Abstract
Adopting electronic health records fuel exponential data growth. However, more data doesn’t necessarily lead to more information unless you have an efficient tool to translate massive data into actionable insights in real time and in a cost-effective manner. This paper is a preliminary study which introduces a new breed of data discovery technology and its value as emerging differentiator from traditional business intelligence, especially in the usability perspective. We present an exemplary case of using QlikView for clinical report dashboard. Physicians and care providers explore patient populations, data patterns, answer questions spontaneously, and forge new drill paths through data volume of millions of rows. Initial evaluation result is promising and indicates visual data discovery tool empowers end users with intuitive and interactive experience, rapid deployment, customizable ad-hoc questions and answers. The next step will be integration with data governance, advanced statistics, predictive modeling and thorough user evaluation with subject matter experts including clinical and IT staff.
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© 2013 Springer-Verlag Berlin Heidelberg
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Zeng, J., Zhang, J. (2013). Visual Data Discovery to Support Patient Care. In: Zeng, D., et al. Smart Health. ICSH 2013. Lecture Notes in Computer Science, vol 8040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39844-5_9
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DOI: https://doi.org/10.1007/978-3-642-39844-5_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39843-8
Online ISBN: 978-3-642-39844-5
eBook Packages: Computer ScienceComputer Science (R0)