Features of mobile diabetes applications: review of the literature and analysis of current applications compared against evidence-based guidelines
- PMID: 21979293
- PMCID: PMC3222161
- DOI: 10.2196/jmir.1874
Features of mobile diabetes applications: review of the literature and analysis of current applications compared against evidence-based guidelines
Abstract
Background: Interest in mobile health (mHealth) applications for self-management of diabetes is growing. In July 2009, we found 60 diabetes applications on iTunes for iPhone; by February 2011 the number had increased by more than 400% to 260. Other mobile platforms reflect a similar trend. Despite the growth, research on both the design and the use of diabetes mHealth applications is scarce. Furthermore, the potential influence of social media on diabetes mHealth applications is largely unexplored.
Objective: Our objective was to study the salient features of mobile applications for diabetes care, in contrast to clinical guideline recommendations for diabetes self-management. These clinical guidelines are published by health authorities or associations such as the National Institute for Health and Clinical Excellence in the United Kingdom and the American Diabetes Association.
Methods: We searched online vendor markets (online stores for Apple iPhone, Google Android, BlackBerry, and Nokia Symbian), journal databases, and gray literature related to diabetes mobile applications. We included applications that featured a component for self-monitoring of blood glucose and excluded applications without English-language user interfaces, as well as those intended exclusively for health care professionals. We surveyed the following features: (1) self-monitoring: (1.1) blood glucose, (1.2) weight, (1.3) physical activity, (1.4) diet, (1.5) insulin and medication, and (1.6) blood pressure, (2) education, (3) disease-related alerts and reminders, (4) integration of social media functions, (5) disease-related data export and communication, and (6) synchronization with personal health record (PHR) systems or patient portals. We then contrasted the prevalence of these features with guideline recommendations.
Results: The search resulted in 973 matches, of which 137 met the selection criteria. The four most prevalent features of the applications available on the online markets (n = 101) were (1) insulin and medication recording, 63 (62%), (2) data export and communication, 61 (60%), (3) diet recording, 47 (47%), and (4) weight management, 43 (43%). From the literature search (n = 26), the most prevalent features were (1) PHR or Web server synchronization, 18 (69%), (2) insulin and medication recording, 17 (65%), (3) diet recording, 17 (65%), and (4) data export and communication, 16 (62%). Interestingly, although clinical guidelines widely refer to the importance of education, this is missing from the top functionalities in both cases.
Conclusions: While a wide selection of mobile applications seems to be available for people with diabetes, this study shows there are obvious gaps between the evidence-based recommendations and the functionality used in study interventions or found in online markets. Current results confirm personalized education as an underrepresented feature in diabetes mobile applications. We found no studies evaluating social media concepts in diabetes self-management on mobile devices, and its potential remains largely unexplored.
Conflict of interest statement
None declared
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References
-
- Lim S, Kang SM, Shin H, Lee HJ, Won Yoon J, Yu SH, Kim SY, Yoo SY, Jung HS, Park KS, Ryu JO, Jang HC. Improved glycemic control without hypoglycemia in elderly diabetic patients using the ubiquitous healthcare service, a new medical information system. Diabetes Care. 2011 Feb;34(2):308–13. doi: 10.2337/dc10-1447. http://care.diabetesjournals.org/cgi/pmidlookup?view=long&pmid=2127018834/2/308 - DOI - PMC - PubMed
-
- Lim S, Kim SY, Kim JI, Kwon MK, Min SJ, Yoo SY, Kang SM, Kim HI, Jung HS, Park KS, Ryu JO, Shin H, Jang HC. A survey on ubiquitous healthcare service demand among diabetic patients. Diabetes Metab J. 2011 Feb;35(1):50–7. doi: 10.4093/dmj.2011.35.1.50. http://e-dmj.org/DOIx.php?id=10.4093/dmj.2011.35.1.50 - DOI - PMC - PubMed
-
- Lyles CR, Harris LT, Le T, Flowers J, Tufano J, Britt D, Hoath J, Hirsch IB, Goldberg HI, Ralston JD. Qualitative evaluation of a mobile phone and web-based collaborative care intervention for patients with type 2 diabetes. Diabetes Technol Ther. 2011 May;13(5):563–9. doi: 10.1089/dia.2010.0200. - DOI - PubMed
-
- Giménez-Pérez G, Gallach M, Acera E, Prieto A, Carro O, Ortega E, González-Clemente JM, Mauricio D. Evaluation of accessibility and use of new communication technologies in patients with type 1 diabetes mellitus. J Med Internet Res. 2002 Dec;4(3):E16. doi: 10.2196/jmir.4.3.e16. http://www.jmir.org/2002/3/e16/ - DOI - PMC - PubMed
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