Evidence map›Paper›PMID 39438381›Full record

ArticleJournal of general internal medicine2025

Demographic, Social, Behavioral, and Clinical Characteristics Associated with Long-Term Opioid Therapy and Any Opioid Prescription in High-Risk VA Patients.

Dan V Blalock, Liberty Greene, Ryan M Kane, Valerie A Smith, Josephine Jacobs, Mayuree Rao, Alicia J Cohen, Donna M Zulman, Matthew L Maciejewski

Abstract read
In one paragraph

Article in Journal of general internal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Dan V BlalockCenter of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System, Durham, NC, USA.ORCID 0000-0002-8349-9825
Liberty GreeneCenter for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, CA, USA.
Ryan M KaneDivision of General Internal Medicine, Department of Medicine, Duke University, Durham, NC, USA.
Valerie A SmithCenter of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System, Durham, NC, USA.
Josephine JacobsCenter for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, CA, USA.
Mayuree RaoSeattle-Denver Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, WA, USA.
Alicia J CohenCenter of Innovation in Long Term Services and Supports, VA Providence Healthcare System, Providence, RI, USA.
Donna M ZulmanCenter for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, CA, USA.
Matthew L MaciejewskiCenter of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System, Durham, NC, USA. matthew.maciejewski@va.gov.

Funding

HSRD VA CIN 13-410HSRD VA I01 HX003269HSRD VA IK2 HX003013HSRD VA IK2 HX003085HSRD VA IK6 HX003157U.S. Department of Veterans Affairs CDA 19-035U.S. Department of Veterans Affairs CDA 20-037U.S. Department of Veterans Affairs IIR 20-114VA RCS 10-391
6 · The paper itself

Abstract

backgroundSocial risks (individual social and economic conditions) have been implicated as playing a major role in the opioid epidemic and may be more prevalent in the most medically vulnerable patients. However, the extent to which specific social risks and other patient factors are associated with opioid use among high-risk patients has not been comprehensively assessed.

objectiveTo identify patient-reported and electronic health record (EHR)-derived demographic, social, behavioral/psychological, and clinical characteristics associated with opioid use in Veterans Affairs (VA) patients at high risk for hospitalization or death.

designWe used generalized estimating equations to calculate the probability of long-term opioid therapy (LTOT) and the probability of filling any opioid prescription (regardless of duration) over five intervals during a 4-year period (12/2016-12/2020).

participantsProspective cohort of 4121 medically high-risk VA patients not receiving palliative or end-of-life care, and who responded to a survey mailed to a nationally representative sample of 10,000 high-risk VA patients. MAIN MEASURES: Patient-reported demographic, social risk, behavioral/psychological, and clinical measures, and linked EHR-derived data. KEY

resultsThe average age was 69.8 years, 6.7% were female, and 17.5% were Non-Hispanic Black race/ethnicity. The majority had diagnosed chronic pain (76.1%). LTOT and any opioid prescription were positively associated with the following: younger age, non-Hispanic White race/ethnicity (compared to non-Hispanic Black race/ethnicity), male sex assigned at birth (LTOT only), not being currently employed, current tobacco use, no alcohol use, higher grit (any opioid prescription only), functional limitations, diagnosed chronic pain, lower comorbidity burden (LTOT only), obesity class I or class II/III (any opioid prescription only), undergoing surgery (any opioid prescription only), and diagnosed cancer (any opioid prescription only).

conclusionsMultifactor screening could help identify individuals at elevated risk for adverse opioid-related outcomes and augment current multifaceted initiatives, as several social risks and patient characteristics were predictors of LTOT and any opioid prescription.

Indexed as

Analgesics, OpioidChronic PainDrug PrescriptionsOpioid-Related DisordersVeteransAgedFemaleHumansMaleMiddle AgedProspective StudiesRisk FactorsUnited StatesUnited States Department of Veterans AffairsAnalgesics, Opioidlong-term opioid therapyopioid usesocial determinants of healthsocial risksVeterans

Identifiers

PMID39438381
PMCPMC12463771

What OpenQuestion holds

Textmetadata
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.