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VA for Personalized Medicine

This research program provides visual analytics support for the work of the UBC Life Sciences Institute, not-for-profic Personalized Medicine Initiative, and Molecular You Inc. We will support the design and evaluation of visual analysis tools for exploration, monitoring and communication of complex, large scale, diverse data from the Molecular You initiative to consumers.

 

Using a combination of NSERC Engage, MITACS, and MYco funding we will study how health care consumers and caregivers can understand complex health data, propose interventions, and assess the results through the use of interactive visualization environments. Considering the initiative is a rather new endeavor, this project represents both a challenge and a unique opportunity for implementing and evaluating human centered design methods. Our initial pilot project will:

Assess Molecular You data dimensions, constraints, and characteristics.

  • Data cleaning, structuring, and integrity checking
  • Focus Groups with Molecular You clients to understand their capabilities, goals, beliefs, privacy expectations, and interests when dealing with health data.

 Design and Develop a Personalized Health Data Exploration Tool for Molecular You clients.

  • Prototype interactive visualization interfaces using scalable technologies (Python/D3).
  • Feedback from project actors: project leaders, omics experts, and general audience
  • User study of the analytical performance of consumers with multi-source health data 

Identify key research challenges for visual analytics in personalized health management.

 

  • Document process of eliciting user needs, organizing and cleaning data sets
  • Assess and describe cognitive tasks that health consumers perform
  • Document which visualizations are most effective for clients
  • Provide preliminary assessment of individual differences in visualization literacy

 Evaluation will then be done using our Pair Analysis method, combining a visual analytics and a user/ subject matter expert on an analytic task. These sessions are captured on video and analyzed based on Joint Activity Theory. The findings are then used to propose a design and software engineering approach to development of the MYCo interface.