Data-Driven Personalized Feedback to Patients with Type 1 Diabetes: A Randomized Trial.

ABSTRACT:

Background

A mobile phone-based application can be useful for patients with type 1 diabetes in managing their disease. This results in large datasets accumulated on the patient's devices, which can be used for individualized feedback. The effect of such feedback is investigated in this article.

Materials and methods

We developed an application that included a data-driven feedback module known as Diastat for patients on self-measured blood glucose regimens. Using a stepped-wedge design, both groups initially received an application without Diastat. Group 1 activated Diastat after 4 weeks, whereas Group 2 activated Diastat 12 weeks after startup (T1). End points were glycated hemoglobin (HbA1c) level and number of out-of-range (OOR) measurements (i.e., outside the range 72-270

SUBMITTER: Skrovseth SO 

PROVIDER: S-EPMC4504254 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature