# gschwandtner2011carecruiser
# CareCruiser: Exploring and visualizing plans, events, and effects interactively
Concept
The authors introduce CareCruiser to support the exploration of effects on a patient's condition after clinical actions [1].
CareCruiser aims to provide an enhanced visual analysis system to explore the result of each applied clinical action and identities sub-optimal treatment choices. This helps clinicians investigate and optimize their treatment plans.
Implementation
Figure 1 shows an overview of CareCruiser visualizing a patient's historical oxygen saturation(tcpSO2) and carbon dioxide(PCO2) pressure values during treatment plan executions. Colors are coded to represent the deviation of the value from its initial point, only brushed sections will be highlighted in color. Details of the brushed treatment plans are shown on the top left. The lower left shows a tree graph visualizing brushed treatment plans and sub-plans in a hierarchical structure. User options to filter and search clinical actions within the brushed area are shown above the main view.
Below the main view is the plan bar, glyphs are used to represent clinical actions along the x-axis which represents time. Actions applied that are not part of the plan are laid below the plan bar.
Related Work
The filtering of clinical events are inspired by LifeLine 2 [2] and PatternFinder [3].
KNAVE II [4] introduces filtering on different granularities of time and event alignment with absolute and relative time scales.
LiveRAC [5] arranges charts in a matrix and provides reordering of rows and columns and zooming in multiple levels.
The authors only find a few tools that support visualization of applied treatment plans in combination with patient data. GOT [6] shows basic characteristics of the treatment plan with a focus on patient data. CareVis [7] supports temporal constraints of treatment plans. Midgaard [8] visualizes treatment plans in a hierarchical structure.
Data Characteristics
- Data source: unknown
- Size: 1 patient
- Spatial dimensionality: 2D
- Temporal dimensionality: static
- Type: multivariate
- Libraries used: Java
Visualization Techniques
- Glyph
- Tree
- Time-series chart
Papers Cited
27
Years Spanned
1932-2011
Application Domain
- Electronic Health Record Visualization
- Medical focus: discuss with Bob
Reference
Gschwandtner, T., Aigner, W., Kaiser, K., Miksch, S., & Seyfang, A. (2011). CareCruiser: Exploring and visualizing plans, events, and effects interactively. IEEE Pacific Visualization Symposium 2011, PacificVis 2011 - Proceedings, 43â50. https://doi.org/10.1109/PACIFICVIS.2011.5742371 âŠī¸
Plaisant, C., Mushlin, R., Snyder, A., Li, J., Heller, D., & Shneiderman, B. (1998). LifeLines: using visualization to enhance navigation and analysis of patient records. Proceedings / AMIA ... Annual Symposium. AMIA Symposium. âŠī¸
Fails, J. A., Karlson, A., Shahamat, L., & Shneiderman, B. (2006). A visual interface for multivariate temporal data: Finding patterns of events across multiple histories. IEEE Symposium on Visual Analytics Science and Technology 2006, VAST 2006 - Proceedings. https://doi.org/10.1109/VAST.2006.261421 âŠī¸
Martins, S. B., Shahar, Y., Goren-Bar, D., Galperin, M., Kaizer, H., Basso, L. V., âĻ Goldstein, M. K. (2008). Evaluation of an architecture for intelligent query and exploration of time-oriented clinical data. Artificial Intelligence in Medicine. https://doi.org/10.1016/j.artmed.2008.03.006 âŠī¸
McLachlan, P., Munzner, T., Koutsofios, E., & North, S. (2008). LiveRAC: Interactive visual exploration of system management time-series data. Conference on Human Factors in Computing Systems - Proceedings. https://doi.org/10.1145/1357054.1357286 âŠī¸
W. Aigner. Guideline overview tool (GOT), Asgaard-TR-2001-4. Technical report, Vienna University of Technology, Institute of Soft- ware Technology and Interactive Systems, Vienna, Austria, 2001. âŠī¸
Aigner, W., & Miksch, S. (2006). CareVis: Integrated visualization of computerized protocols and temporal patient data. Artificial Intelligence in Medicine. https://doi.org/10.1016/j.artmed.2006.04.002 âŠī¸
Bade, R., Schlechtweg, S., & Miksch, S. (2004). Connecting time-oriented data and information to a coherent interactive visualization. Conference on Human Factors in Computing Systems - Proceedings. âŠī¸
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