Evidence map›Paper›PMID 39774411›Full record

ArticleEpidemiology (Cambridge, Mass.)2025

Rates of Receiving Medication for Opioid Use Disorder and Opioid Overdose Deaths During the Early Synthetic Opioid Crisis: A County-level Analysis.

Julian Santaella-Tenorio, Ariadne Rivera-Aguirre, Staci A Hepler, David M Kline, Jonathan Cantor, Maria DeYoreo, Silvia S Martins, Noa Krawczyk, Magdalena Cerda

Abstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

9 authors.

Julian Santaella-TenorioFrom the Department of Population Health, Center for Opioid Epidemiology and Policy, NYU Grossman School of Medicine, NY.ORCID 0000-0003-3060-5994
Ariadne Rivera-AguirreFrom the Department of Population Health, Center for Opioid Epidemiology and Policy, NYU Grossman School of Medicine, NY.
Staci A HeplerDepartment of Statistical Sciences, Wake Forest University, Winston-Salem, NC.
David M KlineDepartment of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC.
Jonathan CantorRAND Corporation, Santa Monica, CA.
Maria DeYoreoRAND Corporation, Santa Monica, CA.
Silvia S MartinsDepartment of Epidemiology, Columbia University, NY.
Noa KrawczykFrom the Department of Population Health, Center for Opioid Epidemiology and Policy, NYU Grossman School of Medicine, NY.
Magdalena CerdaFrom the Department of Population Health, Center for Opioid Epidemiology and Policy, NYU Grossman School of Medicine, NY.

Funding

Examining the Synergistic Effects of Cannabis and Prescription Opioid Policies on Chronic Pain, Opioid Prescribing, and Opioid OverdoseR01DA045872 · NIDA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CERDA, MAGDALENA, MARTINS, SILVIA SABOIA · 2019 to 2023
$4.3M
Spatio-temporal Methods for Surveillance of the Opioid SyndemicR01DA052214 · NIDA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI HEPLER, STACI, KLINE, DAVID M · 2021 to 2025
$3.7M
NIDA NIH HHS R01 DA045872NIDA NIH HHS R01 DA052214
6 · The paper itself

Abstract

backgroundMedications for opioid use disorder are associated with a lower risk of drug overdoses at the individual level. However, little is known about whether these effects translate to population-level reductions. We investigated whether county-level efforts to increase access to medication for opioid use disorder in 2012-2014 were associated with opioid overdose deaths in New York State during the first years of the synthetic opioid crisis.

methodsWe performed an ecologic county-level study including data from 60 counties (2010-2018). We calculated rates of people receiving medication for opioid use disorder among the population misusing opioids in 2012-2014 and categorized counties into quartiles of this exposure. We modeled synthetic and nonsynthetic opioid overdose death rates using Bayesian hierarchical models.

resultsCounties with higher rates of receiving medications for opioid use disorder in 2012-2014 had lower synthetic opioid overdose deaths in 2016 (highest vs. lowest quartile: rate ratio [RR] = 0.33, 95% credible interval [CrI] = 0.12, 0.98; and second-highest vs. lowest: RR = 0.20, 95% CrI = 0.07, 0.59) and 2017 (quartile second-highest vs. lowest: RR = 0.22, 95% CrI = 0.06, 0.83), but not 2018. There were no differences in nonsynthetic opioid overdose death rates comparing higher quartiles versus lowest quartile of exposure.

conclusionsA spatio-temporal modeling approach incorporating counts of the population misusing opioids provided information about trends and interventions in the target population. Higher rates of receiving medications for opioid use disorder in 2012-2014 were associated with lower rates of synthetic opioid overdose deaths early in the crisis.

Indexed as

Analgesics, OpioidDrug OverdoseOpiate OverdoseOpioid EpidemicOpioid-Related DisordersAdultBayes TheoremFemaleHumansMaleNew YorkAnalgesics, Opioid

Identifiers

PMID39774411
PMCPMC11785500

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.