Evidence map›Paper›PMID 37351873›Full record

ArticleJAMA health forum2023

State- and County-Level Geographic Variation in Opioid Use Disorder, Medication Treatment, and Opioid-Related Overdose Among Medicaid Enrollees.

Stephan R Lindner, Kyle Hart, Brynna Manibusan, Dennis McCarty, K John McConnell

Open access · goldAbstract read
In one paragraph

Article in JAMA health forum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
7.5field-weighted citation impact, top 2% 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

25 citing papers in PubMed, 26 citations in OpenAlex.

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  8. Spatio-Temporal Modeling for Multi-County Opioid Overdose Surveillance: A Unified Graph Convolutional Framework.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026
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  16. Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.IEEE journal of biomedical and health informatics · 2025
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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

5 authors at 2 institutions in 1 country.

Stephan R LindnerCenter for Health Systems Effectiveness, Oregon Health & Science University (OHSU), Portland.
Kyle HartCenter for Health Systems Effectiveness, Oregon Health & Science University (OHSU), Portland.
Brynna ManibusanCenter for Health Systems Effectiveness, Oregon Health & Science University (OHSU), Portland.
Dennis McCartyOHSU-Portland State University School of Public Health, Portland.
K John McConnellCenter for Health Systems Effectiveness, Oregon Health & Science University (OHSU), Portland.
Oregon Health & Science University · USPortland State University · US

Funding

The Effects of States' Substance Use Waivers on Healthcare Utilization and Opioid-related Overdoses Among Medicaid Enrollees with Opioid Use DisorderR01DA052388 · NIDA · OREGON HEALTH & SCIENCE UNIVERSITY · PI LINDNER, STEPHAN REINHARD · 2021 to 2024
$2.5M
NIDA NIH HHS R01 DA052388
6 · The paper itself

Abstract

Importance: The opioid crisis disproportionately affects Medicaid enrollees, yet little systematic evidence exists regarding how prevalence of and health care utilization for opioid use disorder (OUD) vary across geographical areas. Objectives: To characterize state- and county-level variation in claims-based prevalence of OUD and rates of medication treatment for OUD and OUD-related nonfatal overdose among Medicaid enrollees. Design, Setting, and Participants: This cross-sectional study used data from the Transformed Medicaid Statistical Information System Analytic Files from January 1, 2016, to December 31, 2018. Participants were Medicaid enrollees with or without OUD in 46 states; Washington, DC; and Puerto Rico who were aged 18 to 64 years and not dually enrolled in Medicare. The analysis was conducted between September 2022 and April 2023. Exposure: Calendar-year OUD prevalence. Main Outcomes and Measures: The main outcomes were claims-based measures of OUD prevalence and rates of medication treatment for OUD and opioid-related nonfatal overdose. Individual records were aggregated at the state and county level, and variation was assessed within and across states. Results: Of the 76 390 817 Medicaid enrollee-year observations included in our study (mean [SD] enrollee age, 36.5 [1.6] years; 59.0% female), 2 280 272 (3.0%) had a claims-based OUD (mean [SD] age, 38.9 [3.6] years; 51.4% female). Of enrollees with OUD, 41.2% were eligible due to Medicaid expansion, 46.4% had other substance use disorders, 55.8% had mental health conditions, 55.2% had claims indicating some form of OUD medication, and 5.8% had claims indicating an overdose during a calendar year. Claims-based outcomes exhibited substantial variation across states: OUD prevalence ranged from 0.6% in Arkansas and Puerto Rico to 9.7% in Maryland, rates of OUD medication treatment ranged from 17.7% in Kansas to 82.8% in Maine, and rates of overdose ranged from 0.3% in Mississippi to 10.5% in Illinois. Pronounced variation was also found within states (eg, OUD prevalence in Maryland ranged from 2.2% in Prince George's County to 21.6% in Cecil County). Conclusions and Relevance: In this cross-sectional study of Medicaid enrollees from 2016 to 2018, claims-based prevalence of OUD and rates of OUD medication treatment and opioid-related overdose varied substantially across and within states. Further research appears to be needed to identify important factors influencing this variation.

Indexed as

Drug OverdoseOpiate OverdoseOpioid-Related DisordersAdultAgedAnalgesics, OpioidCross-Sectional StudiesFemaleHumansMaleMedicaidMedicareUnited StatesAnalgesics, Opioid

Identifiers

PMID37351873
PMCPMC10290243
OpenAlexW4381715845

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.