Connecting time-oriented data and information to a coherent interactive visualization

Bade, Ragnar; Schlechtweg, Stefan; Miksch, Silvia

doi:10.1145/985692.985706

Cited by 111 publications

(77 citation statements)

References 10 publications

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“…Many of these support only a single EHR -Lifelines (9) , Midgaard (10) , Web-Based Interactive Visualization System (11) , VIE-VISU (12) , to name a few. They generally focus on supporting physicians to quickly absorb a patient's potentially lengthy medical history in order to make better medical decisions.…”

Section: Related Workmentioning

confidence: 99%

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Extracting Insights from Electronic Health Records: Case Studies, a Visual Analytics Process Model, and Design Recommendations

et al. 2011

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Current electronic health record (EHR) systems facilitate the storage, retrieval, persistence, and sharing of patient data. However, the way physicians interact with EHRs has not changed much. More specifically, support for temporal analysis of a large number of EHRs has been lacking. A number of information visualization techniques have been proposed to alleviate this problem. Unfortunately, due to their limited application to a single case study, the results are often difficult to generalize across medical scenarios. We present the usage data of Lifelines2 [22], our information visualization system, and user comments, both collected over eight different medical case studies. We generalize our experience into a visual analytics process model for multiple EHRs. Based on our analysis, we make seven design recommendations to information visualization tools to explore EHR systems.

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Section: Related Workmentioning

confidence: 99%

“…It is important to improve information density in Lifelines2 and other time-line based visualizations, e.g., (10,13,35) . From our experience, the reason our physician collaborators look at the detail of the records is to better understand event sequences across multiple EHRs.…”

Section: (Increase Information Density)mentioning

confidence: 99%

Extracting Insights from Electronic Health Records: Case Studies, a Visual Analytics Process Model, and Design Recommendations

et al. 2011

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“…Comparing patient data to medical guidelines is a related domain problem and has yielded some designs that combine features from the groups of MIVA and LifeLines (e.g., CareCruiser [11], Midgaard [4]). However, these designs cater more to different tasks than open-ended exploration.…”

Section: Related Workmentioning

confidence: 99%

“…2): a semantic zoom chart (cp. [4]), a step chart, a silhouette graph, a horizon graph (cp. [26]), and a document browser.…”

Section: Visualization Techniquesmentioning

confidence: 99%

Visual Exploration of Time-Oriented Patient Data for Chronic Diseases: Design Study and Evaluation

Rind

Aigner

Miksch

et al. 2011

Lecture Notes in Computer Science

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Abstract. Medical care, particularly for chronic diseases, accumulates a huge amount of patient data over extensive time periods that needs to be accessed and analyzed accordingly. Information Visualization methods hold great promises in turning data deluge into improved quality of medical care. Yet, patient data management systems mostly provide documents, form-based displays, or static visualizations. We present a design study of an interactive visualization system, called VisuExplore, to support long-term care and medical analysis of patients with chronic diseases. VisuExplore offers interaction techniques for effective exploration of time-oriented data and employs simple, but intuitive visualization techniques. It was developed in close cooperation with physicians. We conducted two user studies with nine physicians and 16 students, which indicate that our design is useful and appropriate for particular tasks.

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“…For example, Bade et al designed an intensive care unit monitoring system in which multiple timelines are displayed. Users can select a subrange at the bottom timeline, then rescale the time range and show it in the middle and top timelines [12]. We borrowed the ideas from the above literature to represent the unevenly spaced timeline in this paper.…”

Section: Related Workmentioning

confidence: 99%

Visual Exploration of Stream Pattern Changes Using a Data-Driven Framework

Xie

Ward

Rundensteiner

2010

Advances in Visual Computing

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Abstract. When using visualization techniques to explore data streams, an important task is to convey pattern changes. Challenges include: (1) Most data analysis tasks require users to observe the pattern change over a long time range; (2) The change rate of patterns is not a constant, and most users are normally more interested in bigger changes than smaller ones. Although distorting the time axis as proposed in the literature can partially solve this problem, most of these are driven by the user. This is however not applicable to streaming data exploration tasks that normally require near real-time responsiveness. In this paper, we propose a data-driven framework to merge and thus condense time windows having small or no changes. Only significant changes are shown to users. Juxtaposed views are discussed for conveying data pattern changes. Our experiments show that our merge algorithm preserves more change information than uniform sampling. We also conducted a user study to confirm that our proposed techniques can help users find pattern changes more quickly than via a non-distorted time axis.

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Connecting time-oriented data and information to a coherent interactive visualization

Cited by 111 publications

References 10 publications

Extracting Insights from Electronic Health Records: Case Studies, a Visual Analytics Process Model, and Design Recommendations

Extracting Insights from Electronic Health Records: Case Studies, a Visual Analytics Process Model, and Design Recommendations

Visual Exploration of Time-Oriented Patient Data for Chronic Diseases: Design Study and Evaluation

Visual Exploration of Stream Pattern Changes Using a Data-Driven Framework

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