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Record W2999746377 · doi:10.1186/s13011-019-0250-1

A rapid access to addiction medicine clinic facilitates treatment of substance use disorder and reduces substance use

2020· article· en· W2999746377 on OpenAlex
David Wiercigroch, Hasan Sheikh, Jennifer Hulme

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSubstance Abuse Treatment Prevention and Policy · 2020
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity Health NetworkCanada Research ChairsUniversity of TorontoToronto General HospitalUniversity of New Brunswick
FundersSpoedeisende Geneeskunde OnderzoeksfondsUniversity of TorontoUniversity Health Network
KeywordsMedicineReferralBuprenorphineOpioid use disorderAddiction medicineAddictionSubstance abusePsychiatryAlcohol use disorderEmergency departmentFamily medicineEmergency medicineInternal medicineAlcoholOpioid

Abstract

fetched live from OpenAlex

BACKGROUND: Substance use is prevalent in Canada, yet treatment is inaccessible. The Rapid Access to Addiction Medicine (RAAM) clinic opened at the University Health Network (UHN) in January 2018 as part of a larger network of addictions clinics in Toronto, Ontario, to enable timely, low barrier access to medical treatment for substance use disorder (SUD). Patients attend on a walk-in basis without requiring an appointment or referral. We describe the RAAM clinic model, including referral patterns, patient demographics and substance use patterns. Secondary outcomes include retention in treatment and changes in both self-reported and objective substance use. METHODS: The Electronic Medical Record at the clinic was reviewed for the first 26 weeks of the clinic's operation. We identified SUD diagnoses, referral source, medications prescribed, retention in care and self-reported substance use. RESULTS: The clinic saw 64 unique patients: 66% had alcohol use disorder (AUD), 39% had opiate use disorder (OUD) and 20% had stimulant use disorder. Fifty-five percent of patients were referred from primary care providers, 30% from the emergency department and 11% from withdrawal management services. Forty-two percent remained on-going patients, 23% were discharged to other care and 34% were lost to follow-up. Gabapentin (39%), naltrexone (39%), and acamprosate (15%) were most frequently prescribed for AUD. Patients with AUD reported a significant decrease in alcohol consumption at their most recent visit. Most patients (65%) with OUD were prescribed buprenorphine, and most patients with OUD (65%) had a negative urine screen at their most recent visit. CONCLUSION: The RAAM model provides low-barrier, accessible outpatient care for patients with substance use disorder and facilitates the prescription of evidence-based pharmacotherapy for AUD and OUD. Patients referred by their primary care physician and the emergency department demonstrated a reduction in median alcohol consumption and high rates of opioid abstinence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.109
GPT teacher head0.367
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it