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Record W4408413161 · doi:10.1136/bmjoq-2024-003088

Improving screening rates for sexually transmitted and blood-borne infections among patients initiating care in a low-barrier addiction medicine clinic: a quality improvement project

2025· article· en· W4408413161 on OpenAlexafffund
Geneviève Kerkerian, Cole Stanley, Rachelle Funaro, Emma Mitchell

Bibliographic record

VenueBMJ Open Quality · 2025
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsAIDS VancouverVancouver Coastal HealthUniversity of British ColumbiaProvidence Health Care
FundersProvidence Health Care
KeywordsMedicinePsychological interventionFamily medicineChlamydiaAddictionSyphilisPopulationHuman immunodeficiency virus (HIV)PsychiatryEnvironmental healthImmunology

Abstract

fetched live from OpenAlex

Despite a high prevalence of sexually transmitted and blood-borne infections (STBBIs) among patients with substance use disorders, screening rates in addiction medicine settings are often low. At baseline in our addiction clinic, only 65% of patients were offered screening and only 6% completed screening blood work. This quality improvement project aimed to improve the rate of STBBI screening among new intakes in our clinic by 50%.Interventions included the creation of clinic screening guidelines to include annual screening for all patients for HIV, hepatitis B and C, syphilis, gonorrhoea and chlamydia. Additionally, an on-site phlebotomist was hired. These interventions increased screening rates to an average of 33% with the greatest improvement seen after the addition of the phlebotomist. We found that implementing a bundle of interventions improved rates of screening and detection of STBBIs in a low-barrier addiction medicine clinic. Comprehensive infection prevention, screening and linkage-to-treatment protocols are needed to close gaps in care for this vulnerable patient population.

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.

How this classification was reachedexpand

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)0.006
metaresearch head score (Gemma)0.008
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 score0.300
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.090
GPT teacher head0.477
Teacher spread0.387 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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