Evidence map›Paper›PMID 42506314›Full record

ArticleMedical sciences (Basel, Switzerland)2026

Trends in Co-Prescribing Opioids and Gabapentinoids Among Medicare Beneficiaries, 2017 to 2022.

Mukaila Raji, Aashnika Sujit, Jordan Westra, Shilpa Rajagopal, Yong-Fang Kuo

Abstract read
In one paragraph

Article in Medical sciences (Basel, Switzerland), 2026. 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

5 authors.

Mukaila RajiDivision of Geriatrics, Department of Internal Medicine, University of Texas Medical Branch (UTMB), Galveston, TX 77555, USA.ORCID 0000-0002-7460-7281
Aashnika SujitJohn Sealy School of Medicine, University of Texas Medical Branch (UTMB), Galveston, TX 77555, USA.
Jordan WestraDepartment of Epidemiology, School of Public and Population Health, University of Texas Medical Branch (UTMB), Galveston, TX 77555, USA.ORCID 0000-0002-1473-1766
Shilpa RajagopalJohn Sealy School of Medicine, University of Texas Medical Branch (UTMB), Galveston, TX 77555, USA.ORCID 0009-0002-9741-6768
Yong-Fang KuoDepartment of Biostatistics & Data Science, School of Public and Population Health, University of Texas Medical Branch (UTMB), Galveston, TX 77555, USA.ORCID 0000-0003-1927-0927

Funding

Pattern, Variation and Outcomes of Opioid Prescription in Older AdultsR01DA039192 · NIDA · UNIVERSITY OF TEXAS MED BR GALVESTON · PI KUO, YONG-FANG, RAJI, MUKAILA A · 2016 to 2023
$3.1M
NIDA NIH HHS 5R01DA039192-08NIDA NIH HHS R01 DA039192
6 · The paper itself

Abstract

backgroundCo-prescribing opioids and gabapentinoids (GABA, gabapentin and pregabalin) is associated with increased risk of falls, fractures, opioid overdose and deaths. The Centers for Disease Control and Prevention (CDC) in 2016 and the Food and Drug Administration (FDA) in 2019 recommended caution in such co-prescribing. A key step in updating policy and revising prescribing guidelines aimed at reducing opioid and GABA co-use and its associated consequences is a thorough understanding of the prescriber and the patient factors associated with co-use. We thus examined national trends and patterns in opioid and GABA co-prescribing among Medicare beneficiaries from 2017 to 2022.

methodsWe conducted a retrospective study of Medicare beneficiaries with ≥90 consecutive days of opioid use from 2017 to 2022. The study outcome was GABA use during the 90-day opioid use episode. A multivariable logistic regression model was constructed to examine the patient, prescriber and prescription factors associated with receiving a GABA prescription.

resultsOur sample comprised 8035 opioid-only and 2818 opioid and GABA users. Non-cancer (e.g., back and neuropathic) pain was a more common diagnosis in the opioid and GABA cohorts than in the opioid-only cohorts. The opioid-GABA co-prescribing rate did not substantially change (2017: 24.5%, 2019: 28.2% and 2022: 25%). Co-prescribing rates were higher in non-white patients, those on Medicaid and Medicare, and those whose initial Medicare entitlement was not based on age. Tramadol and hydrocodone were the most prescribed opioids. Approximately 33% of opioid and GABA users started with an initial daily GABA dose of ≥1200 mg. In the 12-month lookback period, patients on opioids and GABA had nearly 17 clinic visits to approximately 8 different providers. Factors associated with co-prescribing were seeing pain physicians (odds ratio = 1.29, 95% confidence interval-[CI] = 1.11-1.50), having more healthcare encounters (6-11 visits, odds ratio-[OR] = 1.19, 95% CI = 1.02-1.39; 12-19, OR = 1.20, 95% CI = 1.00-1.43; 20+, OR = 1.27, 95% CI = 1.03-1.57) and seeing >10 providers (OR = 1.40, 95% CI = 1.12-1.73).

conclusionsOne in four Medicare beneficiaries with long-term opioid use received opioid and GABA prescriptions. Our findings of association in co-prescribing with multiple visits to different clinics/prescribers can inform the development of public health policy and practice guidelines (e.g., prescription-drug monitoring program checks within electronic medical records, EMR alerts with opioid and GABA co-prescribing) to potentially reduce opioid and GABA prescriptions and associated adverse outcomes.

Indexed as

Analgesics, OpioidDrug PrescriptionsGabapentinPractice Patterns, Physicians'PregabalinAgedAged, 80 and overFemaleHumansMaleMedicareRetrospective StudiesUnited StatesAnalgesics, OpioidGabapentinPregabalinchronic painco-prescribinggabapentinoidsgeriatricslong-term opioid usemedicareolder adultsopioidsprescriptionstrends

Identifiers

PMID42506314
PMCPMC13413538

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.