Evidence map›Paper›PMID 29410132›Full record

ArticlePreventive medicine2018

Use of a prescription opioid registry to examine opioid misuse and overdose in an integrated health system.

Cynthia I Campbell, Amber L Bahorik, Paul VanVeldhuisen, Constance Weisner, Andrea L Rubinstein, G Thomas Ray

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Preventive medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 2 pooled it
8.7field-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

36 citing papers in PubMed, 2 syntheses or guidelines pooled it, 61 citations in OpenAlex.

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  19. Assessing opioid overdose risk: a review of clinical prediction models utilizing patient-level data.Translational research : the journal of laboratory and clinical medicine · 2021
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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

6 authors at 4 institutions in 1 country.

Cynthia I CampbellDivision of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, USA; Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, 401 Parnassus, Box 0984, San Francisco 94143, USA. Electronic address: cynthia.i.campbell@kp.org.
Amber L BahorikDepartment of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, 401 Parnassus, Box 0984, San Francisco 94143, USA.
Paul VanVeldhuisenThe Emmes Corporation, Rockville, 401 North Washington Street, Suite 700, Rockville, MD 20850, USA.
Constance WeisnerDivision of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, USA; Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, 401 Parnassus, Box 0984, San Francisco 94143, USA.
Andrea L RubinsteinKaiser Permanente Santa Rosa Medical Center, Department of Anesthesiology, 3925 Old Redwood Hwy, Santa Rosa, CA 95403, USA.
G Thomas RayDivision of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, USA.
Kaiser Permanente · USUniversity of California, San Francisco · USEmmes (United States) · USKaiser Permanente Santa Rosa Medical Center · US

Funding

Project-002UG1DA040314 · NIDA · KAISER FOUNDATION RESEARCH INSTITUTE · PI Ingrid A Binswanger, CYNTHIA I CAMPBELL · 2015 to 2026
$34.9M
NIDA NIH HHS UG1 DA040314
6 · The paper itself

Abstract

Strategies are needed to identify at-risk patients for adverse events associated with prescription opioids. This study identified prescription opioid misuse in an integrated health system using electronic health record (EHR) data, and examined predictors of misuse and overdose. The sample included patients from an EHR-based registry of adults who used prescription opioids in 2011 in Kaiser Permanente Northern California, a large integrated health care system. We characterized time-at-risk for opioid misuse and overdose, and used Cox proportional hazard models to model predictors of these events from 2011 to 2014. Among 396,452 patients, 2.7% were identified with opioid misuse and 1044 had an overdose event. Older patients were less likely to meet misuse criteria or have an overdose. Whites were more likely to be identified with misuse, but not to have an overdose. Alcohol and drug disorders were related to higher risk of misuse and overdose, with the exception that marijuana disorder was not related to opioid misuse. Higher daily opioid dosages and benzodiazepine use increased the risk of both opioid misuse and overdose. We characterized several risk factors associated with misuse and overdose using EHR-based data, which can be leveraged relatively quickly to inform preventive strategies to address the opioid crisis.

Indexed as

Drug OverdosePrescription Drug MisuseRegistriesAdultAgedAged, 80 and overAnalgesics, OpioidCaliforniaElectronic Health RecordsFemaleHumansMaleMiddle AgedOpioid-Related DisordersRisk FactorsAnalgesics, OpioidElectronic health recordOpioid misuseOpioid overdoseRegistry

Identifiers

PMID29410132
PMCPMC6034705
OpenAlexW2794369775

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.