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Description

In recent years, healthcare organizations have tackled numerous challenges including quality improvement in the face of rising healthcare costs, facilitating interoperability, innovation with health information technologies (HIT), and integration of data from novel data sources such as patient-generated health data (PGHD) and mobile app data. The increasing diversity and volume of healthcare data poses a challenging task for medical experts trying to make sense of patients’ health and illness conditions, for patients trying to make sense of their health data and their health, and for analysts to conduct outcomes and discovery research. Visual Analytics, the science of analytical reasoning facilitated by interactive visual interfaces, has the potential to provide great benefits to healthcare providers, patients, and data analysts.

Learning Objective 1: Provide a venue and continue to develop a community in which subject matter experts, technologists, and patient-researchers interested in clinical visual analytics can talk and discuss opportunities, challenges, methodologies, visualization techniques, and tools

Learning Objective 2: Help the broader visual analytic community receive feedback and suggestions from subject matter experts and develop an understanding of patient-researcher needs and opportunities for collaboration

Authors:

Annie Chen (Presenter)
University of Washington

Jeremy Warner (Presenter)
Vanderbilt University

Danny Wu (Presenter)
University of Cincinnati

Presentation Materials:

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