title: An in silico method to identify computer-based protocols worthy of clinical study: An insulin infusion protocol use case.
abstract: OBJECTIVE
  Develop an efficient non-clinical method for identifying promising computer-based protocols for clinical study. An in silico comparison can provide information that informs the decision to proceed to a clinical trial. The authors compared two existing computer-based insulin infusion protocols: eProtocol-insulin from Utah, USA, and Glucosafe from Denmark.
  
  
  METHODS
  The authors used eProtocol-insulin to manage intensive care unit (ICU) hyperglycemia with intravenous (IV) insulin from 2004 to 2010. Recommendations accepted by the bedside clinicians directly link the subsequent blood glucose values to eProtocol-insulin recommendations and provide a unique clinical database. The authors retrospectively compared in silico 18,984 eProtocol-insulin continuous IV insulin infusion rate recommendations from 408 ICU patients with those of Glucosafe, the candidate computer-based protocol. The subsequent blood glucose measurement value (low, on target, high) was used to identify if the insulin recommendation was too high, on target, or too low.
  
  
  RESULTS
  Glucosafe consistently provided more favorable continuous IV insulin infusion rate recommendations than eProtocol-insulin for on target (64% of comparisons), low (80% of comparisons), or high (70% of comparisons) blood glucose. Aggregated eProtocol-insulin and Glucosafe continuous IV insulin infusion rates were clinically similar though statistically significantly different (Wilcoxon signed rank test P = .01). In contrast, when stratified by low, on target, or high subsequent blood glucose measurement, insulin infusion rates from eProtocol-insulin and Glucosafe were statistically significantly different (Wilcoxon signed rank test, P < .001), and clinically different.
  
  
  CONCLUSIONS
  This in silico comparison appears to be an efficient nonclinical method for identifying promising computer-based protocols.
  
  
  CONCLUSIONS
  Preclinical in silico comparison analytical framework allows rapid and inexpensive identification of computer-based protocol care strategies that justify expensive and burdensome clinical trials.
authors.affiliation: Department of Biomedical Informatics, Intermountain Medical Center and University of Utah School of Medicine, Salt Lake City, Utah, USA.
authors.forename: Anthony F
authors.initials: AF
authors.lastname: Wong
authors.affiliation: Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
authors.forename: Ulrike
authors.initials: U
authors.lastname: Pielmeier
authors.affiliation: Department of Biomedical Informatics, Intermountain Medical Center and University of Utah School of Medicine, Salt Lake City, Utah, USA.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Haug
authors.affiliation: Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
authors.forename: Steen
authors.initials: S
authors.lastname: Andreassen
authors.affiliation: Department of Biomedical Informatics, Intermountain Medical Center and University of Utah School of Medicine, Salt Lake City, Utah, USA Pulmonary and Critical Care Divisions, Departments of Medicine, Intermountain Medical Center and University of Utah School of Medicine, Salt Lake City, Utah, USA alan.morris@imail.org.
authors.forename: Alan H
authors.initials: AH
authors.lastname: Morris
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002985:Clinical Protocols; D003198:Computer Simulation; D004360:Drug Therapy, Computer-Assisted; D006801:Humans; D006943:Hyperglycemia / Q000188:drug therapy*; D007328:Insulin / Q000008:administration & dosage*; D007362:Intensive Care Units; D008875:Middle Aged; D055815:Young Adult
chemical_list: D007328:Insulin
keywords: comparison algorithms; computer/health; computer/informatics; preclinical investigations; preclinical/technical