Evidence map›Paper›PMID 30469100›Full record

ArticleDrug and alcohol dependence2019

Influence of comorbid drug use disorder on receipt of evidence-based treatment for alcohol use disorder among VA patients with alcohol use disorder and Hepatitis C and/or HIV.

Madeline C Frost, Theresa E Matson, Judith I Tsui, Emily C Williams

Abstract read
In one paragraph

Article in Drug and alcohol dependence, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
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

6 citing papers in PubMed, 10 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Madeline C FrostHealth Services Research and Development (HSR&D) Center of Innovation for Veteran-Centered and Value-Driven Care, Veterans Affairs (VA) Puget Sound Health Care System, 1660 South Columbian Way, Seattle, WA, 98108, United States. Electronic address: Madeline.Frost@va.gov.
Theresa E MatsonHealth Services Research and Development (HSR&D) Center of Innovation for Veteran-Centered and Value-Driven Care, Veterans Affairs (VA) Puget Sound Health Care System, 1660 South Columbian Way, Seattle, WA, 98108, United States; Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave, Seattle, WA, 98101, United States. Electronic address: Tessa.E.Matson@kp.org.
Judith I TsuiDepartment of Medicine, University of Washington School of Medicine, 1959 NE Pacific St, Seattle, WA, 98195, United States. Electronic address: tsuij@uw.edu.
Emily C WilliamsHealth Services Research and Development (HSR&D) Center of Innovation for Veteran-Centered and Value-Driven Care, Veterans Affairs (VA) Puget Sound Health Care System, 1660 South Columbian Way, Seattle, WA, 98108, United States; Department of Health Services, University of Washington School of Public Health, 1959 NE Pacific St, Seattle, WA, 98195, United States. Electronic address: Emily.Williams3@va.gov.
University of Washington · USVA Puget Sound Health Care System · US

Funding

Alcohol-related Care & Outcomes for Outpatients with HIV in a National VA CohortR21AA022866 · NIAAA · KAISER FOUNDATION HEALTH PLAN OF WASHINGTON · PI BRADLEY, KATHARINE ANTHONY, WILLIAMS, EMILY CATERINA · 2015 to 2016
$434k
Implementation Research for Evidence-based Care for Alcohol DependenceIK2HX001161 · VA · VA PUGET SOUND HEALTHCARE SYSTEM · PI WILLIAMS, EMILY CATERINA · 2015 to 2015
–
HSRD VA IK2 HX001161NIAAA NIH HHS R21 AA022866
6 · The paper itself

Abstract

backgroundAlcohol use is risky for patients with hepatitis C virus (HCV) and/or human immunodeficiency virus (HIV) infection, but alcohol use disorder (AUD) treatment is underutilized in these populations. Comorbid drug use disorders (DUD) are common, but their influence on AUD treatment receipt is understudied. We evaluated the association between DUD and AUD treatment receipt in two national samples of patients with AUD, those with HIV and those with HCV, in the U.S. Veterans Health Administration.

methodsSamples included patients with AUD and HCV and/or HIV among positive alcohol screens (AUDIT-C≥5) documented 10/01/09-5/30/13 in the national electronic health record. Poisson regression models estimated incidence rate ratios for receiving specialty treatment (stop codes) and pharmacotherapy (filled prescription for naltrexone, disulfiram, acamprosate, or topiramate) within 365 days of positive alcohol screening for patients with DUD versus those without. Models were clustered on patient and adjusted for potential confounders.

resultsAmong 22,039 patients with HCV/AUD, 45.2% (N = 9,964) had DUD, which was associated with receiving specialty treatment [adjusted incidence rate ratio: 1.89 (95% confidence interval 1.82-1.96)] and pharmacotherapy [aIRR: 1.50 (1.37-1.65)]. Among 1,834 patients with HIV/AUD, 56.9% (N = 1,043) had DUD, which was associated with receiving specialty treatment [aIRR: 1.94 (1.68-2.24)], but not pharmacotherapy.

conclusionsRates of AUD treatment receipt among patients with AUD and HCV and/or HIV were low overall, but likelihood of treatment receipt was generally higher among those with comorbid DUD. Future research should investigate mechanisms underlying these associations, such as enhanced readiness for treatment or differential provider prescribing or referral practices.

Indexed as

AdolescentAdultAgedAged, 80 and overAlcoholismEvidence-Based MedicineFemaleHepatitis CHIV InfectionsHospitals, VeteransHumansMaleMiddle AgedSocioeconomic FactorsSubstance-Related DisordersTreatment OutcomeAlcoholAlcohol use disorderComorbidityHCVHIVTreatment

Identifiers

PMID30469100
PMCPMC6312483
OpenAlexW2898907240

What OpenQuestion holds

Textmetadata
LicenceTDM
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.