Evidence map›Paper›PMID 37814576›Full record

ArticlePharmacoepidemiology and drug safety2024

An individual segmented trajectory approach for identifying opioid use patterns using longitudinal dispensing data.

Stanley Xu, Komal J Narwaney, Anh P Nguyen, Ingrid A Binswanger, David L McClure, Jason M Glanz

Open access · greenAbstract read
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
–field-weighted citation impact, top 76% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Stanley XuDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.ORCID 0000-0002-4750-7672
Komal J NarwaneyInstitute for Health Research, Kaiser Permanente Colorado, Aurora, Colorado, USA.
Anh P NguyenInstitute for Health Research, Kaiser Permanente Colorado, Aurora, Colorado, USA.
Ingrid A BinswangerDepartment of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, USA.
David L McClureCenter for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA.
Jason M GlanzInstitute for Health Research, Kaiser Permanente Colorado, Aurora, Colorado, USA.
Kaiser Permanente · USMarshfield Clinic · US

Funding

Assessing the Safety and Effectiveness of Opioid Tapering in Large Health SystemsR01DA047537 · NIDA · KAISER FOUNDATION RESEARCH INSTITUTE · PI BINSWANGER, INGRID A, GLANZ, JASON M · 2019 to 2022
$2.6M
NIDA NIH HHS R01 DA047537
6 · The paper itself

Abstract

purposeThe aim of this study is to use electronic opioid dispensing data to develop an individual segmented trajectory approach for identifying opioid use patterns. The resulting opioid use patterns can be used for examining the association between opioid use and drug overdose.

methodsWe retrospectively assembled a cohort of members on long-term opioid therapy (LTOT) between January 1, 2006 and June 30, 2019 who were 18 years and older and enrolled in one of three health care systems in the US. We have developed an individual segmented trajectory analysis for identifying various opioid use patterns by scanning over the follow-up and finding distinct opioid use patterns based on variability measured with coefficient of variation and trends of milligram morphine equivalents levels.

resultsAmong 31, 865 members who were on LTOT between January 1, 2006 and June 30, 2019, 58.3% were female, and the average age was 55.4 years (STD = 15.4). The study population had 152 557 person-years of follow-up, with an average follow-up of 4.4 years per enrollment per person (STD = 3.4). This novel approach identified up to 13 distinct patterns including 88 756 episodes of "stable" pattern (42.1%) with an average follow-up of 11.2 months, 29 140 episodes of "increasing" pattern (13.8%) with an average follow-up of 6.0 months, 13 201 episodes of ≤10% dose reduction (6.3%) with an average follow-up of 10.4 months, 7286 episodes of 11%-20% dose reduction (3.5%) with an average follow-up of 5.3 months, 4457 episodes of 21%-30% dose reduction (2.1%) with an average follow-up of 4.0 months, and 9903 episodes of >30% dose reduction (4.7%) with an average follow-up of 2.6 months.

conclusionsA novel approach was developed to identify 13 distinct opioid use patterns using each individual's longitudinal dispensing data and these patterns can be used in examining overdose risk during the time that these patterns are ongoing.

Indexed as

Drug OverdoseOpioid-Related DisordersAnalgesics, OpioidFemaleHumansMaleMiddle AgedPractice Patterns, Physicians'Retrospective StudiesAnalgesics, Opioidcoefficient of variationdose reductionindividual segmented trajectorylong-term opioid therapyopioid prescriptionoverdose

Identifiers

PMID37814576
PMCPMC10841826
OpenAlexW4387472671

What Socratic holds

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Registered trials

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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 Socratic graph.