Evidence map›Paper›PMID 40663583›Full record

ArticleHeadache2025

Real-world barriers to health care utilization among people living with migraine: Insights from the All of Us Research Program.

Idris Demirsoy, Richard B Lipton, Ali Ezzati

Abstract read
In one paragraph

Article in Headache, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Idris DemirsoyDepartment of Computer Engineering, Usak University, Usak, Turkey.ORCID 0000-0002-3321-4748
Richard B LiptonSaul R. Korey Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA.
Ali EzzatiDepartment of Neurology, University of California, Irvine, Irvine, California, USA.ORCID 0000-0003-1307-4589

Funding

Technology to Empower Changes in Health (TECH) Network Participant Technologies CenterU24OD023176 · OD · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2016 to 2022
$204.7M
Precision Medicine Initiative Cohort Program BiobankU24OD023121 · OD · MAYO CLINIC ROCHESTER · PI CEKANOVA, MARIA, CICEK, MINE · 2016 to 2024
$185.5M
Enhancing All of Us Data Resources for Nutrition Precision Health: the All of Us Data and Research CenterU2COD023196 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GLAZER, DAVID, HARRIS, PAUL A. · 2016 to 2022
$143.7M
Adaptive Platform for Personalized EngagementU24OD023163 · OD · VIGNET, INC. · PI JAIN, PRADUMAN · 2017 to 2020
$102.6M
University of Arizona-Banner Health All of Us Research Program OT2OD026549 · OD · UNIVERSITY OF ARIZONA · PI MORENO, FRANCISCO A, REIMAN, ERIC MICHAEL · 2018 to 2023
$78.9M
Vascular Structure and Function in Cognitive AgingP01AG003949 · NIA · YESHIVA UNIVERSITY · PI CAROL A. DERBY · 1985 to 2026
$73.9M
California Precision Medicine Research Program ConsortiumOT2OD026552 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANTON-CULVER, HODA A, OHNO-MACHADO, LUCILA · 2018 to 2023
$73.4M
All of Us PennsylvaniaOT2OD026554 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E, VISWESWARAN, SHYAM · 2018 to 2023
$72.1M
New York City Consortium for Precision MedicineOT2OD026556 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BIER, LOUISE E, GHARAVI, ALI G · 2018 to 2023
$67.3M
SouthEast Enrollment Center (SEEC) OT2OD026551 · OD · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CARRASQUILLO, OLVEEN, COLON, VIVIAN · 2018 to 2023
$62.8M
Southern All of Us NetworkOT2OD026548 · OD · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI FOUAD, MONA N., KORF, BRUCE R · 2018 to 2023
$60.5M
Illinois Precision Medicine Consortium OT2OD026557 · OD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI AHSAN, HABIBUL, ARGOS, MARIA · 2018 to 2023
$60.5M
AOU NIH HHS WB999999FDA HHS UG3 FD006795NCCIH NIH HHS R01 AT011005NIA NIH HHS P01 AG003949NIA NIH HHS R01 AG057531NIA NIH HHS R01 AG075758NIA NIH HHS R01 AG077639NIA NIH HHS R01 AG080635NIA NIH HHS RF1 AG057531NIA NIH HHS RF1 AG077639NIA NIH HHS U19 AG076581NIDA NIH HHS RM1 DA055437NIH HHS OT2 OD023205NIH HHS OT2 OD023206NIH HHS OT2 OD025276NIH HHS OT2 OD025277NIH HHS OT2 OD025315NIH HHS OT2 OD025337NIH HHS OT2 OD026548NIH HHS OT2 OD026549NIH HHS OT2 OD026550NIH HHS OT2 OD026551NIH HHS OT2 OD026552NIH HHS OT2 OD026553NIH HHS OT2 OD026554NIH HHS OT2 OD026555NIH HHS OT2 OD026556NIH HHS OT2 OD026557NIH HHS U24 OD023121NIH HHS U24 OD023163NIH HHS U24 OD023176NIH HHS U2C OD023196NINDS NIH HHS K23 NS107643NINDS NIH HHS R01 NS123374NINDS NIH HHS R61 NS125153NINDS NIH HHS U24 NS113847University of California, Irvine
6 · The paper itself

Abstract

OBJECTIVES/

backgroundThis study was undertaken to compare health care utilization barriers between participants with medically diagnosed migraine and matched controls without diagnosed migraine. Migraine imposes a significant burden on individuals and on health care systems worldwide. The role of sociodemographic factors and comorbidities in shaping health care utilization for migraine remains insufficiently understood, necessitating further investigation.

methodsThe All of Us Research Program is a large-scale, prospective cohort study funded by the National Institutes of Health. It collects extensive demographic, lifestyle, and health information through self-reports and electronic health records. This analysis uses the Controlled Tier Dataset V7, covering participant data from May 2018 to May 2024. Participants with migraine were identified based on self-reported data from the survey and confirmation of a medical migraine diagnosis through electronic health records using Systematized Nomenclature of Medicine (SNOMED) codes. Additionally, migraine-free controls were propensity-matched to the migraine cases on age, sex, race, and income.

resultsWe identified 8346 migraine cases and an equal number of controls. Each group had an average age of 53.3 years and was 87% female. Despite matching for demographic variables and income, people with migraine had significantly more financial, social, and access barriers than those without migraine. There were higher rates of financial difficulties (46.8% vs. 40.3%, p < 0.001) and more transportation issues (9.9% vs. 5.8%, p < 0.001). They also reported more frequent doctor visits within the past 6 months (93.6% vs. 88.9%, p < 0.001) and a greater number of total doctor visits annually compared to those free of diagnosed migraine (31.1% vs. 17.4%, p < 0.001).

conclusionThis study highlights the significant financial, social, and access barriers faced by participants with migraine, alongside higher health care utilization, compared to those without diagnosed migraine despite matching for demographic variables and income. These findings underscore the substantial burden of migraine and emphasize the urgent need for targeted interventions to enhance health care accessibility and reduce the burden on affected individuals. These data do not capture the burden of undiagnosed migraine due to the method of case ascertainment.

Indexed as

Health Services AccessibilityMigraine DisordersPatient Acceptance of Health CareAdultAgedFemaleHumansMaleMiddle AgedProspective StudiesUnited StatesAll of Us Research Programbarrierscomorbiditieshealth care utilizationmigrainesociodemographic

Identifiers

PMID40663583
PMCPMC12308160

What OpenQuestion holds

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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.