Evidence map›Paper›PMID 39257310›Full record

ArticlePsychiatric services (Washington, D.C.)2025

High Out-of-Pocket Cost Burden of Mental Health Care for Adult Outpatients in the United States.

Y Nina Gao, Mark Olfson

Abstract read
In one paragraph

Article in Psychiatric services (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

2 authors.

Y Nina GaoDepartment of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, and New York State Psychiatric Institute, New York City (all authors); Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City (Olfson).
Mark OlfsonDepartment of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, and New York State Psychiatric Institute, New York City (all authors); Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City (Olfson).

Funding

Research Training in Mood and Anxiety Disorders: From Animal Models to PatientsT32MH015144 · NIMH · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Eduardo David Leonardo · 1985 to 2026
$11.1M
NIMH NIH HHS T32 MH015144
6 · The paper itself

Abstract

objectiveThis report describes characteristics of patients who had high out-of-pocket (OOP) spending on mental health care relative to income.

methodsA sample of 8,923 U.S. adults with outpatient mental health visits was drawn from the 2018-2021 Medical Expenditure Panel Survey. Respondents who spent ≥10% of their disposable family incomes on OOP mental health visits were defined as having a high OOP cost burden.

resultsUsing weighted percentages, the authors found that 2.4% of psychiatric outpatients had a high OOP burden; among those below the federal poverty level, 12.8% had a high OOP burden. Patients with a high (vs. low) OOP burden were statistically significantly more likely to be uninsured (7.5% vs. 2.4%) or diagnosed as having a substance use disorder (8.7% vs. 2.8%) or bipolar disorder (14.5% vs. 8.0%).

conclusionsDespite federal policies extending the availability of insurance for mental health care, many low-income psychiatric outpatients experience high OOP cost burden.

Indexed as

Ambulatory CareCost of IllnessHealth ExpendituresMental DisordersMental Health ServicesOutpatientsAdolescentAdultAgedFemaleHumansMaleMiddle AgedPovertyUnited StatesYoung Adultinsurancelow incomemental health careoutpatient treatmentpoverty level

Identifiers

PMID39257310
PMCPMC11786981

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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.