Personal technologies for everyday health management have the potential to transform healthcare by empowering individuals to engage in their own care, scaffolding access to critical information, and supporting patient-centered decision-making. Currently, many personal health tools often focus only on a single task or isolated event. However, chronic illnesses are characterized by information needs and challenges that shift over time; thus, these illnesses are better defined as a dynamic trajectory than a series of singular events. In this talk, I discuss my work designing and implementing novel computing systems that: 1) support chronic illness trajectories and 2) reduce patients’ barriers to health information access. I’ll present my approach using personalized and adaptive content to connect individuals with timely and actionable feedback. Using results from longitudinal field deployments, I demonstrate the ability for these tools to facilitate patients’ proactive health management and engagement in their care. I’ll also discuss the utility of this approach for encouraging to long-term engagement with health tools, as evidenced by longitudinal usage patterns. I’ll conclude with opportunities for using personalization as a strategy to support other complex information tasks, including the health management of illness trajectories in which uncertainty is paramount and the integration of machine learning models into clinical workflows.
Dr. Maia Jacobs is a postdoctoral fellow at Harvard University’s Center for Research on Computation and Society. Jacobs’ research focuses on the development and assessment of novel approaches for health information tools to support chronic disease management. She completed her PhD in Human Centered Computing at Georgia Institute of Technology with the thesis, “Personalized Mobile Tools to Support the Cancer Trajectory”. Jacobs’ research was recognized in the 2016 report to the President of the United States from the President's Cancer Panel, which focuses on improving cancer-related outcomes. Her research has been funded by the National Science Foundation, the National Cancer Institute and the Harvard Data Science Institute. Jacobs was awarded the iSchools Doctoral Dissertation Award and the Georgia Institute of Technology College of Computing Dissertation Award. Jacobs was also recognized as a Foley Scholar, the highest award given by the GVU center to PhD candidates at Georgia Tech. Prior to joining Georgia Tech, Maia received a B.S. degree in Industrial and Systems Engineering from the University of Wisconsin-Madison and worked as a User Experience Specialist for Accenture Consulting