Practical Steps in Implementing Privacy Measures with Synthetic Health Data (Preprint)

UNSTRUCTURED Privacy concerns related to the use of sensitive personal healthcare information is a consistent concern for innovators in both academic and industrial sectors as a barrier to healthcare data access. Synthetic data (new data generated from the original data) is becoming one of the approaches that innovators use to reduce privacy concerns while conducting research or building translational tools. Synthetic data serve to replicate the patterns within the original data, without containing the personal information of “real” participants. In this article, we discuss the importance of collaboration between industry, academia, and legislative bodies to address the pervasive challenge of privacy concerns associated with the use of sensitive personal healthcare information. Synthetic data represents a nexus for academia, industry, and lawmakers, which offers a compelling solution for innovations in healthcare if done through a pragmatic lens.