Evidence map›Paper›PMID 41125156›Full record

ArticleJournal of substance use and addiction treatment2026

Developing and validating measures of take-home methadone with administrative data.

Shashi N Kapadia, Kenneth Karan, Hao Zhang, Promi Chakraborty, Noa Krawczyk, Yuhua Bao

Abstract readValidation Study
In one paragraph

Article in Journal of substance use and addiction treatment, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

6 authors.

Shashi N KapadiaDepartment of Medicine, Weill Cornell Medicine, New York, NY, 10021, USA; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, 10065, USA. Electronic address: shk9078@med.cornell.edu.
Kenneth KaranDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, 10065, USA.
Hao ZhangDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, 10065, USA; Department of Health Policy and Organization, University of Alabama at Birmingham, Birmingham, AL, 35294, USA.
Promi ChakrabortyDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, 10065, USA; Sophie Davis Biomedical Education Program, CUNY School of Medicine, New York, NY, 10031, USA.
Noa KrawczykDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, 10016, USA.
Yuhua BaoDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, 10065, USA.

Funding

HEAL Data2Action Modeling and Economic Resource CenterU24DA057650 · NIDA · WEILL MEDICAL COLL OF CORNELL UNIV · PI Benjamin P. Linas, KATHRYN E MCCOLLISTER · 2022 to 2026
$8.1M
Integrated Care for Hepatitis C: Current Uptake & Impact on Future TreatmentK01DA048172 · NIDA · WEILL MEDICAL COLL OF CORNELL UNIV · PI KAPADIA, SHASHI · 2019 to 2023
$948k
Beyond Treatment Initiation: Enhancing Opioid Use Disorder Care Transitions Across Health System TouchpointsK01DA055758 · NIDA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Noa Krawczyk · 2023 to 2026
$722k
NIDA NIH HHS K01 DA048172NIDA NIH HHS K01 DA055758NIDA NIH HHS U24 DA057650
6 · The paper itself

Abstract

backgroundTake-home methadone (THM) flexibility has increased since 2020, representing innovation in opioid use disorder treatment. There are no established approaches to measuring THM using insurance claims data. We proposed and validated candidate measures of THM.

methodsUsing 2020 Medicaid data from 4 states, we constructed treatment episodes for enrollees aged 18-64. Episodes started after July 1, 2020 and lasted at least 60 days. We labelled individuals as receiving THM if they received ≥6 consecutive days of THM in their 2nd month of treatment, as defined by presence of claims with a modifier code indicating THM (the "gold-standard" indicator). We defined 4 candidate indicators of THM based on intervals between in-clinic methadone administrations. We assessed performance of each candidate indicator against the gold-standard. We assessed the extent to which between-program variation explained total variation in measured THM.

resultsThe study sample included 4836 episodes for 4801 individuals. THM was present in 14 % of episodes. Sensitivity of candidate indicators ranged from 65 to 100 %, with the most sensitive being an indicator that was true if any two adjacent in-clinic service dates had a gap of ≥7 days. Specificity ranged from 80 to 96 %, with the most specific measure being one requiring 2 consecutive intervals of ≥7 days that were of the same length. Between-program variation explained 38.6-48.3 % of variation in THM receipt.

conclusionsTwo indicators of THM using Medicaid data presented excellent performance when evaluated against a gold-standard indicator. Our approach can be used to assess uptake and outcomes of THM.

Indexed as

Analgesics, OpioidMethadoneOpiate Substitution TreatmentOpioid-Related DisordersAdolescentAdultFemaleHumansMaleMedicaidMiddle AgedUnited StatesYoung AdultAnalgesics, OpioidMethadoneadministrative datahealth servicesMedicaidmethadoneopioid use disordertake-home

Identifiers

PMID41125156
PMCPMC12755281

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LicenceCC BY-NC-ND
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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.