Diabetes Management: Mobile Phone Applications Used Within Healthcare Systems for Type 1 Diabetes Self-Management

The CPSTF uses recently published systematic reviews to conduct accelerated assessments of interventions that could provide program planners and decision-makers with additional, effective options. The following published review was selected and evaluated by a team of specialists in systematic review methods, and in research, practice, and policy related to diabetes management.

Hou C, Carter B, Hewitt J, Francisa T, Mayor S. Do mobile phone applications improve glycemic control (HbA1c) in the self-management of diabetes? A systematic review, meta-analysis, and GRADE of 14 randomized trials. Diabetes Care 2016; 39:2089-95.

The review included four studies that targeted patients with type 1 diabetes (search period January 1996—June 2015). The team examined each of the studies included in the systematic review and abstracted supplemental information about study, intervention, and population characteristics.

The CPSTF finding is based on results from the published review, additional information from the included studies, and expert input from team members and the CPSTF.

Mobile phone (both cell phone and smart phone) ownership in the Unites States reached 95% in 2016 (Pew Research Center, 2017). Apps have been developed to help users manage chronic diseases, and about 70% of these apps are specific to diabetes (Fatehi et al., 2017).

Mobile apps may help patients manage chronic diseases by providing constant monitoring and tracking of self-management tasks, sending self-management tips, and delivering clinically accurate feedback when needed.

Currently, there are no guidelines in the field on how to assess the effectiveness of these apps.

Detailed results from the systematic review are available in the CPSTF Finding and Rationale Statement.

• Compared with usual care, mobile phone apps implemented in healthcare settings reduced blood glucose levels (A1c) by 0.9% and 1.4% (2 studies).
• Compared with teaching carbohydrate counting to patients face-to-face, teaching the same techniques through mobile phone apps resulted in the following:
  
  • Similar reductions in A1c levels
  • Less time needed to learn the same materials (apps took a median of 6 hours, control groups took a median of 12 hours)

An economic review of this intervention was not conducted because the CPSTF did not have enough information to determine if the intervention works.

Applicability of this intervention across different settings and populations was not assessed because the CPSTF did not have enough information to determine if the intervention works.

The CPSTF identified several areas that have limited information. Additional research and evaluation could help answer the following questions and fill remaining gaps in the evidence base. (What are evidence gaps?)

• Are self-management apps implemented in healthcare systems effective in reducing A1c levels among patients with type 1 diabetes?
• Are diabetes self-management apps available in app stores effective in reducing A1c levels for users with type 1 diabetes?
• What factors influence app effectiveness?
  
  • Number of functionalities offered?
  • Specific functionalities offered?
  • Type of feedback (i.e., none, automated, personalized feedback from healthcare professionals, or a combination of the latter two)?
  • Demographic characteristics such as age, race and ethnicity, income, and education?
  • Users’ health literacy?

Interventions were implemented in healthcare systems in the following countries:

• Australia (1 study), France (1 study), Italy (1 study), and multiple European Union countries (1 study)

Study participants had the following demographic characteristics:

• Mean age of 35.5 years (4 studies)
• 59.1% female (4 studies)
• Diagnosis of type 1 diabetes for a mean of 16.5 years (4 studies)

Intervention characteristics:

• Three unique apps with the following functionalities were evaluated.
  
  • Carbohydrate and insulin bolus calculator (2 apps)
  • Medication adjustment support (3 apps)
  • Graphical feedback (1 app)
  • Automated feedback (3 apps)
  • Healthcare professional feedback (3 apps)
• Apps tracked users’ diabetes-related outcomes
  
  • Blood glucose levels (3 apps)
  • Food and carbohydrate intake (2 apps)
  • Diabetes medication (2 apps)
  • Physical activity (3 apps)
• Intervention duration ranged from 6 to 9 months, with a median of 6 months