Digital Integrated Healthcare Platform in Patients With Type 2 Diabetes

• ClinicalTrials.gov Identifier: NCT04161170
• Recruitment Status: Unknown
• First Posted: November 13, 2019
• Last Update Posted: January 18, 2020
• Sponsor: Samsung Medical Center
• Information provided by (Responsible Party): Jae Hyeon Kim, MD, PhD, Samsung Medical Center

Study Description

Brief Summary:

In this three multicenter clinical trial, investigators will study the efficacy of digital integrated healthcare platform and CGMS (continuous glucose monitoring system) on diabetes management in patients with Type 2 diabetes. The platform is based on monitoring and intervention by medical staff using AI (aritificial intelligence)-based diet management solution.

The study group includes 3 groups; a total of 294 participants with 1:1:1 randomized allocation: Control group A (no intervention and conventional diabetes management with regular outpatiant clinic visit every 3 months), Interventional group B (applying digital integrated healthcare platform by themselves, no monitoring and intervention by medical staff), and Interventional group C (applying digital integrated healthcare platform based on monitoring and intervention by medical staff using AI-based diet management solution and applying CGMS).

This parallel study will be conducted for 48 weeks.

Condition or disease	Intervention/treatment	Phase
Type 2 Diabetes	Device: Digital integrated healthcare platform	Not Applicable

Detailed Description:

The reason why it is difficult to improve the lifestyle of patients with diabetes using existing digital healthcare applications (apps) is that there is a limit of sustainability that most people do not continue to use digital healthcare apps, thus, it can be possible only with monitoring and intervention by medical staff.

Not only users, but also medical staff can access integrated biometric data on the digital integrated healthcare platform so that individual patient-specific management systems that monitor and intervene can continuously motivate patients to manage themselves. Also, it could be a prerequisite for the successful management of patients with diabetes using digital healthcare apps, many existing apps have been identified as failure cases in previous studies. In this clinical trial, investigators will study the efficacy of digital integrated healthcare platform based on monitoring and intervention by medical staff using AI (aritifical intelligence)-based diet management solution.

In addition, in this clinical trial, the latest medical device, real-time continuous glucose monitoring system (CGMS) will be applied to monitor blood glucose levels. It has been reported that glucose level is well controlled when the number of self blood glucose measurement is performed frequently, but in practice, patients have time and space limitation in self blood glucose measurement, and it is difficult to change the management pattern of patients by encouraging self blood glucose measurement. Therefore, by applying a CGMS every three months, not only the patient but also the medical staff can access the 24-hour blood glucose values, and can actively participate in the blood sugar management of the patients. Therefore, investigators plan to conduct clinical trial using digital integrated healthcare platform using AI-based diet management solution and real-time CGMS

Study Design

• Study Type: Interventional (Clinical Trial)
• Estimated Enrollment: 294 participants
• Allocation: Randomized
• Intervention Model: Parallel Assignment
• Intervention Model Description: Control group A: no intervention Interventional group B: digital integrated healthcare platform Interventional group C: digital integrated healthcare platform + CGMS apply + medical team monitoring + educational intervation
• Masking: None (Open Label)
• Primary Purpose: Treatment
• Official Title: Validation of Diabetes Management Effectiveness of Digital Integrated Healthcare Platform Utilizing AI-based Dietary Management Solution and Real-time Continuous Glucose Monitoring System
• Actual Study Start Date: November 20, 2019
• Estimated Primary Completion Date: August 31, 2021
• Estimated Study Completion Date: December 31, 2021

Arms and Interventions

Arm	Intervention/treatment
No Intervention: Control A; no intervention conventional diabetes treatment and clinic visit every 3 months
Active Comparator: Intervention B; apply digital integrated healthcare platform clinic visit every 3 months	Device: Digital integrated healthcare platform; Digital Integrated Healthcare Platform Utilizing AI-based Dietary Management Solution and Real-time Continuous Glucose Monitoring system
Experimental: Intervention C; apply digital integrated healthcare platform, CGMS, and medical team monitoring, and education clinic visit every 3 months	Device: Digital integrated healthcare platform; Digital Integrated Healthcare Platform Utilizing AI-based Dietary Management Solution and Real-time Continuous Glucose Monitoring system

