Patient-Centered Data Visualizations for Diabetes

Diabetes self-management activities generate an enormous amount of data, including carbohydrate intake and patient glucose and insulin levels. While the data are available, the extent to which this information is utilized for developing insights about self  management is limited. Most data visualization displays are static and often display only blood glucose numbers without providing additional information or insights. Adolescents with type 1 diabetes are a particularly important group to engage in data use because they have access to mobile device data, yet their glycemic control is suboptimal.

This project assessed the needs of adolescents, caregivers, and healthcare providers related to comprehending and using complex data. Researchers developed and tested a data visualization prototype for adolescents and their parents to view their diabetes data in conjunction with contextual information.

The specific aims of the project were as follows:

• Perform environmental scans of existing data visualization techniques from commercial diabetes software and consumer-facing mobile technology. 
• Peform a literature review of data visualization and interactive techniques for viewing longitudinal data that may have the potential to enhance patients’ and families' ability to interpret their healthcare data. 
• Understand adolescent, caregiver, and provider information needs related to diabetes and for understanding complex longitudinal data. 
• Devise a list of candidate visualization techniques, develop a software prototype to operationalize these techniques, and iteratively refine the prototype through a series of user studies. 
• Have adolescents with type 1 diabetes collect diabetes data and contextual variables using mobile technology and incorporate this data into the data visualization prototype for usability testing. 

An environmental scan of data visualization was conducted using semi-structured interviews with adolescents and their caregivers, and focus groups with diabetes providers. The results informed the development of a mobile application that was evaluated with a pilot study. Findings indicated significant variation across diabetes data platforms and a lack of standardization in data presentation. The pilot study found that participants were able to use multiple data sources to discover new insights regarding their diabetes. Possible solutions for addressing patterns of high and low blood glucose values were generated using the prototype visualizations that incorporated contextual information such as daily activities, mood, and stress. Parents of the teen participants preferred a cumulative summary graph of blood glucose, carbohydrate intake, and insulin doses in order to identify trends around mealtimes, certain days of the week, and activities. The project team concluded that personalizing contextual diabetes data is an important feature of any diabetes data visualization system.