Abstract: A Cost Analysis of the Family Access Center of Excellence (FACE): A Community-Based Organization Funded By a Local Earmarked Tax Intended to Improve School and Community Behavioral Health (Society for Social Work and Research 31st Annual Conference)

682P A Cost Analysis of the Family Access Center of Excellence (FACE): A Community-Based Organization Funded By a Local Earmarked Tax Intended to Improve School and Community Behavioral Health

Schedule:
Saturday, January 23, 2027
Continental 1-4 (Hilton San Francisco Union Square)
* noted as presenting author
Aaron Thompson, PhD, Associate Professor, University of Missouri-Columbia, Columbia, MO
Dani Adams, Assistant Professor, University of Missouri
Andy Frey, Professor, University of Missouri-Columbia
Background and Purpose: Youth behavioral health needs in the United States continue to rise while access to evidence‑based services remains limited, prompting communities to explore locally earmarked taxes to sustain prevention and intervention systems. Despite their growing use, little is known about how these tax revenues translate into operational costs at the organizational level. This study examined the Family Access Center of Excellence (FACE) of Boone County, a university–community partnership funded entirely by a dedicated county sales tax, to address the question: What are the maintenance‑year costs of implementing FACE, and how are these costs distributed across roles, cost categories, and prevention versus intervention services? Methods: Using an ingredients‑based, gross costing approach, we conducted a cost analysis from the perspective of the county’s Children’s Services Board for the 2023 contract year. Data included actual expenditures across personnel, operating, information technology, facilities and administration, and therapy access, supplemented by staff self‑reported time allocation and annual service utilization records. Costs were disaggregated by personnel roles (e.g., leadership, supervisors, regional coordinators, family intervention specialists, outreach coordinators, case managers), cost categories, and school‑based versus community‑based prevention and intervention activities. Average (marginal) costs per service were calculated by dividing total expenditures allocated to each activity by the number of units delivered. Results: Personnel expenditures constituted 83% of total costs, with 74% supporting direct service roles. Regional coordinators and family intervention specialists accounted for 25% and 27% of personnel costs, respectively, reflecting the labor‑intensive nature of school‑based service delivery. Prevention and intervention activities accounted for 48% and 52% of combined school‑ and community‑based expenditures. School‑based screening was the least expensive service ($1.90 per screening), whereas community‑based case management was the most costly ($1,490 per family). Outreach contacts averaged $35 per unit, school‑based student intervention averaged $801 per student, and caregiver‑focused services averaged $1,096 per caregiver. Conclusions and Implications: Findings illustrate how a local earmarked tax can sustainably finance a comprehensive, multi‑tiered system of school‑ and community‑based behavioral health supports. The cost structure of FACE—characterized by high investment in direct service personnel and relatively low operational overhead—demonstrates a financially transparent and scalable model for counties seeking to expand behavioral health infrastructure. Low per‑unit costs for universal screening and prevention support fiscal feasibility for broad implementation, while comparatively moderate costs for intensive family services position the model as a cost‑efficient alternative to more resource‑intensive evidence‑based case management programs. This analysis provides policymakers, funders, and local agencies with actionable cost benchmarks and highlights the potential of university–community partnerships to enhance sustainability, penetration, and system‑level impact. Future research should examine cost variation over time, conduct sensitivity analyses, and link costs to outcomes to inform cost‑effectiveness and guide decisions about scale‑up and replication.