US public health surveillance, reimagined

This study presents two novel concepts for standardizing electronic health records (EHR)-based public health surveillance through utilization of existing informatics methods and data platforms.

Drawing from the collective experience in applied epidemiology, health services research and health informatics, the author presents a vision for an alternative path to public health surveillance by repurposing existing tools and resources, such as (1) computable phenotypes which have already been created and validated for a variety of chronic diseases of interest to public health and (2) large data platforms/collaboratives, such as All of Us Research Program and National COVID Cohort Collaborative. Opportunities and challenges are discussed regarding EHR-based chronic disease surveillance, as well as the concept of phenotype definitions and large data platforms reuse for public health needs.

Reusing of computable phenotypes for EHR-based public health surveillance would require secure data platforms and nationally representative data. Standardization metrics for reuse of previously developed and validated computable phenotypes are also necessary and are currently being developed by the author. This study presents a reimagined Learning Health System framework by incorporating Public Health and two novel concept sets of solutions into the healthcare ecosystem.

Alternative approaches to limited resources and current infrastructure of the US Public Health System, especially as applied to disease surveillance, are needed and may be possible when repurposing the resources and methodologies across the Learning Health System.