Building a hospital‐based addiction medicine consultation service in Vancouver, Canada: the path taken and lessons learned
Bibliographic record
Abstract
BACKGROUND AND AIMS: To improve evidence-based addiction care in acute care settings, many hospitals across North America are developing an inpatient addiction medicine consultation service (AMCS). St Paul's Hospital in Vancouver, Canada houses a large interdisciplinary AMCS. This study aimed to: (1) describe the current model of clinical care and its evolution over time; (2) evaluate requests for an AMCS consultation over time; (3) highlight the established clinical training opportunities and educational curriculum and (4) provide some lessons learned. DESIGN, SETTING AND PARTICIPANTS: A retrospective observational analysis in an urban, academic hospital in Vancouver, Canada with a large interdisciplinary AMCS, studied from 2013 to 2018, among individuals who presented to hospital and had a substance use disorder. MEASUREMENTS: Data were collected using the hospital's electronic medical records. The primary outcome was number of AMCS consultations over time. FINDINGS: In 2014 the hospital's AMCS was restructured into an academic, interdisciplinary consultation service. A 228% increase in the number of consultations was observed between 2013 (1 year prior to restructuring) and 2018 (1373 versus 4507, respectively; P = 0.027). More than half of AMCS consultations originated from the emergency department, with this number increasing over time (55% in 2013 versus 74% in 2018). Referred patients were predominantly male (> 60% in all 5 years) between the ages of 45 and 65 years. Reasons for consultation remained consistent and included: opioids (33%), stimulants (30%), alcohol (23%) and cannabis use (8%). CONCLUSIONS: After St Paul's Hospital in Vancouver, Canada was restructured in 2014 to a large, interdisciplinary addiction medicine consultation service (AMCS), the AMCS saw a 228% increase in the number of consultation requests with more than half of requests originating from the emergency department. Approximately two-thirds of consultation requests were for opioid or stimulant use.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".