Artificial Intelligence in Medicine
Volume 37, Issue 3 , Pages 203-218, July 2006

CareVis: Integrated visualization of computerized protocols and temporal patient data

Institute of Software Technology & Interactive Systems (ISIS), Vienna University of Technology, Favoritenstraße 9-11/188, A-1040 Vienna, Austria

Received 15 April 2005; received in revised form 6 April 2006; accepted 10 April 2006.

Summary 

Objective

Currently, visualization support for patient data analysis is mostly limited to the representation of directly measured data. Contextual information on performed treatment steps is an important source to find reasons and explanations for certain phenomena in the measured patient data, but is mostly spared out in the analysis process. This work aims to fill this gap via integrating classical data visualization and visualization of treatment information.

Methods and material

We considered temporal as well as logical data aspects and applied a user-centered development approach that was guided by user input gathered via a user study, design reviews, and prototype evaluations. Furthermore, we investigated the novel PlanningLine glyph, that is used to represent plans in the temporal domain, via a comparative empirical user study.

Results

Our interactive visualization approach CareVis provides multiple simultaneous views to cover different aspects of the complex underlying data structure of treatment plans and patient data. The tightly coupled views use visualization methods well-known to domain experts and are designed to facilitate users’ tasks. The views are based on the concepts of clinical algorithm maps and LifeLines which have been extended in order to cope with the powerful and expressive plan representation language Asbru. Initial feedback of physicians was encouraging and is accompanied by empirical evidence which verifies that PlanningLines are well suited to manage temporal uncertainty.

Conclusion

The interactive integration of different visualization methods forms a novel way of combining, relating, and analyzing different kinds of medical data and information that otherwise would be separated.

Keywords: Protocol-based care, Information visualization, Clinical guidelines, Treatment plans, Patient data, User-centered design, Temporal uncertainties

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PII: S0933-3657(06)00059-5

doi:10.1016/j.artmed.2006.04.002

Artificial Intelligence in Medicine
Volume 37, Issue 3 , Pages 203-218, July 2006