title: Data entry errors and design for model-based tight glycemic control in critical care.
abstract: BACKGROUND
  Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. Model-based methods and computerized protocols offer the opportunity to improve TGC quality but require human data entry, particularly of blood glucose (BG) values, which can be significantly prone to error. This study presents the design and optimization of data entry methods to minimize error for a computerized and model-based TGC method prior to pilot clinical trials.
  
  
  METHODS
  To minimize data entry error, two tests were carried out to optimize a method with errors less than the 5%-plus reported in other studies. Four initial methods were tested on 40 subjects in random order, and the best two were tested more rigorously on 34 subjects. The tests measured entry speed and accuracy. Errors were reported as corrected and uncorrected errors, with the sum comprising a total error rate. The first set of tests used randomly selected values, while the second set used the same values for all subjects to allow comparisons across users and direct assessment of the magnitude of errors. These research tests were approved by the University of Canterbury Ethics Committee.
  
  
  RESULTS
  The final data entry method tested reduced errors to less than 1-2%, a 60-80% reduction from reported values. The magnitude of errors was clinically significant and was typically by 10.0 mmol/liter or an order of magnitude but only for extreme values of BG < 2.0 mmol/liter or BG > 15.0-20.0 mmol/liter, both of which could be easily corrected with automated checking of extreme values for safety.
  
  
  CONCLUSIONS
  The data entry method selected significantly reduced data entry errors in the limited design tests presented, and is in use on a clinical pilot TGC study. The overall approach and testing methods are easily performed and generalizable to other applications and protocols.
authors.affiliation: Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Christchurch, New Zealand.
authors.forename: Logan
authors.initials: L
authors.lastname: Ward
authors.forename: James
authors.initials: J
authors.lastname: Steel
authors.forename: Aaron
authors.initials: A
authors.lastname: Le Compte
authors.forename: Alicia
authors.initials: A
authors.lastname: Evans
authors.forename: Chia-Siong
authors.initials: CS
authors.lastname: Tan
authors.forename: Sophie
authors.initials: S
authors.lastname: Penning
authors.forename: Geoffrey M
authors.initials: GM
authors.lastname: Shaw
authors.forename: Thomas
authors.initials: T
authors.lastname: Desaive
authors.forename: J Geoffrey
authors.initials: JG
authors.lastname: Chase
mesh_terms: D001786:Blood Glucose / Q000032:analysis / Q000378:metabolism*; D003201:Computers; D003422:Critical Care / Q000379:methods* / Q000592:standards; D016638:Critical Illness / Q000628:therapy*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods / Q000592:standards*; D019300:Medical Errors / Q000517:prevention & control; D008962:Models, Theoretical; D008991:Monitoring, Physiologic / Q000295:instrumentation / Q000379:methods; D010865:Pilot Projects; D012107:Research Design / Q000592:standards*; D013269:Stochastic Processes; D014110:Touch / Q000502:physiology; D014584:User-Computer Interface
chemical_list: D001786:Blood Glucose