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Interactive Data Visualization to Understand Data Better: Case Studies in Healthcare System

Interactive Data Visualization to Understand Data Better: Case Studies in Healthcare System

Zhecheng Zhu, Bee Hoon Heng, Kiok Liang Teow
Copyright: © 2014 |Volume: 4 |Issue: 2 |Pages: 10
ISSN: 1947-9115|EISSN: 1947-9123|EISBN13: 9781466655393|DOI: 10.4018/IJKDB.2014070101
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MLA

Zhu, Zhecheng, et al. "Interactive Data Visualization to Understand Data Better: Case Studies in Healthcare System." IJKDB vol.4, no.2 2014: pp.1-10. http://doi.org/10.4018/IJKDB.2014070101

APA

Zhu, Z., Heng, B. H., & Teow, K. L. (2014). Interactive Data Visualization to Understand Data Better: Case Studies in Healthcare System. International Journal of Knowledge Discovery in Bioinformatics (IJKDB), 4(2), 1-10. http://doi.org/10.4018/IJKDB.2014070101

Chicago

Zhu, Zhecheng, Bee Hoon Heng, and Kiok Liang Teow. "Interactive Data Visualization to Understand Data Better: Case Studies in Healthcare System," International Journal of Knowledge Discovery in Bioinformatics (IJKDB) 4, no.2: 1-10. http://doi.org/10.4018/IJKDB.2014070101

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Abstract

This paper focuses on interactive data visualization techniques and their applications in healthcare systems. Interactive data visualization is a collection of techniques translating data from its numeric format to graphic presentation dynamically for easy understanding and visual impact. Compared to conventional static data visualization techniques, interactive data visualization techniques allow users to self-explore the entire data set by instant slice and dice, quick switching among multiple data sources. Adjustable granularity of interactive data visualization allows for both detailed micro information and aggregated macro information displayed in a single chart. Animated transition adds extra visual impact that describes how system transits from one state to another. When applied to healthcare system, interactive visualization techniques are useful in areas such as information integration, flow or trajectory presentation and location related visualization, etc. In this paper, three case studies are shared to illustrate how interactive data visualization techniques are applied to various aspects of healthcare systems. The first case study shows a pathway visualization representing longitudinal disease progression of a patient cohort. The second case study shows a dashboard profiling different patient cohorts from multiple perspectives. The third case study shows an interactive map illustrating patient geographical distribution at adjustable granularity. All three case studies illustrate that interactive data visualization techniques help quick information access, fast knowledge sharing and better decision making in healthcare system.

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