Evidence map›Paper›PMID 41114975›Full record

ArticleJAMA network open2025

Medicare Part D Use and Costs for Immune-Mediated Neurologic Therapies.

Ka-Ho Wong, Esther Zeng, Tammy L Smith, Jordan B King, Erica Marini, Abigail Sorenson, Heewon Hwang, Chloe Stein, Trieste Francis, John W Rose and 3 more

Abstract read
In one paragraph

Article in JAMA network open, 2025. 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

13 authors.

Ka-Ho WongDepartment of Neurology, University of Utah School of Medicine, Salt Lake City.
Esther ZengDepartment of Undergraduate Studies, University of California, Berkeley.
Tammy L SmithDepartment of Neurology, University of Utah School of Medicine, Salt Lake City.
Jordan B KingDepartment of Population Health Science, University of Utah School of Medicine, Salt Lake City.
Erica MariniUniversity of Utah School of Pharmacy, Salt Lake City.
Abigail SorensonDepartment of Undergraduate Studies, University of California, Berkeley.
Heewon HwangDepartment of Neurology, University of Utah School of Medicine, Salt Lake City.
Chloe SteinDepartment of Neurology, University of Utah School of Medicine, Salt Lake City.
Trieste FrancisDepartment of Neurology, University of Utah School of Medicine, Salt Lake City.
John W RoseDepartment of Neurology, University of Utah School of Medicine, Salt Lake City.
Vivek K ReddyDepartment of Neurology, University of Utah School of Medicine, Salt Lake City.
Adam Helme de HavenonDepartment of Neurology, Yale University, New Haven, Connecticut.
Stacey L ClardyDepartment of Neurology, University of Utah School of Medicine, Salt Lake City.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The expansion in the number of disease-modifying therapies (DMTs) for immune-mediated neurologic diseases raises critical questions about trends in their use and cost over time and whether this growth could be contributing to escalating financial burdens within the Medicare system. Objective: To examine trends in claims and Medicare Part D payments for DMTs for immune-mediated neurologic diseases. Design and Setting: This retrospective economic evaluation analyzed Medicare Part D Prescriber Public Use Files from January 1, 2013, to December 31, 2022, restricting to prescription drug claims categorized under the clinician-defined neurology taxonomy. Only prescription drugs used as DMTs for multiple sclerosis, neuromyelitis optica spectrum disorder, and other immune-mediated neurologic disorders were included. To ensure accuracy, these medications were validated by 2 pharmacists. The data were analyzed between October 1, 2023, and November 12, 2024. Main Outcomes and Measures: Ten-year trends in total payments, number of claims, and payment per claim for DMTs were assessed for their contribution to overall cost increases. Inflation adjustments were applied using both medical care-specific and prescription drug-specific indices. Results: Between 2013 and 2022, 63 unique drugs used as DMTs for multiple sclerosis, neuromyelitis optica spectrum disorder, and other immune-mediated neurologic disorders (eg, autoimmune encephalitis, myasthenia gravis) accounted for 6 526 278 claims and contributed $35 billion in Medicare drug expenditures. Between 2013 and 2022, annual claims for DMTs increased by 3.8% (from 549 766 to 570 298 claims). However, total payments for DMTs saw a disproportionate increase of 70.3% (95% CI, 13.5%-130.3%) from 2013 to 2022. After adjusting for medical care or prescription drug inflation, 2022 payments per claim increased by 29.1% (95% CI, 15.6% to 51.6%) and 35.9% (95% CI, 29.5%-50.3%), respectively, indicating that the rise in drug costs exceeded adjustments for medical care or prescription drug inflation rates. For the 29 DMTs available over the entire 10-year period, total claims decreased by 14.8% (from 546 026 to 465 089). Despite this reduction in claims, total payments increased by 60.5% (95% CI, 50.9%-90.6%). After adjusting for medical care inflation, the total payment increased significantly by 26.2% (95% CI, 10.5%-49.4%). Conclusions and Relevance: Over the past decade, Medicare Part D expenditures for DMTs targeting immune-mediated neurologic diseases have increased substantially, despite relatively stable claim volumes. These findings show that increases have consistently outpaced inflation rates, adding substantial economic pressure to federally funded neurologic care.

Indexed as

Medicare Part DNervous System DiseasesAgedFemaleHumansMaleMultiple SclerosisRetrospective StudiesUnited States

Identifiers

PMID41114975
PMCPMC12538365

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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.