Outcome Measures

Primary Outcome Measures :

1. Change of HbA1c (glycated hemoglobin) at 6months from baseline [ Time Frame: Change of HbA1c (glycated hemoglobin) at 6months from baseline ]
   Change of HbA1c (glycated hemoglobin) at 6months from baseline

Secondary Outcome Measures :

1. HbA1c [ Time Frame: glycated hemoglobin at baseline, 3, 6, 12 months ]
   glycated hemoglobin
2. number of intervention for education in interventinal group C [ Time Frame: number of intervention for education in interventinal group C at baseline, 3, 6, 12 months ]
   The number of educational intervention by digital integrated healthcare platform
3. hypoglycemic events [ Time Frame: hypoglycemic events at baseline, 3, 6, 12 months ]
   the number of hypoglycemic events
4. adverse events [ Time Frame: adverse events at baseline, 3, 6, 12 months ]
   the number and types of hypoglycemic events
5. patient satisfaction questionnaire score [ Time Frame: patient satisfaction questionnaire score at baseline, 3, 6, 12 months ]
   patient satisfaction questionnaire score includes 8 questions and each question has score range 0 (min) - 6 (max). For questions number 2 and 3, higher score mean worse outcome in hypoglycemia but for the rest of questions, higher scores mean better outcome in diabetes management.
6. body weight [ Time Frame: body weight at baseline, 3, 6, 12 months ]
   body weight
7. BMI (body mass index) [ Time Frame: BMI at baseline, 3, 6, 12 months ]
   BMI (body mass index)
8. body fat (%) [ Time Frame: body fat (%) at baseline, 3, 6, 12 months ]
   body fat (%)
9. step count [ Time Frame: average step count at baseline, 3, 6, 12 months ]
   step count
10. burned calories [ Time Frame: average burned calories at baseline, 3, 6, 12 months ]
    burned calories
11. walking distances [ Time Frame: average walking distances at baseline, 3, 6, 12 months ]
    walking distances
12. intake calories [ Time Frame: intake calories at baseline, 3, 6, 12 months ]
    intake calories
13. fasting glucose level [ Time Frame: average fasting glucose level at baseline, 3, 6, 12 months ]
    fasting glucose level
14. total cholesterol level [ Time Frame: total cholesterol level at baseline, 3, 6, 12 months ]
    total cholesterol level
15. HDL cholesterol level [ Time Frame: HDL cholesterol level at baseline, 3, 6, 12 months ]
    HDL cholesterol level
16. Triglycerides level [ Time Frame: Triglycerides level at baseline, 3, 6, 12 months ]
    Triglycerides level
17. LDL cholesterol level [ Time Frame: LDL cholesterol level at baseline, 3, 6, 12 months ]
    LDL cholesterol level
18. mean glucose level by CGMS (continuous glucose monitoring system) in interventional group C [ Time Frame: mean glucose level by CGMS at baseline, 3, 6, 12 months ]
    mean glucose level by CGMS in interventional group C
19. glycemic variability by CGMS in interventional group C [ Time Frame: glycemic variability by CGMS at baseline, 3, 6, 12 months ]
    glycemic variability by CGMS in interventional group C
20. standard deviation by CGMS in interventional group C [ Time Frame: standard deviation by CGMS at baseline, 3, 6, 12 months ]
    standard deviation by CGMS in interventional group C
21. average applying time of CGMS in interventional group C [ Time Frame: average applying time of CGMS at baseline, 3, 6, 12 months ]
    average applying time of CGMS in interventional group C
22. time in range of <54mg/dL by CGMS in interventional group C [ Time Frame: time in range of <54mg/dL by CGMS at baseline, 3, 6, 12 months ]
    time in range of <54mg/dL by CGMS in interventional group C
23. time in range of <70mg/dL by CGMS in interventional group C [ Time Frame: time in range of <70mg/dL by CGMS at baseline, 3, 6, 12 months ]
    time in range of <70mg/dL by CGMS in interventional group C
24. time in range of 70-180 mg/dL by CGMS in interventional group C [ Time Frame: time in range of 70-180 mg/dL by CGMS at baseline, 3, 6, 12 months ]
    time in range of 70-180 mg/dL by CGMS in interventional group C
25. time in range of >180 mg/dL by CGMS in interventional group C [ Time Frame: time in range of >180 mg/dL by CGMS at baseline, 3, 6, 12 months ]
    time in range of >180 mg/dL by CGMS in interventional group C
26. time in range of >250 mg/dL by CGMS in interventional group C [ Time Frame: time in range of >250 mg/dL by CGMS at baseline, 3, 6, 12 months ]
    time in range of >250 mg/dL by CGMS in interventional group C

