Evidence map›Paper›PMID 36199698›Full record

ArticleSubstance abuse : research and treatment2022

Associations Between Copays, Coverage Limits for Naloxone, and Prescribing in Medicaid.

John C Messinger, Aaron S Kesselheim, Seanna M Vine, Michael A Fischer, Rachel E Barenie

Abstract read
In one paragraph

Article in Substance abuse : research and treatment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

John C MessingerHarvard Medical School, Boston, MA, USA.
Aaron S KesselheimHarvard Medical School, Boston, MA, USA.
Seanna M VineProgram on Regulation, Therapeutics, and Law (PORTAL), Boston, MA, USA.
Michael A FischerHarvard Medical School, Boston, MA, USA.
Rachel E BarenieProgram on Regulation, Therapeutics, and Law (PORTAL), Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: To describe naloxone dispensing in Medicaid fee-for-service (FFS) and examine relationships between copays and coverage limits for naloxone and its dispensing rates. Methods: Cross-sectional study using Medicaid FFS State Drug Utilization Data to quantify the use of naloxone in 2018. The primary outcomes of this study were the proportion of naloxone prescriptions relative to all prescriptions and all opioid prescriptions dispensed in each state. We obtained drug benefit design information from the Medicaid Behavioral Health Services Database. The primary analysis examined the influence of copays (yes/no), copay amounts, and coverage limits on medication dispensing using simple linear regression, excluding states with no measurable use or less than 5% Medicaid FFS. Results: We found substantial variability across 50 states and DC in the proportion of prescriptions dispensed for Narcan and generic naloxone. We found a positive relationship between copay and copay amount and dispensing of generic naloxone. However, a sensitivity analysis including the broadest possible cohort of states failed to confirm this relationship. We found no other relationships between copays or coverage limits and dispensing of any naloxone formulation. Conclusions: Substantial variation exists between the rates of naloxone dispensing across the US for Medicaid patients, but we did not find a meaningful relationship between plan design and dispensing. Whether drug benefit designs in Medicaid influence naloxone use requires further evaluation to avoid limiting access to this life-saving medication.

Indexed as

copaycoverage limitdispensingdrug benefit designMedicaidNaloxone

Identifiers

PMID36199698
PMCPMC9528040

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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 OpenQuestion graph.