Evidence map›Paper›PMID 31152355›Full record

ArticleJournal of medical toxicology : official journal of the American College of Medical Toxicology2019

Opioid Use Disorder and Prescribed Opioid Regimens: Evidence from Commercial and Medicaid Claims, 2005-2015.

Mir M Ali, Eli Cutler, Ryan Mutter, Rachel Mosher Henke, Peggy L O'Brien, Jesse M Pines, Maryann Mazer-Amirshahi, Jared Diou-Cass

Open access · bronzeAbstract read
In one paragraph

Article in Journal of medical toxicology : official journal of the American College of Medical Toxicology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 23% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Observational
  4. Article
  5. Prevalence and Expenses of Outpatient Opioid Prescriptions, With Associated Sociodemographic, Economic, and Work Characteristics.International journal of health services : planning, administration, evaluation · 2020
    Article
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

8 authors at 5 institutions in 1 country.

Mir M AliOffice of the Assistant Secretary for Planning & Evaluation, US Department of Health & Human Services, 200 Independence Avenue SW, Washington, DC, 20201, USA. ali.mir.m@gmail.com.ORCID 0000-0003-0597-6419
Eli CutlerQventus, Mountain View, CA, USA.
Ryan MutterHealth, Retirement and Long-Term Analysis Division, Congressional Budget Office, Washington, DC, USA.
Rachel Mosher HenkeIBM Watson Health, Cambridge, MA, USA.
Peggy L O'BrienIBM Watson Health, Cambridge, MA, USA.
Jesse M PinesUS Acute Care Solutions, Canton, OH, USA.
Maryann Mazer-AmirshahiMedStar Washington Hospital Center, Washington, DC, USA.
Jared Diou-CassTruven Health Analytics, an IBM company, San Jose, CA, USA.
IBM (United States) · USCongressional Budget Office · USMedStar Washington Hospital Center · USOffice of the Assistant Secretary for Planning and Evaluation · USTruven Health Analytics (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn response to the US opioid crisis, interventions are being implemented to lower opioid prescribing to reduce opioid misuse and overdose. As opioid prescribing falls, opioid misuse may shift from prescriptions to other, possibly illicit, sources. We examined how the percentage of patients with an opioid use disorder (OUD) diagnosis in a given year without a current opioid prescription changed over a decade among commercially insured enrollees and Medicaid beneficiaries. We also examined how the percentages differed by enrollee demographic factors.

methodsWe used commercial and Medicaid claims from the IBM MarketScan® databases from 2005 to 2015 to identify enrollees with and without current opioid prescriptions who have been diagnosed with OUD. We measured the percentage of enrollees with OUD without a current opioid prescription by year and demographic factors.

resultsWe identified 99,396 enrollee-years with OUD covered by commercial insurance and 60,492 enrollee-years with OUD covered by Medicaid. Among enrollees with OUD, the percentage without a current opioid prescription increased from 37% in 2005 to 49% in 2012 before falling back to 39% in 2015 in the commercial population, and increased from 32% in 2005 to 38% in 2015 in the Medicaid population. Differences in percentages were observed by age, sex, race, and region, particularly among young people where 70 to 89% had OUD without a current prescription.

conclusionsMost enrollees with OUD in the data had current opioid prescriptions, suggesting that continuing efforts to reduce misuse of prescribed opioids among patients with prescriptions may be effective. However, a substantial percentage of enrollees with OUD may be obtaining opioids via other, likely illegitimate, channels, particularly younger people, which suggests an opportunity for targeted efforts to reduce opioid diversion.

Indexed as

AdolescentAdultAge FactorsAnalgesics, OpioidChildDrug PrescriptionsFemaleHumansMaleMedicaidMiddle AgedOpioid-Related DisordersRetrospective StudiesTime FactorsUnited StatesYoung AdultAnalgesics, OpioidMedicaidOpioidOpioid use disorderPrivate insurance

Identifiers

PMID31152355
PMCPMC6597680
OpenAlexW2947368150

What OpenQuestion holds

Textmetadata
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.