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Diabetes Management: Mobile Phone Applications Used Within Healthcare Systems for Type 2 Diabetes Self-Management

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What the CPSTF Found

About The Systematic Review

The CPSTF considers recently published systematic reviews to provide public health professionals and decision-makers with effective intervention options. A team of specialists in systematic review methods and in diabetes management research, practice, and policy selected and evaluated the following published review:

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 nine studies that had patients with type 2 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.

Context

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.

Summary of Results

More details about study results 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 a median of 0.4% (9 studies).
  • Apps that provided feedback from healthcare professionals produced greater reductions in blood glucose levels when compared to apps that only offered automated feedback (mean reductions in A1c of 0.58% and 0.44%, respectively).
  • Patients 55 years of age or younger experienced greater reductions in A1c when compared with patients over 55 years of age (mean reductions in A1c of 1.03% and 0.41%, respectively).

Summary of Economic Evidence

Content is in development.

Applicability

Based on results for interventions in different settings and populations, findings should be applicable to women and men with type 2 diabetes who are living in high income countries.

Evidence Gaps

Additional research and evaluation are needed to answer the following questions and fill existing gaps in the evidence base. (What are evidence gaps?)

  • Are diabetes self-management apps available in app stores effective in reducing A1c levels for users with type 2 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 race and ethnicity, income, and education?
    • Users’ health literacy?

Study Characteristics

Interventions were implemented in healthcare systems in the following countries:

  • Australia (1 study), Japan (1 study), Korea (1 study), the European Union (6 studies), the United Kingdom (1 study), and the United States (3 studies)

Study participants had the following demographic characteristics:

  • Mean age of 57.7 years (8 studies)
  • 43.7% female (8 studies)
  • Diagnosis of type 2 diabetes for a mean of 8.8 years (6 studies)

Intervention characteristics:

  • Eight unique apps with the following functionalities were evaluated.
    • Medication adjustment support (3 apps)
    • Graphical feedback (5 apps)
    • Automated feedback (6 apps)
    • Healthcare professional feedback (6 apps)
  • Apps tracked users’ diabetes-related outcomes
    • Blood glucose levels (8 apps)
    • Blood pressure (2 apps)
    • Body weight (3 apps)
    • Food intake (3 apps)
    • Diabetes medication adherence (5 apps)
  • Intervention duration ranged from 3 to 12 months, with a median of 6 months

Publications

There are no Community Guide publications for this systematic review.