title: 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 (DIGS™) (Hygieia, Inc., Ann Arbor, MI) software, which automatically advises patients on adjustment of insulin dosage, would provide safe and effective weekly insulin dosage adjustments.
  
  
  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 run-in 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.
authors.affiliation: International Diabetes Center at Park Nicollet , Minneapolis, Minnesota, USA.
authors.forename: Richard M
authors.initials: RM
authors.lastname: Bergenstal
authors.forename: Eran
authors.initials: E
authors.lastname: Bashan
authors.forename: Margaret
authors.initials: M
authors.lastname: McShane
authors.forename: Mary
authors.initials: M
authors.lastname: Johnson
authors.forename: Israel
authors.initials: I
authors.lastname: Hodish
mesh_terms: D000328:Adult; D000368:Aged; D001786:Blood Glucose / Q000378:metabolism*; D015190:Blood Glucose Self-Monitoring; D003362:Cost-Benefit Analysis; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000188:drug therapy* / Q000191:economics; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000188:drug therapy* / Q000191:economics; D004305:Dose-Response Relationship, Drug; D004334:Drug Administration Schedule; D054796:Drug Dosage Calculations; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage*; D007328:Insulin / Q000008:administration & dosage*; D008297:Male; D008875:Middle Aged; D017060:Patient Satisfaction; D011446:Prospective Studies; D012984:Software; D016896:Treatment Outcome; D014481:United States; D055815:Young Adult
chemical_list: D001786:Blood Glucose; D007004:Hypoglycemic Agents; D007328:Insulin