Health Data Utilities: The Future of Public Health Infrastructure

‍How a distributed network of state-based Health Data Utilities could transform surveillance, detection, response, and research in the United States.

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TL;DR

The U.S. public health system still relies on slow, fragmented, provider-driven reporting that leaves states and the federal government unprepared for fast-moving threats. Health Data Utilities (HDUs), state-based, transparently governed data intermediaries that integrate clinical, claims, and public health data, offer a path to transform this landscape.

HDUs enable continuous surveillance, predictive detection, real-time crisis response, and continuous-learning research by providing curated, trusted, population-level data infrastructure. Building a national, federated network of HDUs would shift public health from episodic reporting to a resilient, always-on utility layer, much like the electric grid.

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To make this vision real, we recommend federal leaders pursue:

Independent verification and conflict-of-interest safeguards

A public-health performance overlay focused on timeliness, completeness, and epidemiologic fidelity

Federated identity and consent policies

Open governance and equity reporting

A unified CDC–ASTP/ONC–CMS roadmap linking HDU capabilities to sustainable funding

The technology and frameworks exist today; what’s needed now is leadership and national commitment to treat health data as critical public-health infrastructure.

Setting the Stage

Our Public Health Dilemma

After decades of progress in digitizing healthcare, America’s public-health data infrastructure still runs on brittle pipes. Outbreak data travel slowly across stove-piped and incomplete pathways. Reporting requirements differ by jurisdiction. Local and state health departments shoulder redundant onboarding and compliance work.

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The COVID-19 pandemic made these cracks impossible to ignore and spurred a wave of investment in data modernization. Recent rules from ASTP/ONC included certification requirements to drive public health case reporting modernizations.¹ CDC formed the Office of Public Health Data Standards and Technology (OPHDST), which developed the CDC Public Health Data Strategy² while actively investing in a new enterprise data platform. CMS issued rules to increase the interoperability and timeliness of data sharing³. And other agencies, like HRSA and SAMHSA, began piloting ways to increase the granularity, fidelity, and interoperability of the data they collect about the grants they fund to further improve public health.

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All this is necessary, yet the deeper challenge remains: we have connected systems, not capabilities. We can move data, but we cannot yet trust, verify, or reuse it across missions.

A Better Way

Imagine the next national public health emergency. In our new world, instead of scrambling for hospital data feeds, every state is already connected and ready, receiving reliable, current data relevant to the emergency. Public health agencies open a live dashboard on demand that shows new admissions, lab confirmations, and vaccination rates by ZIP code. Clinicians receive alerts within hours, not days, while in parallel, researchers access de-identified trend data to model spread, and communities can see transparent, equity-based metrics of how the response unfolds.

This common sense vision is not idealistic, nor futuristic. It is possible now. Let me share some examples that stand out as bright spots from the pandemic, all of which leverage national infrastructure that exists today.

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During the COVID-19 pandemic, Health Information Exchanges (HIEs) across the nation collaborated with providers and public health leaders, quickly deploying dashboards to provide situational awareness and enable effective responses⁴ and alert providers⁵. Similarly, the eHealth Exchange, an interstate network of HIEs, worked with its members and the Association of Public Health Laboratories (APHL) to deliver electronic case reports across the 20 states in its network.⁶

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Imagine what these national resources could do with robust and sustained state, federal, and commercial partnerships.

Introducing the Health Data Utility (HDU)

That’s exactly what forward-thinking leaders in the HIE community did. Coming together to form the Consortium for State and Regional Interoperability or CSRI, they worked to define how HIEs could play a more active role in healthcare and public health based on the lessons they learned from the pandemic. Emerging from their work, a new concept took shape: the next-generation model for the nation’s health-data backbone—the Health Data Utility (HDU)⁷.

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To avoid the buzz-word trap that afflicts so many innovative concepts, the consortium developed a definition of what it means for a statewide data organization to act as a public utility for health information and published a maturity model⁸ to act as a roadmap for HIEs. At the heart of the model lay the foundational requirement to link clinical, claims, and public-health data under transparent, multi-stakeholder governance.

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Version 2⁹ of the model, which CSRI renamed a Capability Model and released in October 2025, builds on and extends the capabilities listed in Version 1, making those measurable and verifiable, offering a stronger foundation for federal and state partners to use in their efforts to build a distributed, trusted network for the public good. This new version provides the building blocks to develop a blueprint for transforming public health data sharing.

Reimagining Public Health

What could such a blueprint look like? What do HDUs enable? Let’s consider those questions from the four central perspectives of public health: surveillance, detection, response, and research.

I. Surveillance: From passive reporting to continuous awareness

Today’s surveillance still relies on episodic, provider-driven reporting, particularly for case reports¹⁰. HDUs replace that model with a live feed of population health data flowing automatically from source to consumer as events occur.

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Near-term possibilities (1–3 years):

Unified data flows: HDUs already ingest electronic lab results, case reports, and syndromic data. With shared data-quality validation engines, they can harmonize inputs from EHRs, labs, and payers into single, curated streams.

Equity visibility: Through automated race-and-ethnicity enrichment and disaggregated dashboards, HDUs can reveal where gaps in data—and care—persist.

Community intelligence: Real-time dashboards could replace monthly PDFs, giving local health officials daily situational awareness across hospitals, schools, and long-term-care settings.

