Evidence map›Paper›PMID 38419116›Full record

ArticleAddiction science & clinical practice2024

Tools to implement measurement-based care (MBC) in the treatment of opioid use disorder (OUD): toward a consensus.

A John Rush, Robert E Gore-Langton, Gavin Bart, Katharine A Bradley, Cynthia I Campbell, James McKay, David W Oslin, Andrew J Saxon, T John Winhusen, Li-Tzy Wu and 2 more

Open access · goldAbstract read
In one paragraph

Article in Addiction science & clinical practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.2field-weighted citation impact, top 14% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Trial
  2. Article
  3. 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

12 authors at 11 institutions in 2 countries.

A John RushDuke-NUS Medical School, The National University of Singapore, Duke University School of Medicine, Singapore, Singapore.
Robert E Gore-LangtonThe Emmes Company, Rockville, MD, USA.
Gavin BartSchool of Medicine & Division of Medicine at Hennepin Healthcare, University of Minnesota, Minneapolis, MN, USA.
Katharine A BradleyKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Cynthia I CampbellKaiser Permanente Northern California Division of Research, Oakland, CA, USA.
James McKayPenn Center on the Continuum of Care in the Addictions, Philadelphia VA Center of Excellence in Substance Addiction Treatment and Education, University of Pennsylvania, Philadelphia, PA, USA.
David W OslinUniversity of Psychiatry, VISN 4 Mental Illness, Research, Education and Clinical Center Crescenz VA Medical Center, Stephen A. Cohen Military Family Clinic at the Perelman School of Medicine, Philadelphia, PA, USA.
Andrew J SaxonUniversity of Washington and Center of Excellence in Substance Addiction Treatment and Education at the VA Puget Sound Health Care System, Seattle, WA, USA.
T John WinhusenAddiction Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Li-Tzy WuDuke University School of Medicine, Durham, NC, USA.
Landhing M MoranCenter for Clinical Trials Network, National Institute on Drug Abuse, Bethesda, MD, USA.
Betty TaiCenter for Clinical Trials Network, National Institute on Drug Abuse, National Institutes of Health, 11601 Landsdown Street (3WF), Bethesda, MD, 20892, USA. btai@nih.gov.ORCID 0000-0002-7163-9763
Duke University · USEmmes (United States) · USKaiser Permanente · USKaiser Permanente Washington Health Research Institute · USNational Institute on Drug Abuse · USNational Institutes of Health · USNational University of Singapore · SGUniversity of Cincinnati Medical Center · USUniversity of Minnesota · USUniversity of Pennsylvania · USUniversity of Washington · US

Funding

Clinical Trials Network, Ohio Valley Node U10DA013732U10DA013732 · NIDA · UNIVERSITY OF CINCINNATI · PI WINHUSEN, T JOHN · 2000 to 2015
$45.0M
Project-002UG1DA040314 · NIDA · KAISER FOUNDATION RESEARCH INSTITUTE · PI Ingrid A Binswanger, CYNTHIA I CAMPBELL · 2015 to 2026
$34.9M
Clinical Trials Network: Pacific Northwest Node (CTN-0082, -0131, -0139 and dissemination library)UG1DA013714 · NIDA · UNIVERSITY OF WASHINGTON · PI Mary Akiko Hatch, John M. Roll · 2015 to 2026
$19.8M
NIDA NIH HHS U10 DA013732NIDA NIH HHS UG1 DA013714NIDA NIH HHS UG1 DA040314
6 · The paper itself

Abstract

backgroundThe prevalence and associated overdose death rates from opioid use disorder (OUD) have dramatically increased in the last decade. Despite more available treatments than 20 years ago, treatment access and high discontinuation rates are challenges, as are personalized medication dosing and making timely treatment changes when treatments fail. In other fields such as depression, brief measures to address these tasks combined with an action plan-so-called measurement-based care (MBC)-have been associated with better outcomes. This workgroup aimed to determine whether brief measures can be identified for using MBC for optimizing dosing or informing treatment decisions in OUD.

methodsThe National Institute on Drug Abuse Center for the Clinical Trials Network (NIDA CCTN) in 2022 convened a small workgroup to develop consensus about clinically usable measures to improve the quality of treatment delivery with MBC methods for OUD. Two clinical tasks were addressed: (1) to identify the optimal dose of medications for OUD for each patient and (2) to estimate the effectiveness of a treatment for a particular patient once implemented, in a more granular fashion than the binary categories of early or sustained remission or no remission found in The Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5). DISCUSSION: Five parameters were recommended to personalize medication dose adjustment: withdrawal symptoms, opioid use, magnitude (severity and duration) of the subjective effects when opioids are used, craving, and side effects. A brief rating of each OUD-specific parameter to adjust dosing and a global assessment or verbal question for side-effects was viewed as sufficient. Whether these ratings produce better outcomes (e.g., treatment engagement and retention) in practice deserves study. There was consensus that core signs and symptoms of OUD based on some of the 5 DSM-5 domains (e.g., craving, withdrawal) should be the basis for assessing treatment outcome. No existing brief measure was found to meet all the consensus recommendations. Next steps would be to select, adapt or develop de novo items/brief scales to inform clinical decision-making about dose and treatment effectiveness. Psychometric testing, assessment of acceptability and whether the use of such scales produces better symptom control, quality of life (QoL), daily function or better prognosis as compared to treatment as usual deserves investigation.

Indexed as

Opioid-Related DisordersQuality of LifeAnalgesics, OpioidConsensusHumansOpiate Substitution TreatmentAnalgesics, OpioidAddictionDrugEpidemicMeasurement-based careOpioid use disorderOverdose

Identifiers

PMID38419116
PMCPMC10902994
OpenAlexW4392240751

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.