A Mixed-Methods Exploration of the Implementation of Policies That Earmarked Taxes for Behavioral Health.

behavioral health earmarked taxes financing implementation policy policy implementation

Journal

The Milbank quarterly
ISSN: 1468-0009
Titre abrégé: Milbank Q
Pays: United States
ID NLM: 8607003

Informations de publication

Date de publication:
06 Sep 2024
Historique:
revised: 10 07 2024
received: 27 02 2024
accepted: 19 08 2024
medline: 6 9 2024
pubmed: 6 9 2024
entrez: 6 9 2024
Statut: aheadofprint

Résumé

Policy Points Earmarked tax policies for behavioral health are perceived as having positive impacts related to increasing flexible funding, suggesting benefits to expand this financing approach. Implementation challenges related to these earmarked taxes included tax base volatility that impedes long-term service delivery planning and inequities in the distribution of tax revenue. Recommendations for designing or revising earmarked tax policies include developing clear guidelines and support systems to manage the administrative aspects of earmarked tax programs, cocreating reporting and oversight structures with system and service delivery agents, and selecting revenue streams that are relatively stable across years. Over 200 cities and counties in the United States have implemented policies earmarking tax revenue for behavioral health services. This mixed-methods study was conducted with the aim of characterizing perceptions of the impacts of these earmarked tax policies, strengths and weaknesses of tax policy designs, and factors that influence decision making about how tax revenue is allocated for services. Study data came from surveys completed by 274 officials involved in behavioral health earmarked tax policy implementation and 37 interviews with officials in a sample of jurisdictions with these taxes-California (n = 16), Washington (n = 12), Colorado (n = 6), and Iowa (n = 3). Interviews primarily explored perceptions of the advantages and drawbacks of the earmarked tax, perceptions of tax policy design, and factors influencing decisions about revenue allocation. A total of 83% of respondents strongly agreed that it was better to have the tax than not, 73.2% strongly agreed that the tax increased flexibility to address complex behavioral health needs, and 65.1% strongly agreed that the tax increased the number of people served by evidence-based practices. Only 43.3%, however, strongly agreed that it was easy to satisfy tax-reporting requirements. Interviews revealed that the taxes enabled funding for services and implementation supports, such as training in the delivery of evidence-based practices, and supplemented mainstream funding sources (e.g., Medicaid). However, some interviewees also reported challenges related to volatility of funding, inequities in the distribution of tax revenue, and, in some cases, administratively burdensome tax reporting. Decisions about tax revenue allocation were influenced by goals such as reducing behavioral health care inequities, being responsive to community needs, addressing constraints of mainstream funding sources, and, to a lesser degree, supporting services considered to be evidence based. Earmarked taxes are a promising financing strategy to improve access to, and quality of, behavioral health services by supplementing mainstream state and federal financing.

Identifiants

pubmed: 39240049
doi: 10.1111/1468-0009.12715
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NIMH NIH HHS
ID : R21MH12526
Pays : United States
Organisme : NIDA NIH HHS
ID : P50DA054072
Pays : United States

Informations de copyright

© 2024 Milbank Memorial Fund.

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Auteurs

Nicole A Stadnick (NA)

University of California, San Diego.
Altman Clinical and Translational Research Institute, Dissemination and Implementation Science Center, University of California, San Diego.
Child and Adolescent Services Research Center.

Carrie Geremia (C)

University of California, San Diego.

Amanda I Mauri (AI)

Public Health Policy and Management, School of Global Public Health, New York University.

Kera Swanson (K)

Altman Clinical and Translational Research Institute, Dissemination and Implementation Science Center, University of California, San Diego.

Megan Wynecoop (M)

Public Health Policy and Management, School of Global Public Health, New York University.

Jonathan Purtle (J)

Public Health Policy and Management, School of Global Public Health, New York University.

Classifications MeSH