• Wathsala Widanagamaachchi, Yarden Livnat, Peer-Timo Bremer, Scott Duvall, and Valerio Pascucci.
• SCI Institute, University of Utah, Salt Lake City, UT, USA.
• AMIA Annu Symp Proc. 2017 Jan 1; 2017: 1773-1782.

AbstractAs medical organizations increasingly adopt the use of electronic health records (EHRs), large volumes of clinical data are being captured on a daily basis. These data provide comprehensive information about patients and have the potential to improve a wide range of application domains in healthcare. Physicians and clinical researchers are interested in finding effective ways to understand this abundance of data. Use of visual analytics to explore healthcare data is one such research direction. Here, we present a visualization and analysis environment to understand patient progression over time. Through the use of optimized data structures and progressive visualization techniques, we allow users to interactively explore how patients and their progression change over time. Compared to existing techniques, our work provides additional flexibility in analyzing patient data and has the potential to be used in a real-time hospital setting. Finally, we demonstrate the utility of our approach using a publicly available intensive care unit (ICU) database.

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