title: A toolbox to improve algorithms for insulin-dosing decision support.
abstract: BACKGROUND
  Standardized insulin order sets for subcutaneous basal-bolus insulin therapy are recommended by clinical guidelines for the inpatient management of diabetes. The algorithm based GlucoTab system electronically assists health care personnel by supporting clinical workflow and providing insulin-dose suggestions.
  
  
  OBJECTIVE
  To develop a toolbox for improving clinical decision-support algorithms.
  
  
  METHODS
  The toolbox has three main components. 1) Data preparation: Data from several heterogeneous sources is extracted, cleaned and stored in a uniform data format. 2) Simulation: The effects of algorithm modifications are estimated by simulating treatment workflows based on real data from clinical trials. 3) ANALYSIS: Algorithm performance is measured, analyzed and simulated by using data from three clinical trials with a total of 166 patients.
  
  
  RESULTS
  Use of the toolbox led to algorithm improvements as well as the detection of potential individualized subgroup-specific algorithms.
  
  
  CONCLUSIONS
  These results are a first step towards individualized algorithm modifications for specific patient subgroups.
authors.affiliation: HEALTH - Institute for Biomedicine and Health Sciences, JOANNEUM RESEARCH Forschungsgesellschaft mbH , Graz, Austria.
authors.forename: K
authors.initials: K
authors.lastname: Donsa
authors.affiliation: HEALTH - Institute for Biomedicine and Health Sciences, JOANNEUM RESEARCH Forschungsgesellschaft mbH , Graz, Austria.
authors.forename: P
authors.initials: P
authors.lastname: Beck
authors.affiliation: Division of Endocrinology and Metabolism, Department of Internal Medicine, Medical University of Graz , Graz, Austria.
authors.forename: J
authors.initials: J
authors.lastname: Plank
authors.affiliation: Division of Endocrinology and Metabolism, Department of Internal Medicine, Medical University of Graz , Graz, Austria.
authors.forename: L
authors.initials: L
authors.lastname: Schaupp
authors.affiliation: Division of Endocrinology and Metabolism, Department of Internal Medicine, Medical University of Graz , Graz, Austria.
authors.forename: J K
authors.initials: JK
authors.lastname: Mader
authors.affiliation: HEALTH - Institute for Biomedicine and Health Sciences, JOANNEUM RESEARCH Forschungsgesellschaft mbH , Graz, Austria.
authors.forename: T
authors.initials: T
authors.lastname: Truskaller
authors.affiliation: HEALTH - Institute for Biomedicine and Health Sciences, JOANNEUM RESEARCH Forschungsgesellschaft mbH , Graz, Austria.
authors.forename: B
authors.initials: B
authors.lastname: Tschapeller
authors.affiliation: HEALTH - Institute for Biomedicine and Health Sciences, JOANNEUM RESEARCH Forschungsgesellschaft mbH , Graz, Austria.
authors.forename: B
authors.initials: B
authors.lastname: Höll
authors.affiliation: HEALTH - Institute for Biomedicine and Health Sciences, JOANNEUM RESEARCH Forschungsgesellschaft mbH , Graz, Austria.
authors.forename: S
authors.initials: S
authors.lastname: Spat
authors.affiliation: HEALTH - Institute for Biomedicine and Health Sciences, JOANNEUM RESEARCH Forschungsgesellschaft mbH , Graz, Austria ; Division of Endocrinology and Metabolism, Department of Internal Medicine, Medical University of Graz , Graz, Austria.
authors.forename: T R
authors.initials: TR
authors.lastname: Pieber
mesh_terms: D000465:Algorithms; D001786:Blood Glucose / Q000378:metabolism; D020000:Decision Support Systems, Clinical; D054796:Drug Dosage Calculations; D006801:Humans; D007328:Insulin / Q000008:administration & dosage* / Q000494:pharmacology; D008991:Monitoring, Physiologic
chemical_list: D001786:Blood Glucose; D007328:Insulin
keywords: algorithms; clinical decision support systems; computer simulation; diabetes mellitus type 2; workflow