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Longer-term horizon (5–10 years):

Federated national surveillance mesh: Each HDU becomes a node in a TEFCA-aligned network that allows de-identified, near-real-time queries across states while preserving state autonomy.

Adaptive analytics: Continuous data flows feed machine-learning models that flag anomalies in emergency visits or wastewater samples before outbreaks surface in the news.

II. Detection: From reaction to prediction

When every hour matters, the ability to see patterns before they surge defines preparedness. Our nation’s experience with COVID-19 reinforced this reality, inspiring innovative approaches to enable public health authorities to move from reactive to proactive. Monitoring wastewater was one such example.¹¹ HDUs build on these lessons to enable prediction from data derived from secure, well-maintained longitudinal patient records enriched with environmental (e.g., wastewater, geography, social graph) data.

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Near-term:

Predictive outbreak forecasting combines clinical alerts, syndromic surveillance, and environmental sensors within the HDU architecture.

Closed-loop reporting shortens the time from lab confirmation to case investigation by enabling bidirectional exchange between providers and public health.

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Longer-term:

Digital epidemiologic twins: State HDUs could maintain dynamic models of their populations—simulating how interventions would play out under different conditions.

Federated AI for early warning: HDUs’ curated datasets provide a safe substrate for training detection algorithms without moving raw data, enabling national insight without centralized risk.

III. Response: From data collection to data activation

The next crisis will not wait for custom data-sharing agreements. HDUs can serve as pre-positioned infrastructure that activates in emergencies. State and federal authorities must act to design data sharing agreements with built-in “break glass” clauses to enable the infrastructure to activate when needed.

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Near-term:

Data-ready emergency response: Capabilities like “disaster access to patient data” and “family reunification support” can supply real-time information to emergency managers.

Operational dashboards: Integration of bed availability, hospital census, and immunization data gives emergency operations centers live situational control.

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Longer-term:

A national public-health utility layer: Like the electric grid, a federated HDU network could be switched into emergency mode, aggregating situational data nationwide within hours.

Cross-sector coordination: Because HDUs also exchange social-service and Medicaid data, they can orchestrate recovery across housing, food, and education systems that determine community resilience.

IV. Research: From episodic studies to continuous learning

The U.S. spends billions collecting data for research that often arrives too late to inform policy. HDUs could close that loop.

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Near-term:

Federated research commons: HDUs standardize data under the OMOP Common Data Model, allowing universities and agencies to query de-identified datasets in place.

Rapid program evaluation: Longitudinal HDU data enable near-real-time assessment of vaccination campaigns, SDOH initiatives, or telehealth interventions.

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Long-term:

Public Health Learning Network: Linked HDUs form a national data commons that supports continuous analytics and equity benchmarking across jurisdictions.

Ethical AI discovery: With built-in bias detection, consent governance, and data provenance, HDUs can power trustworthy machine-learning models for precision public health.

A Call to Build the Public Health Utility Layer

The United States does not need another proprietary platform or one-off pilot. It needs a national network of trusted, evidence-verified HDUs: locally governed, federally aligned, and universally accountable. If built deliberately, this distributed architecture can transform public health from a reporting function into a living, learning system—one that detects faster, responds smarter, and learns continuously. The pipes exist. The governance framework is emerging. What remains is the decision and the will to treat health data infrastructure as critical public-health infrastructure.

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While the capabilities exist and are maturing, transformation requires more than capability; it requires commitment and leadership. Thankfully, leaders are emerging at the state and federal level to drive this needed revolution in public health, building on the work that began during the pandemic with case reporting and dashboards¹².

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As fellow citizens of our great nation and experts in health technology and data sharing, we offer these recommendations to federal leaders who seek to accelerate the change.

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Establish independent verification and conflict-of-interest safeguards, ensuring HDU assessments remain transparent and credible. While the model advances the measurability and potential procurement-readiness of HDUs, several governance and validation gaps could undermine accountability, transparency, and equity in how “readiness” is determined.

Embed a public-health performance overlay that includes national metrics for timeliness, completeness, and epidemiologic fidelity as gating criteria for HDU funding. Public health interoperability must rest on clear legal authority and transparent consent rules. A CDC-governed overlay ensures uniform compliance with public health law while maintaining compatibility with national interoperability frameworks.

Align consent and identity policies through federated, purpose-limited digital identity and dual-control consent architectures. While the intent behind the inclusion of the shared-domain gates is sound, as written these gates could centralize control in private frameworks, harden vendor lock-in, and create privacy/optics issues that erode public trust.

Require open governance and equity reporting so communities can see who is represented, what data are included, and where gaps remain. Transparency in HDU operations ensures that stakeholders and the public can understand who governs, how decisions are made, and how data are managed. Public visibility increases trust and aligns HDUs with principles of democratic accountability.

Create a joint CDC–ASTP/ONC–CMS roadmap that ties HDU capability advancement to sustainable funding, certification, and Medicaid interoperability goals. Interagency alignment prevents conflicting requirements, streamlines policy implementation, and promotes shared understanding of HDU obligations under federal law.

We stand ready with ground-level expertise and practical ideas to move HDUs from concept to reality. As we do, it is critical to avoid a one-size-fits-all approach. We must balance state, federal, and commercial interests and enable local governance and innovation while ensuring a shared, sustainable funding model for the future.