Digital Interventions in Type 2 Diabetes Mellitus
Main Article Content
Abstract
Introduction: Type 2 diabetes mellitus (T2DM) is a highly prevalent chronic disease with an increasing mortality rate over the last decade. Diabetes self-management education (DSME) programs have been reported as essential to improve survival; however, patient adherence rates are very low. Therefore, digital devices have been created to deliver DSME at a distance and enhance program attendance. This study aims to assess the effects of digitally delivered DSME programs on the glycosylated hemoglobin (HbA1C) of patients with prediabetes and T2DM.
Methods: We researched PUBMED databases for randomized controlled trials (RCT) and observational studies (OS) published between 2012-2022 in English, Portuguese, or Spanish. The selected articles tested digital DSME interventions against treatment as usual (TAU) on adults (>18 years) previously diagnosed with T2DM or prediabetes. The result was measured by determining the HbA1c levels.
Results: Out of 261 articles, 14 RCTs were selected based on eligibility criteria. Digital DSME technologies have different objectives, including monitoring glycemic fluctuation, insulin titration, nutritional guidance, sleeping assessment, enhance- ment of physical activity, control of comorbidities, relevant task notifications, personalized treatment recommendations, educational content, and patient/medical staff remote interaction. Some of the technologies combined machine learning techniques for different functions, including detecting adverse glycemic events, physical activity, and blood pressure, among others. Although the level of adherence varied among the various trials, 4 of the 14 RCTs analyzed reported a significant reduction of HbA1c levels using these digital devices compared to TAU.
Discussion: Programs providing digital DSME education is a potentially cost-effective tool to improve diabetes care worldwide by overcoming distance barriers, facilitating physician-patient communication, and reducing HbA1c levels. Future improvements in implementing these technologies could enhance user compliance and contribute effectively to diabetes management.