Insulin Dose Titration System Using a Short Messaging Service (SMS) Automatically Produced by a Knowledge Matrix

Insulin Dose Titration System Using a Short Messaging Service (SMS) Automatically Produced by a Knowledge Matrix

Insulin Dose Titration System in Diabetic Patients Using a Short Messaging Service 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.

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.

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).

The primary objective was to compare the mean changes of A1C from baseline to end point between two groups.

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.

Inclusion Criteria: patients with type 2 diabetes suboptimally controlled on their previous antidiabetic treatment were included age ≥ 18 years on antidiabetic treatment (any oral and/or insulin therapy) for > 6 months A1C levels > 7.0 and < 12.0% BMI values < 35 kg/m2 Exclusion Criteria: type 1 diabetes renal dysfunction (defined as creatinine blood level > 2.0 mg/dL) hepatic dysfunction (defined as alanine aminotransferase and/or aspartate aminotransferase blood level > 2.5 times the upper normal limit) hypoglycemic unawareness pregnancy severe retinopathy illiteracy elderly over than 70 yrs