Moving Through the Matrix: Improving Population Health in the Digital Age

By Rebecca Vigen, M.D.

Associate Professor of Internal Medicine

Beyond documentation and billing, the electronic health record (EHR) can be used as a platform for detecting disease, identifying gaps in treatment, and deploying care interventions. Along with co-moderator Ty Gluckman, M.D., M.H.A., and panelist Steve Bradley, M.D., M.P.H., I had the opportunity to moderate an innovative and exciting session at #AHA24.

Topics addressed in the session included using the EHR to detect diseases such as familial hyperlipidemia and to create risk models. An example of the latter included the creation of a contrast-associated acute kidney injury model and the use of clinical decision support to mitigate contrast volumes in at-risk patients. Another topic included the use of clinical decision support to improve the uptake of guideline-directed medical therapy for heart failure. Finally, one talk highlighted the use of synthetic data derivatives, which are de-identified datasets derived from EHR data that maintain the statistical properties of the original data and do not contain protected health information. Such synthetic data derivatives have the potential to be shared between investigators and health systems to accelerate research with the aim of improving population health.