Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 910

The DOI matches its Crossref record.

Burden of Migraine in the United States: Disability and Economic Costs

Open access
Hu, X. Henry, Markson, Leona E., Lipton, Richard B., Stewart, Walter F., Berger, Marc L.·1999·Archives of Internal Medicine
DOI 10.1001/archinte.159.8.813
Open this paper in CoChat — free account

Abstract

BACKGROUND: Migraine is a common disabling disease but its economic burden has not been adequately quantified. OBJECTIVE: To estimate the burden of migraine in the United States with respect to disability and economic costs. METHODS: The following data sources were used: published data, the Baltimore County Migraine Study, MEDSTAT's MarketScan medical claims data set, and statistics from the Census Bureau and the Bureau of Labor Statistics. Disability was expressed as bedridden days. Charges for migraine-related treatment were used as direct cost inputs. The human capital approach was used in the estimation of indirect costs. RESULTS: Migraineurs required 3.8 bed rest days for men and 5.6 days for women each year, resulting in a total of 112 million bedridden days. Migraine costs American employers about $13 billion a year because of missed workdays and impaired work function; close to $8 billion was directly due to missed workdays. Patients of both sexes aged 30 to 49 years incurred higher indirect costs compared with younger or older employed patients. Annual direct medical costs for migraine care were about $1 billion and about $100 was spent per diagnosed patient. Physician office visits accounted for about 60% of all costs; in contrast, emergency department visits contributed less than 1% of the direct costs. CONCLUSIONS: The economic burden of migraine predominantly falls on patients and their employers in the form of bedridden days and lost productivity. Various screening and treatment regimens should be evaluated to identify opportunities to reduce the disease burden.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/archinte.159.8.813

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

Metadata

Authors
Hu, X. H., Markson, L. E., Lipton, R. B., Stewart, W. F., & Berger, M. L.
Venue
Archives of Internal Medicine
Publisher
American Medical Association (AMA)
Published
1999-04-26
Volume
159
Issue
8
Pages
813
ISSN
0003-9926 (ISSN-L)
DOI
10.1001/archinte.159.8.813
OpenAlex
W2119011129
Cited by
910
References
0
FWCI
20.60
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.