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Digital Interventions for Self-Management of Type 2 Diabetes Mellitus: Systematic Literature Review and Meta-Analysis
David Kerr1, David Ahn2, Kayo Waki3
1Center for Health Systems Research, Sutter Health, Walnut Creek, CA, United States.
Background:
The proliferation of digital technology has the potential to transform diabetes management. One of the critical aspects of modern diabetes management remains the achievement of glycemic targets to avoid acute and long-term complications.
Objective:
This study aims to describe the landscape of evidence pertaining to the relative effectiveness or efficacy and safety of various digital interventions for the self-management of type 2 diabetes mellitus (T2DM), with a primary focus on reducing glycated hemoglobin A1c (HbA1c) levels.
Methods:
A systematic literature review (SLR) was conducted by searching Embase, MEDLINE, and CENTRAL on April 5, 2022. Study selection, data extraction, and quality assessment were performed by 2 independent reviewers. Eligibility criteria for the SLR included randomized controlled trials (RCTs) and comparative observational studies evaluating interventions containing both human (eg, coaching) and digital components (eg, glucose meter) in adult patients with T2DM. The primary meta-analysis was restricted to studies that reported laboratory-measured HbA1c. In secondary analyses, meta-regression was performed with the intensity of coaching in the digital intervention as a categorical covariate.
Results:
In total, 28 studies were included in this analysis. Most studies (23/28, 82%) used the reduction of HbA1c levels as the primary end point, either directly or as a part of a multicomponent outcome. In total, 21 studies reported statistically significant results with this primary end point. When stratified into 3 intervention categories by the intensity of the intervention supporting the digital health technology (analyzing all 28 studies), the success rate appeared to be proportional to the coaching intensity (ie, higher-intensity studies reported higher success rates). When the analysis was restricted to RCTs using the comparative improvement of HbA1c levels, the effectiveness of the interventions was less clear. Only half (12/23, 52%) of the included RCTs reported statistically significant results. The meta-analyses were broadly aligned with the results of the SLR. The primary analysis estimated a greater reduction in HbA1c associated with digital interventions compared with usual care (-0.31%, 95% CI -0.45% to -0.16%; P<.001). Meta-regression estimated reductions of -0.45% (95% CI -0.81% to -0.09%; P=.02), -0.29% (95% CI -0.48% to -0.11%; P=.003), and -0.28% (95% CI -0.65% to 0.09%; P=.20) associated with high-, medium-, and low-intensity interventions, respectively.
Conclusions:
These findings suggest that reducing HbA1c levels in individuals with T2DM with the help of digital interventions is feasible, effective, and acceptable. One common feature of effective digital health interventions was the availability of timely and responsive personalized coaching by a dedicated health care professional.
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