An animated multivariate visualization for physiological and clinical data in the ICU

  • Authors:
  • Patricia Ordóñez;Marie desJardins;Michael Lombardi;Christoph U. Lehmann;Jim Fackler

  • Affiliations:
  • University of Maryland, Baltimore County, Baltimore, MD, USA;University of Maryland, Baltimore County, Baltimore, MD, USA;University of Maryland, Baltimore County, Baltimore, MD, USA;Johns Hopkins School of Medicine, Baltimore, MD, USA;Johns Hopkins School of Medicine, Baltimore , MD, USA

  • Venue:
  • Proceedings of the 1st ACM International Health Informatics Symposium
  • Year:
  • 2010

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Abstract

Current visualizations of electronic medical data in the Intensive Care Unit (ICU) consist of stacked univariate plots of variables over time and a tabular display of the current numeric values for the corresponding variables and occasionally an alarm limit. The value of information is dependent upon knowledge of historic values to determine a change in state. With the ability to acquire more historic information, providers need more sophisticated visualization tools to assist them in analyzing the data in a multivariate fashion over time. We present a multivariate time series visualization that is interactive and animated, and has proven to be as effective as current methods in the ICU for predicting an episode of acute hypotension in terms of accuracy, confidence, and efficiency with only 30-60 minutes of training.