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


CONCLUSIONS
This u-healthcare service provided effective management for older patients with type 2 diabetes (ClinicalTrial.Gov: NCT01137058).
Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300, Gumi-dong, Bundang-gu, Seongnam, 463-707, Korea.|Department of Medical Informatics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
Soo
S
Lim
Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300, Gumi-dong, Bundang-gu, Seongnam, 463-707, Korea.|Department of Medical Informatics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
Seon Mee
SM
Kang
Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300, Gumi-dong, Bundang-gu, Seongnam, 463-707, Korea.|Department of Medical Informatics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
Kyoung Min
KM
Kim
Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300, Gumi-dong, Bundang-gu, Seongnam, 463-707, Korea.|Department of Medical Informatics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
Jae Hoon
JH
Moon
Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300, Gumi-dong, Bundang-gu, Seongnam, 463-707, Korea.|Department of Medical Informatics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
Sung Hee
SH
Choi
Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300, Gumi-dong, Bundang-gu, Seongnam, 463-707, Korea.|Department of Medical Informatics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
Hee
H
Hwang
Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Hye Seung
HS
Jung
Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Kyong Soo
KS
Park
H3 System Research Institute, Daejeon, Korea.
Jun Oh
JO
Ryu
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.|Department of Medical Informatics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea. janghak@snu.ac.kr.
Hak Chul
HC
Jang
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001786:Blood Glucose / Q000378:metabolism; D001823:Body Composition; D003199:Computer Systems; D003924:Diabetes Mellitus, Type 2 / Q000628:therapy*; D004032:Diet; D004311:Double-Blind Method; D015444:Exercise; D005246:Feedback; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory; D057285:Precision Medicine; D017216:Telemedicine / Q000379:methods
D001786:Blood Glucose; D006442:Glycated Hemoglobin
Clinical decision support system; Telemedicine; Ubiquitous healthcare