  Electronic Health Records (EHRs) contain a large volume of heterogeneous
patient data, which are useful at the point of care and for retrospective
research. These data are typically stored in relational databases. Gaining an
integrated view of these data for a single patient typically requires complex
SQL queries joining multiple tables. In this work, we present a visualization
tool that integrates heterogeneous health care data (e.g., clinical notes,
laboratory test values, vital signs) into a single timeline. We train risk
models offline and dynamically generate and present their predictions alongside
patient data. Our visualization is designed to enable users to understand the
heterogeneous temporal data quickly and comprehensively, and to place the
output of analytic models in the context of the underlying data.
