Model Driven Diabetes Care

Data Driven Feedback as a Method to Improve Glycaemic Control in Type 1 Diabetes

Patients with Diabetes Mellitus Type 1 using electronic self-help tools typically registers a large amount of data on their disease. The study intends to see if giving advanced feedback on these data can improve their blood glucose management.

All patients will be given access to a mobile phone with the diabetes diary known as the Few Touch Application (FTA) installed. They may use either their own compatible Android handsets, or provided handsets. The study uses a delayed start design. Participants are randomized into two groups, who get access to the module "Diastat" after 4 and 12 weeks post-enrollment respectively. Each group uses the FTA with Diastat for 8 weeks post-intervention (i.e. access to Diastat).

Diastat is a module within FTA that provides data-driven feedback to the patients using their own data. This module is based on the data recorded in a previous trial [1]. Three submodules are part of Diastat; Periodicity detection and visualization, multiscale trend detection based on the c-SiZer algorithm [2], and situation matching for insulin dosage [3].

1. Skrøvseth SO et al, Diabetes Technol Ther (2012)
2. Skrøvseth SO et al, PLoS ONE (2012)
3. Skrøvseth SO et al, Accepted for Advanced Technologies and Treatments for Diabetes, Paris, France, 2013.

Inclusion Criteria:

• Confirmed diagnosis with Diabetes Mellitus type 1 for at least one year.
• Age over 18 years
• Has basic familiarity with mobile phones, and uses mobile phone on a daily basis.

Exclusion Criteria:

• Severe complications due to their diabetes.
• Unable to understand or conform to the guidelines when presented with the phone's software.