Evidence map›Paper›PMID 42433393›Full record

ArticleCritical public health2026

Real-world management of opioid use disorder in primary care 2015-2019: associations between clinical practice attributes, diagnosis, and treatment.

Esther E Velásquez, Mathew V Kiang

Abstract read
In one paragraph

Article in Critical public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Esther E VelásquezCenter for Population Health Sciences, Stanford University, Stanford, CA, USA.ORCID 0000-0002-3572-4629
Mathew V KiangDepartment of Epidemiology and Population Health, Stanford University, Stanford, CA, USA.

Funding

Reducing racial disparities in the treatment of opioid use disorder using machine learning-based causal analysisR00DA051534 · NIDA · STANFORD UNIVERSITY · PI KIANG, MATHEW VINHHOA · 2022 to 2024
$747k
NIDA NIH HHS R00 DA051534
6 · The paper itself

Abstract

Expanding the treatment of opioid use disorder (OUD) remains a national priority and given constraints on treatment access, primary care may be an essential treatment context. While intervention studies within primary care have demonstrated efficacy, barriers to successful implementation and scale-up persist. The purpose of this work is to describe real-world management of OUD in primary care and assess how attributes of clinical practices are associated with rates of diagnosis and treatment. This observational study uses electronic health records from the American Family Cohort, a research dataset derived from PRIME, a Qualified Clinical Data Registry for primary care. The analytic cohort includes 854 clinical practices that were active between 2015-01-01 and 2019-12-31 and 4,767,971 patients attending those clinical practices. Overall, the OUD prevalence was 0.59% between 2015 and 2019. Approximately two-thirds of all patients with OUD and nearly 90% of all visits related to OUD were concentrated in only 50 primary care practices (5.8%). High-prevalence practices tended to be in metropolitan areas and have a higher ratio of physicians and behavioral health providers per patient. The concentrated distribution of patients with OUD in our study suggests that primary care practices are an important but underused tool for OUD. Further, targeted investment in a small number of high-volume practices may be more efficient for population health impact than universal scale-up.

Indexed as

access to treatmentepidemiologyhealth care deliveryOpioid use disorderprimary care

Identifiers

PMID42433393
PMCPMC13354046

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.