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


What the CPSTF Found

About The Systematic Review

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 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.


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

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 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

A systematic review of economic evidence has not been conducted.


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

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 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:

  • Studies were conducted in the United States (3 studies), Finland (1 study), Japan (1 study), Korea (1 study), Norway (1 study), and the United Kingdom (2 studies).
  • All of the studies evaluated mobile phone apps implemented within a healthcare system.

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