Evidence map›Paper›PMID 40052707›Full record

ArticleDrug and alcohol review2025

Patterns of opioid prescribing to opioid-naive patients after surgical and emergency care: A population-based cross-sectional study using linked administrative databases in Nova Scotia (2017-2019).

Roah A Merdad, Mark Asbridge, Samuel Campbell, Daniel J Dutton, Jill A Hayden

Abstract read
In one paragraph

Article in Drug and alcohol review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Roah A MerdadDepartment of Community Health and Epidemiology, Dalhousie University, Halifax, Canada.ORCID 0000-0002-7257-0040
Mark AsbridgeDepartment of Community Health and Epidemiology, Dalhousie University, Halifax, Canada.ORCID 0000-0002-2168-6377
Samuel CampbellDepartment of Emergency Medicine, Dalhousie University, Halifax, Canada.
Daniel J DuttonDepartment of Community Health and Epidemiology, Dalhousie University, Halifax, Canada.
Jill A HaydenDepartment of Community Health and Epidemiology, Dalhousie University, Halifax, Canada.

Funding

A PhD thesis bursary provided by the Saudi Arabian Cultural Bureau fully covered data access expenses for this research
6 · The paper itself

Abstract

introductionTo describe opioid prescribing patterns for opioid-naive patients who filled prescriptions after surgical or emergency care.

methodsWe conducted a population-based, cross-sectional study of opioid-naive adults who filled opioid prescriptions within 14 days of receiving surgical or emergency care in Nova Scotia, Canada. Using linked administrative databases, we estimated the prevalence of opioid prescriptions with >7 days' supply, ≥90 morphine milligram equivalents (MME)/day or long-acting opioids. We assessed the association of care setting and specialty with these outcomes.

resultsAmong 124,515 patients, 36,716 (29.5%) were opioid-naive. The median opioid supply duration was 3 days (IQR 2-5), the median dose was 50 MME/day (IQR 30-75). Prescriptions for >7 days, ≥90 MME/day or involving long-acting opioids were filled by 10.9%, 20.2% and 0.7% of the patients, respectively. Hydromorphone (50%) and codeine (26.4%) were the most filled opioids. The emergency care setting had double the odds of filling >7 days' supply (OR 2.13, 95% CI 1.99-2.28), and 69% lower chance of filling ≥90 MME/day (OR 0.31, 95% CI 0.29-0.33) than surgical care. In the surgical care setting, there was significant variation across medical specialties. Otolaryngology was associated with a higher chance of prescribing >7 days' opioid supply than general surgery (OR 4.89, 95% CI 3.86-6.20). Orthopaedic surgery had a higher likelihood of ≥90 MME/day prescriptions (OR 2.92, 95% CI 2.58-3.30) than general surgery. DISCUSSION AND

conclusionsOpioid prescribing patterns vary significantly by setting and specialty in Nova Scotia, Canada. Our results emphasise the need for tailored guidelines that consider clinical context and specialty to enhance patient safety and reduce opioid misuse risk.

Indexed as

Analgesics, OpioidDrug PrescriptionsEmergency Medical ServicesPractice Patterns, Physicians'AdultAgedCross-Sectional StudiesDatabases, FactualFemaleHumansMaleMiddle AgedNova ScotiaPostoperative PainYoung AdultAnalgesics, Opioidemergency careopioidsprescribing patternsprovider specialtysurgical care

Identifiers

PMID40052707
PMCPMC12117293

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.