikely to be housed. Many patients were referred to Crisis, the multidisciplinary mental health team in the hospital, which is available 24/7 but which does not include addictions expertise. Conclusions: Changes to service delivery to increase the use of the AMCS were implemented to improve service accessibility and delivery of care. These included nursing daily rounds in the emergency department and adding more direct links with resources in the community.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".