Page 10 - Driving Public Health in the Fast Lane
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Efforts to modernize public health surveillance and data systems have been made over the years, but
        the categorical, disease-specific approach to funding and implementing improvements have resulted in
        uneven progress. This has created a patchwork of “haves” and “have nots” across systems and jurisdictions,
        preventing transformative, cross-cutting, comprehensive upgrades. For example, the Centers for Disease
        Control and Prevention (CDC) has more than one hundred siloed public health surveillance data systems.
        State, territorial, local, and tribal health departments share data with CDC through these systems. Many
        of these systems are not interoperable, which results in duplicate and redundant data entry.

        Therefore, to transform the nation’s public health surveillance capacity, we must evolve from manual
        data sharing methods and disease or condition-specific silos towards building a core public health
        data infrastructure—a “public health data superhighway”—that facilitates automatic, interoperable
        data exchange. This foundational approach to improvement, or enterprise-wide approach, will
        support widespread and rapid access to public health data for all public health programs at all levels
        of government for all diseases and conditions. Just like a rising tide lifts all boats, a public health data
        superhighway improves all public health programs. Public health needs a coordinated and integrated
        approach to using data to deliver on mission, serve the public, and steward resources while respecting
        privacy and confidentiality.

        The public health data superhighway transformation will:

             • Inform decision-making by providing access to data sources that were previously unavailable or
               burdensome to retrieve;

             • Enable coordinated responses to emerging public health threats without developing multiple
               stand-alone systems for specific diseases or conditions;
             • Ensure that data systems are interoperable within public health, as well as with external health
               care providers;
             • Support sophisticated data analytics, thereby allowing public health professionals and
               policymakers to make smarter, faster decisions and get ahead of chronic, emerging, and urgent
             • Support federal, territorial, tribal, state, and local public health needs;

             • Establish effective security and privacy protections to limit data breaches and minimize their

        This report explores the challenges with data sharing within the current public health surveillance
        system and demonstrates the need to create an efficient and modern 21  century public health data

        According to focus group conversations with public health subject matter experts, key challenges include:

             • Manual paper-based methods remain a prominent mode of data exchange;

             • Systems improvements to date have been limited to specific programs, resulting in siloed benefits;
             • A vast disconnect remains between health care and public health;

        Driving Public Health in the Fast Lane                                                                 10
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