Eligibility Criteria

• Ages Eligible for Study: 19 Years to 70 Years (Adult, Older Adult)
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes

Criteria

Inclusion Criteria:

• 19~70 aged patients with type 2 diabetes
• Patients who have not taken diabetic medications for more than 4 weeks and patients who have taken at least one type of oral hypoglycemic agents at same dosage for more than 12 weeks
• Those who have glycated hemoglobin within 7.0% to 8.5% within the last 3 months
• overweight or obese: BMI (body mass index) ≥ 23 kg / m2
• Those who have agreed to use medical record and participate research by applying the digital integrated healthcare platform
• Those who voluntarily signed the consent form after listening the explanation of the clinical trial.

Exclusion Criteria:

• Diabetes other than type 2 diabetes, including type 1 diabetes and gestational diabetes
• Those who are receiving insulin or GLP-1 agonist other than oral hypoglycemic agents
• Uncontrolled chronic liver disease (hemochromatosis, liver cancer, autoimmune liver disease, cirrhosis of the liver, viral hepatitis-includes all A, B and C, Wilson's disease)
• Those with acute renal failure (up to 1.5 times higher than existing serum creatinine)
• Those with mental illness (schizophrenia, depression, bipolar disorder, etc.)
• Those who are currently taking weight loss agents
• Those who had alcohol or drug addiction within the last three months
• Those who are taking medications that may affect glucose metabolism (eg, corticosteroids, immunoreactive drugs, etc.)
• Those who are pregnant or lactating and planning to become pregnant during the clinical trial (women of childbearing age may agree to the contraceptive plan).
• Those who are deemed inappropriate for participation in clinical trials

Contacts and Locations

Contacts

Contact: Jae Hyeon Kim, MD PhD; +82-2-3410-1580; jaehyeonmd.kim@samsung.com

Locations

Korea, Republic of

Samsung Medical Center; Recruiting

Seoul, Korea, Republic of, 135-710

Contact: Jae Hyeon Kim, M.D.,Ph. D 82-2-3410-1580 jaehyeonmd.kim@samsung.com

Sponsors and Collaborators

Samsung Medical Center

Investigators

• Principal Investigator: Jae Hyeon Kim, MD PhD; Samsung Medical Center

More Information

Publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):

Park SW, Kim G, Hwang YC, Lee WJ, Park H, Kim JH. Validation of the effectiveness of a digital integrated healthcare platform utilizing an AI-based dietary management solution and a real-time continuous glucose monitoring system for diabetes management: a randomized controlled trial. BMC Med Inform Decis Mak. 2020 Jul 10;20(1):156. doi: 10.1186/s12911-020-01179-x.

• Responsible Party: Jae Hyeon Kim, MD, PhD, Professor, Samsung Medical Center
• ClinicalTrials.gov Identifier: NCT04161170
• Other Study ID Numbers: 2019-05-028-007
• First Posted: November 13, 2019
• Last Update Posted: January 18, 2020
• Last Verified: January 2020

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: No

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Jae Hyeon Kim, MD, PhD, Samsung Medical Center:

Continuous glucose monitoring system; Artificial intelligence; Diabetes; Digital healthcare; Education

Additional relevant MeSH terms:

Diabetes Mellitus; Diabetes Mellitus, Type 2; Glucose Metabolism Disorders; Metabolic Diseases; Endocrine System Diseases