Stein Olav Skrøvseth1,2, Eirik Årsand1,3, Fred Godtliebsen2, Ragnar M Joakimsen4,5. 1. 1 Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway , Tromsø, Norway . 2. 2 Department of Mathematics and Statistics, University of Tromsø , Tromsø, Norway . 3. 3 Department of Computer Science, University of Tromsø , Tromsø, Norway . 4. 4 Division of Internal Medicine, University Hospital of North Norway , Tromsø, Norway . 5. 5 Department of Clinical Medicine, University of Tromsø , Tromsø, Norway .
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 mg/dL). RESULTS:Thirty patients were recruited to the study, and 15 were assigned to each group after the initial meeting. There were no significant differences between groups at T1 in HbA1c or OOR events. Overall, all patients had a decrease of 0.6 percentage points in mean HbA1c (P < 0.001) and 14.5 in median OOR events over 2 weeks (P < 0.001). CONCLUSIONS: The study does not provide evidence that data-driven feedback improves glycemic control. The decrease in HbA1c was sizeable and significant, even though the study was not powered to detect this. The overall improvement in glycemic control suggests that, in general, mobile phone-based interventions can be useful in diabetes self-management.
RCT Entities:
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 mg/dL). RESULTS: Thirty patients were recruited to the study, and 15 were assigned to each group after the initial meeting. There were no significant differences between groups at T1 in HbA1c or OOR events. Overall, all patients had a decrease of 0.6 percentage points in mean HbA1c (P < 0.001) and 14.5 in median OOR events over 2 weeks (P < 0.001). CONCLUSIONS: The study does not provide evidence that data-driven feedback improves glycemic control. The decrease in HbA1c was sizeable and significant, even though the study was not powered to detect this. The overall improvement in glycemic control suggests that, in general, mobile phone-based interventions can be useful in diabetes self-management.
Authors: William T Riley; Daniel E Rivera; Audie A Atienza; Wendy Nilsen; Susannah M Allison; Robin Mermelstein Journal: Transl Behav Med Date: 2011-03 Impact factor: 3.046
Authors: Sara Belle Donevant; Robin Dawson Estrada; Joan Marie Culley; Brian Habing; Swann Arp Adams Journal: J Am Med Inform Assoc Date: 2018-10-01 Impact factor: 4.497
Authors: Stephanie Veazie; Kara Winchell; Jennifer Gilbert; Robin Paynter; Ilya Ivlev; Karen B Eden; Kerri Nussbaum; Nicole Weiskopf; Jeanne-Marie Guise; Mark Helfand Journal: J Gen Intern Med Date: 2018-05-08 Impact factor: 5.128
Authors: Birthe Dinesen; Brandie Nonnecke; David Lindeman; Egon Toft; Kristian Kidholm; Kamal Jethwani; Heather M Young; Helle Spindler; Claus Ugilt Oestergaard; Jeffrey A Southard; Mario Gutierrez; Nick Anderson; Nancy M Albert; Jay J Han; Thomas Nesbitt Journal: J Med Internet Res Date: 2016-03-01 Impact factor: 5.428