• Zhilian Huang, Elaine Lum, Geronimo Jimenez, Monika Semwal, Peter Sloot, and Josip Car.
• Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Level 18, 11 Mandalay Road, Singapore, 308232, Singapore. ZHUANG014@e.ntu.edu.sg.
• Bmc Med. 2019 Jul 17; 17 (1): 127127.

BackgroundSmartphone apps are becoming increasingly popular for supporting diabetes self-management. A key aspect of diabetes self-management is appropriate medication-taking. This study aims to systematically assess and characterise the medication management features in diabetes self-management apps and their congruence with best-practice evidence-based criteria.MethodsThe Google Play and Apple app stores were searched in June 2018 using diabetes-related terms in the English language. Apps with both medication and blood glucose management features were downloaded and evaluated against assessment criteria derived from international medication management and diabetes guidelines.ResultsOur search yielded 3369 Android and 1799 iOS potentially relevant apps; of which, 143 apps (81 Android, 62 iOS) met inclusion criteria and were downloaded and assessed. Over half 58.0% (83/143) of the apps had a medication reminder feature; 16.8% (24/143) had a feature to review medication adherence; 39.9% (57/143) allowed entry of medication-taking instructions; 5.6% (8/143) provided information about medication; and 4.2% (6/143) displayed motivational messages to encourage medication-taking. Only two apps prompted users on the use of complementary medicine. Issues such as limited medication logging capacity, faulty reminder features, unclear medication adherence assessment, and visually distracting excessive advertising were observed during app assessments.ConclusionsA large proportion of diabetes self-management apps lacked features for enhancing medication adherence and safety. More emphasis should be given to the design of medication management features in diabetes apps to improve their alignment to evidence-based best practice.

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