Public Health Ecosystem, Data Goals, Sources and Modernization

How the Public Health Data Strategy (PHDS) Advances the Nation’s Public Health Ecosystem

The Public Health Ecosystem has seven components.

The public health ecosystem includes federal partners, the public, providers, CDC, national public health partners, healthcare systems, and states, tribes, localities and territories (STLTs).

CDC uses the term “public health ecosystem” to describe public health’s connectivity with the multitude of people and systems across the nation that depend on, influence and interact with each other. It also includes workforce, policies and technologies used to collect, manage, access, share, analyze and disseminate the most relevant data.

The PHDS uses measurable milestones to build an integrated public health ecosystem that produces and uses public health data to improve our communities and keep people safe.

The PHDS outlines a vision of data exchange within the public health ecosystem that improves speed, quality and completeness.

It builds on lessons learned from recent public health threats such as COVID-19 and mpox to make the ecosystem more response-ready. And it aligns data modernization efforts across the ecosystem with concrete and measurable milestones.

The PHDS Empowers Partners with Data and Tools

Public: Have greater access to critical information on public health emergencies, risks, trends and resources
Healthcare (labs and providers): Reduce time and complexity of reporting data to public health partners (at the STLT- and federal-levels)
States, Tribes, Localities and Territories (STLTs): Detect and address public health threats and potential health equity issues faster, and reduce time and complexity of reporting data to federal partners
CDC Programs: More effectively use core public health data sources to support faster public health threat detection and action
Federal Agencies: Align data and technology investments, and improve response-readiness with faster, more complete collection of core data sources

The Public Health Data Goals

The PHDS has been developed to create accountability for delivering progress against four public health data goals:

  • Goal 1: Strengthen the core of public health data.
    • Ensure core data sources are more complete, timely, rapidly exchanged and available to support the integrated ability to detect, monitor, investigate and respond to public health threats.
  • Goal 2: Accelerate access to analytic and automated solutions to support public health investigations and advance health equity.
    • Make tools available so state, tribal, local and territorial (STLT) public health departments and other public health decision-makers can better use public health data to address health disparities.
  • Goal 3: Visualize and share insights to inform public health action.
    • Serve as a trusted source for near real-time visualizations and offer situational awareness for the public and decision-makers to understand risks, make decisions and direct resources.
  • Goal 4: Advance more open and interoperable public health data.
    • Enable exchange of interoperable data so that health care, STLT public health departments, federal agency partners and CDC programs can access and use data they need, when they need them.

Core Data Sources

Core data sources are data that, together, provide a picture of what is happening in our communities. They are essential to:

  • Identify diseases and conditions.
  • Detect emerging public health threats.
  • Understand disease burden and severity across different populations.
  • Take public health action.

These data can be used to understand any disease or condition, both in emergencies and every day.

The PHDS decreases the burden for STLT public health departments to securely report these critical data while improving dissemination to ensure the right data are available at the right time.

These are the core data sources currently being tracked. The list of sources will evolve as the public health ecosystem evolves.

  • Case data, with personally identifiable information removed, represent comprehensive disease and condition information used by public health to understand disease burden, know who is at risk and identify outbreaks.​
  • Laboratory data, including test results and test type, enable public health agencies to track disease trends and identify outbreaks or exposures and help frontline providers diagnose and treat health conditions.​
  • ED data, including clinical diagnoses, signs and symptoms, help identify near real-time trends for new, emerging and developing public health threats to inform faster detection and response.​
  • Vital statistics data include birth and death data and are essential to understand disease severity, mortality, trauma and toxicity that might signal a larger public health emergency.
  • Immunization data capture vaccine doses administered (both routinely recommended and response-related) to support calculating vaccination coverage levels and trends.
  • Healthcare capacity and utilization data assess availability of healthcare resources, including staff, beds and equipment, aiding understanding of health system stresses and disease severity to inform resource allocation.
  • Wastewater surveillance data capture the presence of virus through assessment of wastewater samples, serving as an early warning of viruses spreading throughout a community.

Core data sources as defined in CDC Advisory Committee to the Director (ACD) Data and Surveillance Workgroup (DSW) Report; non-exhaustive of all data sources critical to public health awareness and response such as advanced molecular detection data.

Data Modernization: Accelerating Data into Action

The PHDS builds on CDC’s data modernization initiative (DMI) begun in 2019 to solve a number of problems facing the nation’s public health ecosystem.

  • Siloed information with disconnected and/or proprietary disease systems driven by disease-specific budget lines keeping the nation from seeing the complete picture.
  • Outdated skills of the public health workforce who need training to use today’s technologies more effectively.
  • The heavy burden for providers in health care and at health departments, required to send data to many places in many ways.
  • Older technologies at many health departments that are not flexible, do not use cloud and are not scalable.
  • A patchwork of policies with the variable landscape of data collection and reporting across the nation complicating rapid response to emerging threats.
  • Healthcare data ecosystem that does not include public health, so public health was left behind as federal incentives and regulations helped healthcare systems be able to easily share data automatically in electronic health records.

DMI enables the PHDS by:

  • Providing the vehicle for broad transformation.
  • Including major improvements for public health data and systems as well as what is needed to carry out the work such as state-of-the-art workforce, expanded partnerships, culture change and unified governance.

The PHDS accelerates DMI by:

  • Laying out important steps that drive DMI priorities forward faster.
  • Highlights what is most meaningful and achievable over the next two years.
  • Identifies actionable goals that will yield the most impact.

Data modernization is not a “one and done.” It is an ongoing, comprehensive and long-term effort involving CDC and STLT public health departments, other federal agencies and healthcare partners.