  To empower users of wearable medical devices, it is important to enable
methods that facilitate reflection on previous care to improve future outcomes.
In this work, we conducted a two-phase user-study involving patients,
caregivers, and clinicians to understand gaps in current approaches that
support reflection and user needs for new solutions. Our results show that
users desire to have specific summarization metrics, solutions that minimize
cognitive effort, and solutions that enable data integration to support
meaningful reflection on diabetes management. In addition, we developed and
evaluated a visualization called PixelGrid that presents key metrics in a
matrix-based plot. Majority of users (84%) found the matrix-based approach to
be useful for identifying salient patterns related to certain times and days in
blood glucose data. Through our evaluation we identified that users desire data
visualization solutions with complementary textual descriptors, concise and
flexible presentation, contextually-fitting content, and informative and
actionable insights. Directions for future research on tools that automate
pattern discovery, detect abnormalities, and provide recommendations to improve
care were also identified.
