The HEALing Communities Study evaluated Communities That HEAL, a large-scale, community-engaged intervention designed to reduce opioid overdose deaths through evidence-based practices, coalition building, data-driven decision-making, and communications campaigns across healthcare, behavioral health, criminal-legal, and community-based settings. This case study reflects Atlas Analytics' approach to implementation cost analysis: translating complex launch activities into practical cost evidence for communities, policymakers, and funders planning large-scale public health interventions.
4
State implementation sites compared
$0.06–$0.67
Per-capita start-up cost range
The challenge
Large-scale public health interventions require up-front investments before services can be delivered, but start-up costs are often excluded from economic evaluations. That creates a planning gap for communities and policymakers trying to understand what it takes to launch a complex, community-driven intervention in real-world settings.
The analysis needed to estimate the resources required to prepare Communities That HEAL for implementation across 34 rural and urban communities in Kentucky, Massachusetts, New York, and Ohio, while accounting for differences in staffing models, infrastructure, training needs, and dashboard development.
Role and analytical contribution
The project translated a multi-state intervention launch into a structured start-up cost framework. The analysis connected implementation activities to measurable cost categories, including hiring, training, equipment and infrastructure, and community dashboard development. Core activities included methodology design, cost data harmonization, Excel-based cost modeling, interpretation of site-level variation, and peer-reviewed manuscript development.
Approach
The study used an activity-based costing approach from the community perspective, reflecting the investments a real-world community would need to make to reproduce the intervention outside a research environment. Costs were identified through administrative records, invoices, wage data, and semi-structured interviews, then assigned unit costs and analyzed using a standardized Excel-based tool.
The analysis compared start-up costs across four state implementation sites and three operating models: hospital-academic, university-academic, and community-leveraged. This structure helped clarify how local infrastructure, staffing approach, and implementation model shaped resource needs.
The study produced practical evidence on the up-front investments required to launch a large-scale, community-level opioid overdose reduction intervention. Across the four sites, the mean start-up cost was $247,673 and the median was $175,683, with hiring and training, infrastructure, equipment, and dashboard costs varying substantially by state and implementation model.
The findings showed that leveraging existing community infrastructure can materially reduce start-up costs. The community-leveraged model used in New York had lower hiring, training, and purchasing costs because it relied on existing local infrastructure, relationships, and support from local organizations.
The analysis also helped decision-makers understand the feasibility of launching similar community-level interventions. Across states, start-up costs ranged from $0.06 to $0.67 per community member, providing a practical planning benchmark for future scale-up and replication.
Deliverables
- —Activity-based start-up cost analysis across 34 communities
- —Cost framework for hiring, training, infrastructure, equipment, and dashboard development
- —Standardized Excel-based cost data collection and analysis tool
- —Cross-site cost comparison across four state implementation sites
- —Interpretation of cost variation by implementation structure and existing infrastructure
- —Per-capita start-up cost estimates for community-level planning
- —Peer-reviewed manuscript published in Addiction Science & Clinical Practice
Services
Health economics
Implementation cost analysis
Activity-based costing
Public health evaluation
Cost modeling
Scale-up planning
Federally funded research
Decision-support evidence