Skip to search boxSkip to navigationSkip to main content

Review of mobile applications for optimizing the follow-up care of patients with diabetes

  • Nikolaos Th Ersotelos
    ,
  • Andrew N. Margioris
    ,
  • Xu Zhang
    ,
  • Feng Dong
  • University of Crete
    ,
  • University of Bedfordshire
Research Output: Contribution to journal Article Peer-review

Open access

Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well

Abstract

Several smartphone applications aim at facilitating communication between patients and healthcare providers. In this review, we evaluate and compare the most promising applications in the field of diabetes mellitus (DM) and obesity. Most applications monitor body weight, fasting or postprandial blood glucose, glycosylated hemoglobin (Hgb) A1c (HgbA1c), and units and types of insulin used. Nine clinically tested applications and two Web platforms were grouped into three categories that were evaluated and compared. Group 1 included seven applications focusing mainly on monitoring DM, fitness and weight, blood glucose levels, and HbA1c. Group 2 included two applications that focus on insulin dosage calculators and glucose self-monitoring tests. Group 3 included two web-platforms that interact with patients via SMS (short message service) messaging. A common feature of the applications examined was the limited number of clinical parameters tested, the small number of subjects taking part in the evaluation, and the fact that the controls were not randomized. Furthermore, the interfaces of the applications varied and were not standardized. Finally, another common characteristic across applications was the lack of standardization of the interface and the overall structure due to language barriers, the devices usually having been designed around a specific language. Lastly, most applications lacked a critical mass of evaluators and were thus not worthy of being considered of serious clinical relevance. The current smartphone applications for DM are characterized by a limited number of participants, a small number of parameters, and a lack of standardization. BACKGROUND METHODS RESULTS CONCLUSIONS

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 541-550 (10 pages)

Journal (Volume, Issue Number)

Hormones (Volume 17, Issue 4)

Publication milestones

  • Published - 13/10/2018

Publication status

Published - 13/10/2018

ISSN

1109-3099

External Publication IDs

  • handle.net: 10547/623044
  • Scopus: 85058643424
  • PubMed: 30317460

Access to documents

Publication metrics

Metrics

Download statistics
Download count
3