📊Imagine… Health Data Access Is Public Health Capacity📊
💡 Imagined Endstate:
Imagine state and territorial health agencies able to detect emerging problems earlier, understand who is being missed, and evaluate whether interventions are actually working . Public health decisions would be informed by a more complete picture of how people move through the health system.
📚 Source:
Budurlean, L., Joseph, R., & Offutt-Powell, T. (2026, August 25). Closing the real-world data gap for public health. Association of State and Territorial Health Officials. Link.
💥 What’s the Big Deal:
Imagine public health agencies moving from partial visibility to a shared operating picture🔎. Instead of waiting for fragmented reports to reveal what has already happened, health leaders could identify patterns earlier and act with greater confidence.
Budurelean et al. (2026) argue that state and territorial public health agencies have historically lacked access to the breadth of real-world data routinely used by health systems, insurers, researchers, and life-sciences organizations🧭. That gap limits surveillance, analysis, and the ability to respond quickly to changing community health needs.
Public health departments already hold some of the most important datasets in government📂. Vital records, disease surveillance systems, immunization registries, cancer registries, environmental data, and Medicaid claims all provide valuable information. But those systems were never designed to provide a complete view of how the entire population experiences health care.
That matters because large portions of the population can remain partially invisible🌱. People covered through commercial insurance, employer-sponsored plans, or Medicare Advantage may not appear consistently in traditional state surveillance systems. When those populations are missing, agencies can struggle to understand chronic disease, preventive-care gaps, behavioral health trends, or emerging patterns across whole communities.
The problem is not simply that the data exist somewhere else💻. Private health systems, insurers, pharmacies, laboratories, and technology companies already operate inside a much broader real-world data ecosystem. The asymmetry is that public health often carries the responsibility for population-level decision-making without equivalent access to those information resources.
ASTHO’s Public Health Data Consortium is designed to change that balance🪢. Launched in 2026 with Veritas Data Research and HealthVerity, the model gives participating jurisdictions access to linked real-world data, technical support, and dashboards designed around state-defined priorities.
The governance structure may be the most important part⚖️. Instead of states becoming passive consumers of commercially assembled data, the consortium places public health agencies inside the governance process. States help determine how data are used, how privacy is protected, and what kinds of questions the system should answer.
That turns data modernization into something larger than a technology project. It becomes an issue of data sovereignty and institutional capacity🚉. Public health agencies need the ability not only to receive information but to shape the rules governing how that information supports public purposes.
The initial priorities show why that matters 🧪. Maternal health, infant and child health, substance use, rural health, and chronic disease all require timely information across multiple systems. Fragmented data can hide patterns that become obvious only when datasets are linked.
There is also a speed problem🧬. When agencies have to build a new data pipeline every time a new question arises, public health becomes reactive. A shared infrastructure allows analysts to ask new questions without starting from zero each time.
For territorial and island health systems, that challenge can be even more pronounced 🌊. Smaller jurisdictions frequently operate with limited informatics staff and fragmented systems. Data modernization therefore cannot mean simply buying more software. It has to include workforce capacity, interoperability, governance, and sustained access to usable information.
The broader lesson is that data themselves do not create public-health value. Value comes from whether institutions can connect, interpret, and act on them🧬. A sophisticated dataset sitting outside the reach of the agency responsible for population health does little to strengthen resilience.
Public health cannot protect populations it cannot fully see🔌. Closing the real-world data gap is not simply about better analytics, it is about giving public institutions the information capacity required to govern health effectively.
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