Can a Tool That Automates Insulin Titration Be a Key to Diabetes Management?

Abstract

Background: Most patients who use insulin do not achieve optimal glycemic control and become susceptible to complications. Numerous clinical trials have shown that frequent insulin dosage titration is imperative to achieve glycemic control. Unfortunately, implementation of such a paradigm is often impractical. We hypothesized that the Diabetes Insulin Guidance System (DIGSÔ) (Hygieia, Inc., Ann Arbor, MI) software, which automatically advises patients on adjustment of insulin dosage, would provide safe and effective weekly insulin dosage adjustments. Subjects and Methods: In a feasibility study we enrolled patients with type 1 and type 2 diabetes, treated with a variety of insulin regimens and having suboptimal glycemic control. The 12-week intervention period followed a 4-week baseline runin period. During the intervention, DIGS processed patients' glucose readings and provided insulin dosage adjustments on a weekly basis. If approved by the study team, the adjusted insulin dosage was communicated to the patients. Insulin formulations were not changed during the study. The primary outcome was the fraction of DIGS dosage adjustments approved by the study team, and the secondary outcome was improved glycemic control. Results: Forty-six patients were recruited, and eight withdrew. The DIGS software recommended 1,734 insulin dosage adjustments, of which 1,731 (99.83%) were approved. During the run-in period the weekly average glucose was stable at 174.2 -36.7 mg/dL (9.7 -2.0 mmol/L). During the following 12 weeks, DIGS dosage adjustments resulted in progressive improvement in average glucose to 163.3 -35.1 mg/dL (9.1 -1.9 mmol/L) (P < 0.03). Mean glycosylated hemoglobin decreased from 8.4 -0.8% to 7.9 -0.9% (P < 0.05). Concomitantly, the frequency of hypoglycemia decreased by 25.2%. Conclusions: The DIGS software provided patients with safe and effective weekly insulin dosage adjustments. Widespread implementation of DIGS may improve the outcome and reduce the cost of implementing effective insulin therapy.

Evidence-based Mobile Medical Applications in Diabetes

“…These studies were published between January 2010 and August 2015, and they evaluated a total of 8 mobile medical app products: Blue Star 8,9 Diabeo, 10–12 Diabetes Diary, 13 DID, 14,15 Accu-Chek Aviva Expert, 16,17 Diabetes Insulin Guidance Systems, 18 FreeStyle InsulLinx, 19,20 and Telcare. 21 Six apps (Dexcom Share, Glooko, Accu-Chek Connect, Dario, Livongo, and Telcare) have received FDA clearance for use but do not have studies on efficacy and safety in peer-reviewed literature.…”

Role of Automation/Technology in Day-to-Day Diabetes Care

“…A feasibility study with a learning algorithm showed improvement in HbA1c, mean glucose level, and hypoglycemia. 11 Future studies should also include assessments of adherence and additional reasons for heterogeneity in results such as the inclusion of bolus reminders along with the bolus calculator in some of the RCTs but not in all.…”

Devices to Support Treatment Decisions in Type 1 Diabetes: The Diabeo System

“…Clearly these systems, which require further evaluation, can help patients, especially those with poor numeracy; however, they cannot overcome the more serious issue of acceptance by patients of their disease. patients with type 2 diabetes on basal-bolus therapy, and (3) patients with type 2 diabetes treated with twice-daily biphasic insulin [14]. During the 12-week intervention period, DIGS processed patients' glucose readings and provided insulin dosage adjustments on a weekly basis.…”