A landscape overview of funding and staffing models for integrated data systems across the U.S. - Nelson, Amy Hawn; Jenkins, Adelia; Algrant, Isabel; Zanti, Sharon; Pepe, Rebecca (International Journal of Population Data Science, 2026)
In the U.S., funding and staffing structures for data sharing and integration vary widely across state and local governments. Since 2009, we have conducted a biennial survey of a large network of integrated data systems (IDS), including questions to deepen our understanding of how IDS develop and are governed, funded, and staffed over time to provide guidance for practitioners and policymakers. This session presents findings from the 2023 and 2025 Network Surveys, as well as 30 qualitative interviews conducted in 2024. These data provide insights and guidance for the field regarding budgets, funding streams, staffing, and capacity development. Findings reveal three broad categories of IDS. Efforts with the smallest budgets have a local and domain specific focus; medium efforts are county or state efforts based at universities; and large efforts tend to be county or state efforts operated within government. Funding comes from a range of sources—federal, local, state, philanthropic, and fee for service. Sites spend the majority of their budgets on staffing and little, comparatively, on technology and infrastructure. Regardless of budget and funding mechanisms, sites spend more money on personnel than any other expense. It costs around $350,000 for the data system itself, including tools for storage and linkage. The major distinction between sites lies in their capacity to afford personnel to do research and design data products internally. These findings fill a critical gap in understanding what resources are needed to stand up IDS in diverse contexts to develop actionable insights for local policymakers.