Evidence map›Paper›PMID 38578818›Full record

ArticlePloS one2024

County-level factors associated with a mismatch between opioid overdose mortality and availability of opioid treatment facilities.

John G Rizk, Jannat Saini, Kyungha Kim, Uzma Pathan, Danya M Qato

Abstract read
In one paragraph

Article in PloS one, 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
–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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Dual-target mu opioid-dopamine DEuropean journal of medicinal chemistry · 2026
    Article
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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.

John G RizkDepartment of Practice, Sciences and Health Outcomes Research, University of Maryland School of Pharmacy, Baltimore, Maryland, United States of America.ORCID 0000-0002-5216-8695
Jannat SainiDepartment of Practice, Sciences and Health Outcomes Research, University of Maryland School of Pharmacy, Baltimore, Maryland, United States of America.ORCID 0000-0002-7693-7073
Kyungha KimDepartment of Practice, Sciences and Health Outcomes Research, University of Maryland School of Pharmacy, Baltimore, Maryland, United States of America.
Uzma PathanDepartment of Practice, Sciences and Health Outcomes Research, University of Maryland School of Pharmacy, Baltimore, Maryland, United States of America.
Danya M QatoDepartment of Practice, Sciences and Health Outcomes Research, University of Maryland School of Pharmacy, Baltimore, Maryland, United States of America.ORCID 0000-0002-6355-1526

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOpioid overdose deaths in the United States remain a major public health crisis. Little is known about counties with high rates of opioid overdose mortality but low availability of opioid use disorder (OUD) treatment facilities. We sought to identify characteristics of United States (US) counties with high rates of opioid overdose mortality and low rates of opioid treatment facilities.

methodsRates of overdose mortality from 3,130 US counties were compared with availability of opioid treatment facilities that prescribed or allowed medications for OUD (MOUD), from 2018-2019. The outcome variable, "risk-availability mismatch" county, was a binary indicator of a high rate (above national average) of opioid overdose mortality with a low (below national average) rate of opioid treatment facilities. Covariates of interest included county-level sociodemographics and rates of insurance, unemployment, educational attainment, poverty, urbanicity, opioid prescribing, depression, heart disease, Gini index, and Theil index. Multilevel logistic regression, accounting for the clustering of counties within states, was used to determine associations with being a "risk-availability mismatch" county.

resultsOf 3,130 counties, 1,203 (38.4%) had high rates of opioid overdose mortality. A total of 1,098 counties (35.1%) lacked a publicly-available opioid treatment facility in 2019. In the adjusted model, counties with an additional 1% of: white residents (odds ratio, OR, 1.02; 95% CI, 1.01-1.03), unemployment (OR, 1.11; 95% CI, 1.05-1.19), and residents without insurance (OR, 1.04; 95% CI, 1.01-1.08) had increased odds of being a mismatch county. Counties that were metropolitan (versus non-metropolitan) had an increased odds of being a mismatch county (OR, 1.85; 95% CI, 1.45-2.38).

conclusionAssessing mismatch between treatment availability and need provides useful information to characterize counties that require greater public health investment. Interventions to reduce overdose mortality are unlikely to be effective if they do not take into account diverse upstream factors, including sociodemographics, disease burden, and geographic context of communities.

Indexed as

Drug OverdoseOpiate OverdoseOpioid-Related DisordersAnalgesics, OpioidHumansPractice Patterns, Physicians'United StatesAnalgesics, Opioid

Identifiers

PMID38578818
PMCPMC10997118

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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.