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Record W3209299048 · doi:10.1136/bmjqs-2021-013503

Association of clinical competence, specialty and physician country of origin with opioid prescribing for chronic pain: a cohort study

2021· article· en· W3209299048 on OpenAlexaffabout
Robyn Tamblyn, Nadyne Girard, John R. Boulet, Dale Dauphinée, Bettina Habib

Bibliographic record

VenueBMJ Quality & Safety · 2021
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsMcGill University
FundersFoundation for Advancement of International Medical Education and Research
KeywordsMedicineSpecialtyMedical prescriptionOpioidFamily medicineChronic painCompetence (human resources)Odds ratioLogistic regressionCohortEmergency medicinePsychiatryInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Although little is known about why opioid prescribing practices differ between physicians, clinical competence, specialty training and country of origin may play a role. We hypothesised that physicians with stronger clinical competence and communication skills are less likely to prescribe opioids and prescribe lower doses, as do medical specialists and physicians from Asia. METHODS: Opioid prescribing practices were examined among international medical graduates (IMGs) licensed to practise in the USA who evaluated Medicare patients for chronic pain problems in 2014-2015. Clinical competence was assessed by the Educational Commission for Foreign Medical Graduates (ECFMG) Clinical Skills Assessment. Physicians in the ECFMG database were linked to the American Medical Association Masterfile. Patients evaluated for chronic pain were obtained by linkage to Medicare outpatient and prescription files. Opioid prescribing was measured within 90 days of evaluation visits. Prescribed dose was measured using morphine milligram equivalents (MMEs). Generalised estimating equation logistic and linear regression estimated the association of clinical competence, specialty, and country of origin with opioid prescribing and dose. RESULTS: 7373 IMGs evaluated 65 012 patients for chronic pain; 15.2% received an opioid prescription. Increased clinical competence was associated with reduced opioid prescribing, but only among female physicians. For every 10% increase in the clinical competence score, the odds of prescribing an opioid decreased by 16% for female physicians (OR 0.84, 95% CI 0.75 to 0.94) but not male physicians (OR 0.99, 95% CI 0.92 to 1.07). Country of origin was associated with prescribed opioid dose; US and Canadian citizens prescribed higher doses (adjusted MME difference +3.56). Primary care physicians were more likely to prescribe opioids, but surgical and hospital-based specialists prescribed higher doses. CONCLUSIONS: Clinical competence at entry into US graduate training, physician gender, specialty and country of origin play a role in opioid prescribing practices.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.048
GPT teacher head0.400
Teacher spread0.352 · 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.

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".

Quick stats

Citations28
Published2021
Admission routes2
Has abstractyes

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