title: Impact of remote management of diabetes via computer: the 360 study--a proof-of-concept randomized trial.
abstract: BACKGROUND
  Previous studies have provided limited guidance regarding the clinical efficacy and cost-effectiveness of interventions using "telemedicine" models in the management of diabetes mellitus. We conducted a study to determine if routine clinical assessments of diabetes patients could be effectively conducted via computer and telephone interaction with patients and still provide clinical results similar to traditional office care.
  
  
  METHODS
  We enrolled 100 subjects with diabetes in this 12-month, randomized, controlled, non-inferiority study. Subjects were randomized (1:1 ratio) to a control group (CG) or study group (SG). Baseline characteristics were similar. CG subjects participated in quarterly office visits; SG subjects participated in two office visits (months 6 and 12) and two telemedicine interactions (months 3 and 9). Changes in clinical measurements (hemoglobin A1c [HbA1c], blood pressure, lipids, body mass index [BMI], and body weight) and clinician time requirements were assessed.
  
  
  RESULTS
  Seventy subjects completed the study (CG, n=37; SG, n=33). No significant between-group differences in HbA1c, blood pressure, lipids, or BMI were seen at 12 months. SG subjects showed significantly greater reductions in mean (SD) body weight compared with CG subjects: -5.2 (1.6) pounds versus -0.7 (1.5) pounds, respectively (P=0.04). Clinician time requirements for SG subjects were reduced by >40%.
  
  
  CONCLUSIONS
  Our study demonstrated that use of a telemedicine-based treatment protocol in diabetes patients is feasible and efficient and yields similar clinical outcomes compared with traditional, clinic-based protocols. Telemedicine applications of computer software can potentially expand access to care for patients and may reduce costs for patients, providers, and payers.
authors.affiliation: Center for Diabetes and Metabolism, Columbus, GA 31904, USA. Sugardoc6@aol.com
authors.forename: Steven B
authors.initials: SB
authors.lastname: Leichter
authors.forename: Kelly
authors.initials: K
authors.lastname: Bowman
authors.forename: Royce A
authors.initials: RA
authors.lastname: Adkins
authors.forename: Zhihong
authors.initials: Z
authors.lastname: Jelsovsky
mesh_terms: D000328:Adult; D000368:Aged; D001786:Blood Glucose / Q000378:metabolism*; D015190:Blood Glucose Self-Monitoring / Q000379:methods*; D015992:Body Mass Index; D001835:Body Weight; D003201:Computers; D003362:Cost-Benefit Analysis; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000453:epidemiology* / Q000628:therapy; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000453:epidemiology* / Q000628:therapy; D005240:Feasibility Studies; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism*; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage; D007328:Insulin / Q000008:administration & dosage; D008055:Lipids / Q000097:blood; D008297:Male; D008875:Middle Aged; D010349:Patient Compliance / Q000706:statistics & numerical data; D017216:Telemedicine / Q000191:economics; D013689:Telephone; D014481:United States / Q000453:epidemiology
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; D007328:Insulin; D008055:Lipids; C517652:hemoglobin A1c protein, human