Zayas-Caban exploring ways to improve predictive models in healthcare

Gabriel Zayas-Caban, an associate professor of industrial and systems engineering, is co-leading a new project funded by the Patient-Centered Outcomes Research Institute to develop methods to better integrate risk prediction models into healthcare systems.

Zayas-Caban and Amy Cochran, an assistant professor of mathematics and population health sciences, are both principal investigators on the three-year, more than $1 million project.

The research team will use causal inference methods to evaluate the use of predictive models in healthcare, to allow those models to incorporate new updates, and to evaluate interventions suggested by the models.

Zayas-Caban and Cochran will specifically look at a model that predicts chronic kidney disease from electronic health record data.