Evidence map›Paper›PMID 37738064›Full record

ArticleJAMA health forum2023

Medicaid Value-Based Payments and Health Care Use for Patients With Mental Illness.

Ashley Lewis, Renata E Howland, Leora I Horwitz, Sunita M Desai

Abstract read
In one paragraph

Article in JAMA health forum, 2023. 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

4 authors.

Ashley LewisDepartment of Population Health, NYU Grossman School of Medicine, New York, New York.
Renata E HowlandDepartment of Population Health, NYU Grossman School of Medicine, New York, New York.
Leora I HorwitzDivision of Healthcare Delivery Science, Department of Population Health, NYU School of Medicine, New York, New York.
Sunita M DesaiDepartment of Population Health, NYU Grossman School of Medicine, New York, New York.

Funding

NYU Training Program in Healthcare Delivery Science and Population Health ResearchT32HS026120 · AHRQ · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI HORWITZ, LEORA, SCHWARTZ, MARK D · 2018 to 2023
$3.4M
Designing policies to incentivize high-quality health care for vulnerable Americans: Evidence from the 340B Drug Pricing ProgramK01HS026980 · AHRQ · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DESAI, SUNITA · 2020 to 2024
$786k
How does implementation of Pay-for-Performance and Collaborative Care impact utilization and health outcomes for Medicaid Behavioral Health patientsF30MH127905 · NIMH · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI LEWIS, ASHLEY · 2022 to 2023
$89k
AHRQ HHS K01 HS026980AHRQ HHS T32 HS026120NIMH NIH HHS F30 MH127905
6 · The paper itself

Abstract

Importance: Medicaid patients with mental illness comprise one of the most high-need and complex patient populations. Value-based reforms aim to improve care, but their efficacy in the Medicaid program is unclear. Objective: To investigate if New York state's Medicaid value-based payment reform was associated with improved utilization patterns for patients with mental illness. Design, Setting, and Participants: This retrospective cohort study used a difference-in-differences analysis to compare changes in utilization between Medicaid beneficiaries whose outpatient practices participated in value-based payment reform and beneficiaries whose practices did not participate from before (July 1, 2013-June 30, 2015) to after reform (July 1, 2015-June 30, 2019). Participants were Medicaid beneficiaries in New York state aged 18 to 64 years with major depression disorder, bipolar disorder, and/or schizophrenia. Data analysis was performed from April 2021 to July 2023. Exposure: Beneficiaries were exposed to value-based payment reforms if their attributed outpatient practice participated in value-based payment reform at baseline (July 1, 2015). Main Outcomes and Measures: Primary outcomes were the number of outpatient primary care visits and the number of behavioral health visits per year. Secondary outcomes were the number of mental health emergency department visits and hospitalizations per year. Results: The analytic population comprised 306 290 individuals with depression (67.4% female; mean [SD] age, 38.6 [11.9] years), 85 105 patients with bipolar disorder (59.6% female; mean [SD] age, 38.0 [11.6] years), and 71 299 patients with schizophrenia (45.1% female; mean [SD] age, 40.3 [12.2] years). After adjustment, analyses estimated a statistically significant, positive association between value-based payments and behavioral health visits for patients with depression (0.91 visits; 95% CI, 0.51-1.30) and bipolar disorder (1.01 visits; 95% CI, 0.22-1.79). There was no statistically significant changes to primary care visits for patients with depression and bipolar disorder, but value-based payments were associated with reductions in primary care visits for patients with schizophrenia (-1.31 visits; 95% CI, -2.51 to -0.12). In every diagnostic population, value-based payment was associated with significant reductions in mental health emergency department visits (population with depression: -0.01 visits [95% CI, -0.02 to -0.002]; population with bipolar disorder: -0.02 visits [95% CI, -0.05 to -0.001]; population with schizophrenia: -0.04 visits [95% CI, -0.07 to -0.01]). Conclusions and Relevance: In this cohort study, Medicaid value-based payment reform was statistically significantly associated with an increase in behavioral health visits and a reduction in mental health emergency department visits for patients with mental illness. Medicaid value-based payment may be effective at altering health care utilization in patients with mental illness.

Indexed as

Major Depressive DisorderMental DisordersAdultCohort StudiesFemaleHumansMaleMedicaidOutpatientsRetrospective StudiesUnited States

Identifiers

PMID37738064
PMCPMC10517380

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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.