title: Automated glycemic pattern analysis can improve health care professional efficiency and accuracy.
abstract: BACKGROUND
  Health care professionals (HCPs) routinely review handwritten blood glucose (BG) logbooks during office visits of patients with diabetes.
  
  
  METHODS
  In this study, 64 HCPs were asked to assess glycemic patterns and estimate BG averages in six simulated handwritten logbooks. The HCPs then reviewed the pattern logs and averages in six OneTouch® Verio™IQ meters containing corresponding data sets.
  
  
  RESULTS
  The average time needed for pattern review was 7.3 min for handwritten logbooks versus 0.9 min using the meter. The total error rate for logbook pattern identification was 43.0% compared with the meter. The mean percentage deviation between HCP estimates of 30-day BG averages and actual values was 14.5%.
  
  
  CONCLUSIONS
  The meter is associated with faster and more accurate pattern analysis compared with handwritten logbooks.
authors: LifeScan Inc., West Chester, Pennsylvania 19380, USA. LKatz3@its.jnj.com
authors: Laurence B
authors: LB
authors: Katz
authors: Riad G
authors: RG
authors: Dirani
authors: Gang
authors: G
authors: Li
authors: Randee A
authors: RA
authors: Randoll
authors: John J
authors: JJ
authors: Mahoney
mesh_terms: D001331:Automation; D015190:Blood Glucose Self-Monitoring / Q000379:methods*; D003922:Diabetes Mellitus, Type 1 / Q000097:blood*; D004526:Efficiency; D006282:Health Personnel; D006801:Humans