Evidence map›Paper›PMID 36781580›Full record

ArticleJournal of general internal medicine2023

Medical Expenditures Associated with Attention-Deficit/Hyperactivity Disorder Among Adults in the United States by Age, 2015-2019.

Brian Witrick, Donglan Zhang, Dejun Su, Yan Li, William V McCall, Brian Hendricks, Lu Shi

Open access · hybridAbstract read
In one paragraph

Article in Journal of general internal medicine, 2023. 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
0.2field-weighted citation impact, top 49% of its field
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 citations in OpenAlex.

  1. Trial
  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

7 authors at 6 institutions in 1 country.

Brian WitrickWest Virginia Clinical and Translational Sciences Institute, PO Box 9102, Morgantown, WV, 26506, USA.ORCID 0000-0002-3800-8695
Donglan ZhangDivision of Health Services Research, Department of Foundations of Medicine, New York University Long Island School of Medicine, Mineola, NY, USA.
Dejun SuUniversity of Nebraska Medical Center, Omaha, NE, USA.
Yan LiIcahn School of Medicine at Mount Sinai, New York, NY, USA.
William V McCallMedical College of Georgia at Augusta University, Augusta, USA.
Brian HendricksWest Virginia Clinical and Translational Sciences Institute, PO Box 9102, Morgantown, WV, 26506, USA.
Lu ShiClemson University, Clemson, SC, USA.
Augusta University · USClemson University · USIcahn School of Medicine at Mount Sinai · USLong Island University · USUniversity of Nebraska Medical Center · USWest Virginia University · US

Funding

West Virginia IDEA-CTRU54GM104942 · NIGMS · WEST VIRGINIA UNIVERSITY · PI Anne Courtney DeVries · 2012 to 2026
$81.0M
Identifying COVID-19 vaccine deserts using Machine Learning and Geospatial Analyses to target Community -engaged testing for vulnerable rural populations to prevent localized outbreaksU01MD017419 · NIMHD · WEST VIRGINIA UNIVERSITY · PI HENDRICKS, BRIAN, PRICE, BRADLEY · 2022 to 2023
$2.2M
NIGMS NIH HHS U54 GM104942NIMHD NIH HHS U01 MD017419
6 · The paper itself

Abstract

backgroundAttention-deficit hyperactivity disorder is a common disorder that affects both children and adults. However, for adults, little is known about ADHD-attributable medical expenditures.

objectiveTo estimate the medical expenditures associated with ADHD, stratified by age, in the US adult population.

designUsing a two-part model, we analyzed data from Medical Expenditure Panel Survey for 2015 to 2019. The first part of the model predicts the probability that individuals incurred any medical costs during the calendar year using a logit model. The second part of the model estimates the medical expenditures for individuals who incurred any medical expenses in the calendar year using a generalized linear model. Covariates included age, sex, race/ethnicity, geographic region, Charlson comorbidity index, insurance, asthma, anxiety, and mood disorders.

participantsAdults (18 +) who participated in the Medical Expenditure Panel Survey from 2015 to 2019 (N = 83,776). MAIN MEASURES: Overall and service specific direct ADHD-attributable medical expenditures. KEY

resultsA total of 1206 participants (1.44%) were classified as having ADHD. The estimated incremental costs of ADHD in adults were $2591.06 per person, amounting to $8.29 billion nationally. Significant adjusted incremental costs were prescription medication ($1347.06; 95% CI: $990.69-$1625.93), which accounted for the largest portion of total costs, and office-based visits ($724.86; 95% CI: $177.75-$1528.62). The adjusted incremental costs for outpatient visits, inpatient visits, emergency room visits, and home health visits were not significantly different. Among older adults (31 +), the incremental cost of ADHD was $2623.48, while in young adults (18-30), the incremental cost was $1856.66.

conclusionsThe average medical expenditures for adults with ADHD in the US were substantially higher than those without ADHD and the incremental costs were higher in older adults (31 +) than younger adults (18-30). Future research is needed to understand the increasing trend in ADHD attributable cost.

Indexed as

Attention Deficit Disorder with HyperactivityHealth ExpendituresAdultAgedAge FactorsFemaleHumansMaleMiddle AgedOffice VisitsPrescription DrugsUnited StatesYoung AdultPrescription DrugsADHDadultsattention-deficit/hyperactivity disorderhealth care costsmedical expenditures

Identifiers

PMID36781580
PMCPMC10361917
OpenAlexW4320483691

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.