Evidence map›Paper›PMID 35089351›Full record

Observational studyJAMA network open2022

Factors Associated With Opioid Overdose After an Initial Opioid Prescription.

Scott G Weiner, Sanae El Ibrahimi, Michelle A Hendricks, Sara E Hallvik, Christi Hildebran, Michael A Fischer, Roger D Weiss, Edward W Boyer, Peter W Kreiner, Dagan A Wright and 2 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 3 pooled it
11.4field-weighted citation impact, top 1% 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

36 citing papers in PubMed, 3 syntheses or guidelines pooled it, 58 citations in OpenAlex.

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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

12 authors at 6 institutions in 1 country.

Scott G WeinerDepartment of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Sanae El IbrahimiDivision of Research and Evaluation, Comagine Health, Portland, Oregon.
Michelle A HendricksDivision of Research and Evaluation, Comagine Health, Portland, Oregon.
Sara E HallvikDivision of Research and Evaluation, Comagine Health, Portland, Oregon.
Christi HildebranDivision of Research and Evaluation, Comagine Health, Portland, Oregon.
Michael A FischerSection of General Internal Medicine, Boston Medical Center, Boston University School of Medicine, Boston, Massachusetts.
Roger D WeissHarvard Medical School, Boston, Massachusetts.
Edward W BoyerDepartment of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Peter W KreinerSchneider Institutes for Health Policy, Heller School for Social Policy and Management, Brandeis University, Waltham, Massachusetts.
Dagan A WrightOCHIN Inc, Portland, Oregon.
Diana P FloresDivision of Research and Evaluation, Comagine Health, Portland, Oregon.
Grant A RitterSchneider Institutes for Health Policy, Heller School for Social Policy and Management, Brandeis University, Waltham, Massachusetts.
Brandeis University · USBrigham and Women's Hospital · USBoston University · USMcLean Hospital · USOchin · USUniversity of Nevada, Las Vegas · US

Funding

Using a Novel Comprehensive Linked Dataset to Determine Early Predictors of Opioid OverdoseR01DA044167 · NIDA · BRIGHAM AND WOMEN'S HOSPITAL · PI WEINER, SCOTT GORDON · 2018 to 2022
$2.6M
NIDA National Early Warning System Network (iN3): An Innovative ApproachR56DA038366 · NIDA · WRIGHT STATE UNIVERSITY · PI BOYER, EDWARD W, CARLSON, ROBERT GEOFFREY · 2014 to 2014
$300k
NIDA NIH HHS R01 DA044167NIDA NIH HHS R56 DA038366
6 · The paper itself

Abstract

Importance: The opioid epidemic continues to be a public health crisis in the US. Objective: To assess the patient factors and early time-varying prescription-related factors associated with opioid-related fatal or nonfatal overdose. Design, Setting, and Participants: This cohort study evaluated opioid-naive adult patients in Oregon using data from the Oregon Comprehensive Opioid Risk Registry, which links all payer claims data to other health data sets in the state of Oregon. The observational, population-based sample filled a first (index) opioid prescription in 2015 and was followed up until December 31, 2018. Data analyses were performed from March 1, 2020, to June 15, 2021. Exposures: Overdose after the index opioid prescription. Main Outcomes and Measures: The outcome was an overdose event. The sample was followed up to identify fatal or nonfatal opioid overdoses. Patient and prescription characteristics were identified. Prescription characteristics in the first 6 months after the index prescription were modeled as cumulative, time-dependent measures that were updated monthly through the sixth month of follow-up. A time-dependent Cox proportional hazards regression model was used to assess patient and prescription characteristics that were associated with an increased risk for overdose events. Results: The cohort comprised 236 921 patients (133 839 women [56.5%]), of whom 667 (0.3%) experienced opioid overdose. Risk of overdose was highest among individuals 75 years or older (adjusted hazard ratio [aHR], 3.22; 95% CI, 1.94-5.36) compared with those aged 35 to 44 years; men (aHR, 1.29; 95% CI, 1.10-1.51); those who were dually eligible for Medicaid and Medicare Advantage (aHR, 4.37; 95% CI, 3.09-6.18), had Medicaid (aHR, 3.77; 95% CI, 2.97-4.80), or had Medicare Advantage (aHR, 2.18; 95% CI, 1.44-3.31) compared with those with commercial insurance; those with comorbid substance use disorder (aHR, 2.74; 95% CI, 2.15-3.50), with depression (aHR, 1.26; 95% CI, 1.03-1.55), or with 1 to 2 comorbidities (aHR, 1.32; 95% CI, 1.08-1.62) or 3 or more comorbidities (aHR, 1.90; 95% CI, 1.42-2.53) compared with none. Patients were at an increased overdose risk if they filled oxycodone (aHR, 1.70; 95% CI, 1.04-2.77) or tramadol (aHR, 2.80; 95% CI, 1.34-5.84) compared with codeine; used benzodiazepines (aHR, 1.06; 95% CI, 1.01-1.11); used concurrent opioids and benzodiazepines (aHR, 2.11; 95% CI, 1.70-2.62); or filled opioids from 3 or more pharmacies over 6 months (aHR, 1.38; 95% CI, 1.09-1.75). Conclusions and Relevance: This cohort study used a comprehensive data set to identify patient and prescription-related risk factors that were associated with opioid overdose. These findings may guide opioid counseling and monitoring, the development of clinical decision-making tools, and opioid prevention and treatment resources for individuals who are at greatest risk for opioid overdose.

Indexed as

AdultAgedAnalgesics, OpioidDrug PrescriptionsFemaleHumansMaleMiddle AgedOpiate OverdoseOregonProportional Hazards ModelsRegistriesRisk FactorsAnalgesics, Opioid

Identifiers

PMID35089351
PMCPMC8800077
OpenAlexW4210724292

What OpenQuestion holds

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LicenceCC BY
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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.