Exploring Flow, Factors and Outcomes of Event Sequences
Electronic Medical Record (EMR) databases contain a large amount of temporal events such as diagnosis dates for various symptoms. Analyzing disease progression pathways in terms of these observed events can provide important insights into how diseases evolve over time. Moreover, connecting these pathways to the eventual outcomes of the corresponding patients can help clinicians understand how certain progression paths may lead to better or worse outcomes. In this paper, we describe the Outflow visualization technique, designed to summarize temporal event data that has been extracted from the EMRs of a cohort of patients. We include sample analyses to show examples of the insights that can be learned from this visualization.
Krist Wongsuphasawat and David Gotz
IBM T.J. Watson Research Center
- Project page on IBM website
- Exploring Flow, Factors and Outcomes of Temporal Event Sequences with the Outflow Visualization by Krist Wongsuphasawat and David Gotz. in Proc. IEEE Conference on Information Visualization (InfoVis) / IEEE Transactions on Visualization and Computer Graphics, Seattle, WA, USA, October, 2012
- Outflow: Visualizing Patients Flow by Symptoms and Outcome by Krist Wongsuphasawat and David Gotz. in Proc. Workshop on Visual Analytics in Healthcare (VAHC) in conjunction with IEEE VisWeek 2011, Providence, RI, USA, 23 October, 2011