Clinical trial NCT01774149: Model Driven Diabetes Care
Official title: Data Driven Feedback as a Method to Improve Glycaemic Control in Type 1 Diabetes
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Diabetes Mellitus, Type 1
Lead sponsor: University Hospital of North Norway
Sponsor class: OTHER
Collaborators: name: University of Tromso
name: The Research Council of Norway
First posted: 2013-01-23
Enrollment: 30
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: SUPPORTIVE_CARE

Brief summary: 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.

Detailed description: 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.

Eligibility criteria: 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.

Primary outcomes:
measure: Change in the Frequency of Hyper- and Hypo-glycemic Events From Baseline to Week 8-12.
timeFrame: Up to 12 weeks post-enrollment
Secondary outcomes:
measure: Change in HbA1c
timeFrame: up to 20 weeks post-enrollment
Other outcomes:
measure: Usability
timeFrame: up to 20 weeks post-enrollment
measure: Empowerment
timeFrame: Up to 12 weeks post-enrollment.
Locations:
city: Tromsø
country: Norway
facility: University Hopital of North Norway
Study officials:
affiliation: University Hospital of North Norway
name: Stein Olav Skrøvseth, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Skrovseth SO, Arsand E, Godtliebsen F, Hartvigsen G. Mobile phone-based pattern recognition and data analysis for patients with type 1 diabetes. Diabetes Technol Ther. 2012 Dec;14(12):1098-104. doi: 10.1089/dia.2012.0160. Epub 2012 Oct 4.
citation: Skrovseth SO, Arsand E, Godtliebsen F, Joakimsen RM. Model driven mobile care for patients with type 1 diabetes. Stud Health Technol Inform. 2012;180:1045-9.
citation: Arsand E, Froisland DH, Skrovseth SO, Chomutare T, Tatara N, Hartvigsen G, Tufano JT. Mobile health applications to assist patients with diabetes: lessons learned and design implications. J Diabetes Sci Technol. 2012 Sep 1;6(5):1197-206. doi: 10.1177/193229681200600525.
citation: Skrovseth SO, Bellika JG, Godtliebsen F. Causality in scale space as an approach to change detection. PLoS One. 2012;7(12):e52253. doi: 10.1371/journal.pone.0052253. Epub 2012 Dec 27.
citation: Skrovseth SO, Arsand E, Godtliebsen F, Joakimsen RM. Model-driven diabetes care: study protocol for a randomized controlled trial. Trials. 2013 May 14;14:139. doi: 10.1186/1745-6215-14-139.
citation: Skrovseth SO, Arsand E, Godtliebsen F, Joakimsen RM. Data-Driven Personalized Feedback to Patients with Type 1 Diabetes: A Randomized Trial. Diabetes Technol Ther. 2015 Jul;17(7):482-9. doi: 10.1089/dia.2014.0276. Epub 2015 Mar 9.