empower users to see complex relationships between clinical variables—such as comorbidities, sociodemographic attributes, biochemical markers, and genomic determinants—and patient outcomes. Better understanding of these relationships allows patient care to be individualized in ways that previously could only be imagined.

Their interdisciplinary team of physicians, outcomes researchers, and information technology experts pay special attention to creating user interfaces that are both intuitive and responsive and that readily integrate into the workflow of the researchers who develop risk models and the clinicians who use them.