Andreas Triantafyllidis1, Haridimos Kondylakis2, Konstantinos Votis3, Dimitrios Tzovaras3, Nicos Maglaveras4, Kazem Rahimi5. 1. Information Technologies Institute, Centre for Research and Technology Hellas (CERTH), Greece; Laboratory of Computing, Medical Informatics and Biomedical Imaging Technologies, School of Medicine, Aristotle University of Thessaloniki, Greece. Electronic address: atriand@iti.gr. 2. Computational Biomedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Greece. 3. Information Technologies Institute, Centre for Research and Technology Hellas (CERTH), Greece. 4. Laboratory of Computing, Medical Informatics and Biomedical Imaging Technologies, School of Medicine, Aristotle University of Thessaloniki, Greece; Department of Electrical Engineering & Computer Science, Northwestern University, USA; Department of Industrial Engineering & Management Sciences, Northwestern University, USA. 5. The George Institute for Global Health, University of Oxford, UK.
Abstract
BACKGROUND: Mobile health (mHealth) technology has the potential to play a key role in improving the health of patients with chronic non-communicable diseases. OBJECTIVES: We present a review of systematic reviews of mHealth in chronic disease management, by showing the features and outcomes of mHealth interventions, along with associated challenges in this rapidly growing field. METHODS: We searched the bibliographic databases of PubMed, Scopus, and Cochrane to identify systematic reviews of mHealth interventions with advanced technical capabilities (e.g., Internet-linked apps, interoperation with sensors, communication with clinical platforms, etc.) utilized in randomized clinical trials. The original studies included the reviews were synthesized according to their intervention features, the targeted diseases, the primary outcome, the number of participants and their average age, as well as the total follow-up duration. RESULTS: We identified 5 reviews respecting our inclusion and exclusion criteria, which examined 30 mHealth interventions. The highest percentage of the interventions targeted patients with diabetes (n = 19, 63%), followed by patients with psychotic disorders (n = 7, 23%), lung diseases (n = 3, 10%), and cardiovascular disease (n = 1, 3%). 14 studies showed effective results: 9 in diabetes management, 2 in lung function, and 3 in mental health. Significantly positive outcomes were reported in 8 interventions (n = 8, 47%) from 17 studies assessing glucose concentration, one intervention assessing physical activity, 2 interventions (n = 2, 67%) from 3 studies assessing lung function parameters, and 3 mental health interventions assessing N-back performance, medication adherence, and number of hospitalizations. Divergent features were adopted in 14 interventions with significantly positive outcomes, such as personalized goal setting (n = 10, 71%), motivational feedback (n = 5, 36%), and alerts for health professionals (n = 3, 21%). The most significant found challenges in the development and evaluation of mHealth interventions include the design of studies with high quality, the construction of robust interventions in combination with health professional inputs, and the identification of tools and methods to improve patient adherence. CONCLUSIONS: This review found mixed evidence regarding the health benefits of mHealth interventions for patients living with chronic diseases. Further rigorous studies are needed to assess the outcomes of personalized mHealth interventions toward the optimal management of chronic diseases.
BACKGROUND: Mobile health (mHealth) technology has the potential to play a key role in improving the health of patients with chronic non-communicable diseases. OBJECTIVES: We present a review of systematic reviews of mHealth in chronic disease management, by showing the features and outcomes of mHealth interventions, along with associated challenges in this rapidly growing field. METHODS: We searched the bibliographic databases of PubMed, Scopus, and Cochrane to identify systematic reviews of mHealth interventions with advanced technical capabilities (e.g., Internet-linked apps, interoperation with sensors, communication with clinical platforms, etc.) utilized in randomized clinical trials. The original studies included the reviews were synthesized according to their intervention features, the targeted diseases, the primary outcome, the number of participants and their average age, as well as the total follow-up duration. RESULTS: We identified 5 reviews respecting our inclusion and exclusion criteria, which examined 30 mHealth interventions. The highest percentage of the interventions targeted patients with diabetes (n = 19, 63%), followed by patients with psychotic disorders (n = 7, 23%), lung diseases (n = 3, 10%), and cardiovascular disease (n = 1, 3%). 14 studies showed effective results: 9 in diabetes management, 2 in lung function, and 3 in mental health. Significantly positive outcomes were reported in 8 interventions (n = 8, 47%) from 17 studies assessing glucose concentration, one intervention assessing physical activity, 2 interventions (n = 2, 67%) from 3 studies assessing lung function parameters, and 3 mental health interventions assessing N-back performance, medication adherence, and number of hospitalizations. Divergent features were adopted in 14 interventions with significantly positive outcomes, such as personalized goal setting (n = 10, 71%), motivational feedback (n = 5, 36%), and alerts for health professionals (n = 3, 21%). The most significant found challenges in the development and evaluation of mHealth interventions include the design of studies with high quality, the construction of robust interventions in combination with health professional inputs, and the identification of tools and methods to improve patient adherence. CONCLUSIONS: This review found mixed evidence regarding the health benefits of mHealth interventions for patients living with chronic diseases. Further rigorous studies are needed to assess the outcomes of personalized mHealth interventions toward the optimal management of chronic diseases.
Authors: Lyndsay A Nelson; Robert A Greevy; Andrew Spieker; Kenneth A Wallston; Tom A Elasy; Sunil Kripalani; Chad Gentry; Erin M Bergner; Lauren M LeStourgeon; Sarah E Williamson; Lindsay S Mayberry Journal: Diabetes Care Date: 2020-11-05 Impact factor: 19.112