Evidence map›Paper›PMID 38756241›Full record

ArticleHealth affairs scholar2023

Commercial coverage of specialty drugs, 2017-2021.

Julia A Rucker, Molly T Beinfeld, Nola B Jenkins, Daniel E Enright, Rochelle R Henderson, James D Chambers

Abstract read
In one paragraph

Article in Health affairs scholar, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. FDA approvals of specialty drugs, 2000-2024.Health affairs scholar · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. 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

6 authors.

Julia A RuckerTufts Medical Center, Center for the Evaluation of Value and Risk in Health, Boston, MA 02111, United States.ORCID https://orcid.org/0009-0003-5216-2968
Molly T BeinfeldTufts Medical Center, Center for the Evaluation of Value and Risk in Health, Boston, MA 02111, United States.
Nola B JenkinsTufts Medical Center, Center for the Evaluation of Value and Risk in Health, Boston, MA 02111, United States.ORCID https://orcid.org/0009-0000-1995-4910
Daniel E EnrightTufts Medical Center, Center for the Evaluation of Value and Risk in Health, Boston, MA 02111, United States.
Rochelle R HendersonNational Pharmaceutical Council, Washington, DC 20006, United States.
James D ChambersTufts Medical Center, Center for the Evaluation of Value and Risk in Health, Boston, MA 02111, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health plans guide their enrollees' access to specialty drugs through coverage policies. We examined a set of health plan policies to determine if they have become more or less stringent over time. We did so by comparing the consistency of policies with Food and Drug Administration (FDA) label indications. We considered coverage policies for the same 187 specialty drugs issued by 17 large US commercial health plans from 2017 through 2021. Overall, the proportion of policies that were consistent with the FDA label declined from 57.1% in 2017 to 45.1% in 2021; the proportion of policies that were more restrictive than the FDA label increased from 39.5% to 51.7%. The proportion of policies excluding drug coverage remained approximately constant (3.4% in 2017; 3.2% in 2021). Trends in coverage restrictiveness varied across plans. For 13 plans, the proportion of policies with restrictions increased over time, while for 4 plans it declined.

Indexed as

insurance coveragepharmaceuticalsspecialty drugs

Identifiers

PMID38756241
PMCPMC10986192

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.