Digital health technology and diabetes management

J Diabetes. 2018 Jan;10(1):10-17. doi: 10.1111/1753-0407.12606. Epub 2017 Nov 6.

Abstract

Diabetes care is largely dependent on patient self-management and empowerment, given that patients with diabetes must make numerous daily decisions as to what to eat, when to exercise, and determine their insulin dose and timing if required. In addition, patients and providers are generating vast amounts of data from many sources, including electronic medical records, insulin pumps, sensors, glucometers, and other wearables, as well as evolving genomic, proteomic, metabolomics, and microbiomic data. Multiple digital tools and apps have been developed to assist patients to choose wisely, and to enhance their compliance by using motivational tools and incorporating incentives from social media and gaming techniques. Healthcare teams (HCTs) and health administrators benefit from digital developments that sift through the enormous amounts of patient-generated data. Data are acquired, integrated, analyzed, and presented in a self-explanatory manner, highlighting important trends and items that require attention. The use of decision support systems may propose data-driven actions that, for the most, require final approval by the patient or physician before execution and, once implemented, may improve patient outcomes. The digital diabetes clinic aims to incorporate all digital patient data and provide individually tailored virtual or face-to-face visits to those persons who need them most. Digital diabetes care has demonstrated only modest HbA1c reduction in multiple studies and borderline cost-effectiveness, although patient satisfaction appears to be increased. Better understanding of the barriers to digital diabetes care and identification of unmet needs may yield improved utilization of this evolving technology in a safe, effective, and cost-saving manner.

Keywords: big data; decision support; diabetes; digital therapy; mobile app; 决策支持; 大数据; 手机应用程序; 数字化治疗; 糖尿病.

Publication types

  • Review

MeSH terms

  • Biomedical Technology*
  • Diabetes Mellitus / therapy*
  • Disease Management
  • Humans
  • Internet / statistics & numerical data*
  • Patient Education as Topic*
  • Self Care*