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Acta Diabetol. 2016 Apr;53(2):189-98. doi: 10.1007/s00592-015-0754-8. Epub 2015 May 5.

Multifactorial intervention in diabetes care using real-time monitoring and tailored feedback in type 2 diabetes.

Author information

1
Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300, Gumi-dong, Bundang-gu, Seongnam, 463-707, Korea.
2
Department of Medical Informatics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
3
Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
4
H3 System Research Institute, Daejeon, Korea.
5
Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300, Gumi-dong, Bundang-gu, Seongnam, 463-707, Korea. janghak@snu.ac.kr.
6
Department of Medical Informatics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea. janghak@snu.ac.kr.

Abstract

AIMS:

In 2011, we demonstrated that an individualized health management system employing advanced medical information technology, designated ubiquitous (u)-healthcare, was helpful in achieving glycemic control without hypoglycemia in patients with diabetes. Following this, we generated a new multidisciplinary u-healthcare system by upgrading our clinical decision support system (CDSS) rule engine and integrating a physical activity-monitoring device and dietary feedback into a comprehensive package.

METHODS:

In a randomized, controlled clinical trial, patients with type 2 diabetes aged over 60 years were assigned randomly to a self-monitored blood glucose (SMBG) group (N = 50) or u-healthcare group (N = 50) for 6 months. The primary endpoint was the proportion of patients achieving glycated hemoglobin (HbA1c) <7 % without hypoglycemia. Changes in body composition and lipid profiles were also investigated. The u-healthcare group was educated to use a specially designed glucometer and an activity monitor that automatically transferred test results to a hospital-based server. An automated CDSS rule engine generated and sent patient-specific messages about glucose, diet, and physical activity to their mobile phones and a Web site.

RESULTS:

After 6 months of follow-up, the HbA1c level was significantly decreased in the u-healthcare group [8.0 ± 0.7 % (64.2 ± 8.8 mmol/mol) to 7.3 ± 0.9 % (56.7 ± 9.9 mmol/mol)] compared with the SMBG group [8.1 ± 0.8 % (64.9 ± 9.1 mmol/mol) to 7.9 ± 1.2 % (63.2 ± 12.3 mmol/mol)] (P < 0.01). The proportion of patients with HbA1c < 7 % without hypoglycemia was greater in the u-healthcare group (26 %) than in the SMBG group (12 %; P < 0.05). Body fat mass decreased and lipid profiles improved in the u-healthcare group but not in the SMBG group.

CONCLUSION:

This u-healthcare service provided effective management for older patients with type 2 diabetes (ClinicalTrial.Gov: NCT01137058).

KEYWORDS:

Clinical decision support system; Telemedicine; Ubiquitous healthcare

PMID:
25936739
DOI:
10.1007/s00592-015-0754-8
[Indexed for MEDLINE]

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