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Record W4410114091 · doi:10.7759/cureus.83593

Exploratory Analysis on the Role of Video Tools and Multidisciplinary Healthcare Providers to Aid Counselling for Buprenorphine/Naloxone Induction Within the Evaluating Microdosing in the Emergency Department Study

2025· article· en· W4410114091 on OpenAlexaffabout
Viseth Long, Elle Wang, Anthony Lau, Jessica Moe

Bibliographic record

VenueCureus · 2025
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsCanadian Association of Nurses in OncologyVancouver General HospitalSt. Paul's HospitalUniversity of British ColumbiaOkanagan University CollegeKelowna General Hospital
Fundersnot available
KeywordsMedicineBuprenorphine(+)-NaloxoneEmergency departmentMedical emergencyMultidisciplinary approachHealth careExploratory researchNursingOpioid

Abstract

fetched live from OpenAlex

Introduction To address the rising deaths and hospitalizations related to opioid toxicity, buprenorphine/naloxone has been provided as a frontline treatment within the emergency department (ED), allowing increased access to opioid agonist therapies (OAT). However, several barriers exist toward initiating patients on buprenorphine/naloxone within the ED, such as shortages in healthcare staff and time limitations in the urgent ED environment. To overcome these barriers, we utilized counselling tools and engaged multidisciplinary healthcare providers to counsel patients for our study, Evaluating Microdosing in the Emergency Department (EMED). The primary objective of this analysis is to describe the proportion of healthcare providers counselling for buprenorphine/naloxone induction within the EMED study, before and after the implementation of a counselling video, and across different time intervals. Additionally, we aim to compare the completion status of enrollment when patients were counselled by different types of healthcare providers. By analyzing these factors, we aim to explore how collaboration with multidisciplinary healthcare providers and the use of video tools can impact buprenorphine/naloxone induction in the ED, thereby increasing accessibility of take-home OAT. Methods Data regarding the type of healthcare worker providing counselling for the EMED study was collected at Vancouver General Hospital from July 23, 2021, to December 31, 2023. The EMED study is an open-label, randomized controlled trial comparing microdosing and standard dosing take-home regimens. We analyzed 172 providers involved in counselling patients for the study. We stratified the data by month, week, and day of the week to assess trends in counselling frequencies. Results We found a statistically significant increase in the proportion of emergency physicians counselling after the implementation of the counselling video. Specifically, we found there was a statistically significant increase in the evenings. Furthermore, we found that pharmacists completed a greater proportion of counselling for buprenorphine/naloxone induction throughout the study period, and there was no statistically significant difference between the completion status of enrollment when counselled by either provider. Conclusion We can improve patient access to buprenorphine/naloxone induction counselling by utilizing an adjunct video tool and distributing workload between emergency physicians and clinical pharmacists. Future sites interested in providing take-home buprenorphine/naloxone kits may benefit from implementing video tools and involving clinical pharmacists to mitigate workflow burdens.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.057
GPT teacher head0.367
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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