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Project ROCKET: Relationship of Clinical Knowledge to Events Tool

Project Description

The Relationship of Clinical Knowledge to Events Tool (ROCKET) is an innovative “big data” research and education tool that supports clinical analysis, data visualization and knowledge linking to allow users to explore large, temporally analyzed clinical datasets. Clinical events (e.g., chronic and non-chronic disease, medications, etc.) are defined and longitudinally analyzed on the institution’s Hadoop cluster with resultant temporal data passed to ROCKET. This user-friendly visualization tool facilitates easy access and review of temporal relationships and potential correlations, thereby providing users an initial analysis that can lead to subsequent research hypotheses focused on improved health-care delivery and patient/population outcomes. The institution’s Hadoop-based clinical research database (CRDB) with 2M patients and nine years of clinical data is longitudinally analyzed with ROCKET clinical events that currently include 25 chronic diseases, 8 non-chronic diseases and two medications (SSRIs and statins). ROCKET predefines clinical event expression maps (currently 1,160), which are temporally ordered plots of one clinical event against another. For example, an event expression map may temporally visualize all detected expression of chronic anemia relative to detected expression of chronic breast cancer, or expression of potential adverse events associated with onset of statin administration. Currently, the default expression display details the temporal relationship between a chosen clinical event and all other diseases (32) or medications (2). Users also can perform ad-hoc multi-event visualizations by selecting an “alignment” event (e.g., acute myocardial infraction) and a desired number of temporal events. Events are Medical Subject Heading (MESH) coded to support linking to online knowledge content.

Primary Contact: Ron Price, Jr.
Institution: Loyola University Chicago Stritch School of Medicine

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