Insulin Dose Titration System Using a Short Messaging Service (SMS) Automatically Produced by a Knowledge Matrix
The investigators designed the system in type 2 diabetic patients treated with long acting insulin to produce an automatic adjustment of insulin dose based on real time glucose level data and to provide to the patients the needed insulin dose by using a short message service (SMS) and apply to the clinical practice.
|Study Design:||Allocation: Randomized
Endpoint Classification: Efficacy Study
Intervention Model: Parallel Assignment
Masking: Open Label
Primary Purpose: Supportive Care
|Official Title:||Insulin Dose Titration System in Diabetic Patients Using a Short Messaging Service Automatically Produced by a Knowledge Matrix|
- The primary objective was to compare the mean changes of A1C from baseline to end point between two groups. [ Time Frame: three months ] [ Designated as safety issue: No ]
- Secondary objectives included the proportion of patients to achieve A1C level below 7.0%; incidence of hypoglycemic episodes; change in body weight; and insulin dose. [ Time Frame: three months ] [ Designated as safety issue: Yes ]
|Study Start Date:||November 2007|
|Study Completion Date:||December 2008|
|Primary Completion Date:||November 2008 (Final data collection date for primary outcome measure)|
Experimental: insulin titration by specialized system
Insulin dose titration system by using a SMS automatically produced by a knowledge matrix
Other: Insulin dose titration system using a SMS
We applied 'Insulin dose titration system in diabetic patients using a short messaging service automatically produced by a knowledge matrix' for 12 weeks in the intervention group. In the control group, a conventional insulin titration schedule was used. The insulin used in this study was Lantus (insulin glargine).
Other Name: insulin used in this study = Lantus (insulin glargine)
Most patients with type 2 diabetes will, in time, need insulin therapy. Starting insulin poses considerable challenges. Also, improving glycemic control with insulin therapy often requires periodic dose adjustments based on glycemic response. Therefore, how to adjust their insulin doses are very important for improvement of glycemic control. Long acting insulin offers the benefit of a more consistent pharmacological dynamic with less hypoglycemia. Therefore, long acting insulin dose adjustments are widely used by patients based on simplified insulin dosing algorithms.
In the management of diabetes, it is important to maintain an intimate and continuous doctor-patient relationship. To achieve an optimal glucose level and to prevent diabetic complications, frequent contact with a medical doctor is recommended, but this causes an increased amount of medical expense. In recent years, web and phone delivery of self-management programs have emerged as popular approaches to the management of diabetes. The major focus of the system was support for blood glucose monitoring with substantive feedback from expert to help interpret results of glucose-level values. Moreover, with this system the patients could be advised to determine the amount of insulin required. However, despite of using these programs, it can take a significant amount of effort and time for physicians to look over each patient's data, formulate an appropriate message, and send it to the patients. Accordingly, computerized, knowledge-based medical treatment advice systems will provide more abundant medical advices, also can be more economic than the previous systems, in which medical personnel were required for the same process.
Recently we designed an Internet-based diabetic patient management using short message service (SMS) that was automatically produced by a knowledge matrix. Moreover, we reported this unique system has shown the great efficacy in glucose control. In this study, we designed the system in patients treated with long acting insulin to produce an automatic adjustment of insulin dose based on real time glucose level data and to provide to the patients the needed insulin dose by using a SMS and apply to the clinical practice with diabetic patients.
Please refer to this study by its ClinicalTrials.gov identifier: NCT00948584
|Principal Investigator:||Chul Sik Kim, MD, PhD||Hallym University Medical Center|