title: Developing optimized automated rule sets for reporting hemolysis, icterus and lipemia based on a priori outcomes analysis.
abstract: BACKGROUND
  There is limited information about the effects of instituting CLSI Document C56A recommended workflows for the automated detection of hemolysis, lipemia and icterus (HIL) in different clinical laboratories and patient populations. We describe a process to develop and tailor automated reporting rules that are appropriate for the local laboratory population.
  
  
  METHODS
  Automated decision algorithms were generated and applied to 2 high volume labs serving community and hospital populations. Proposed rules were applied to the datasets offline to predict the outcomes, and then were further optimized prior to implementation.
  
  
  RESULTS
  Introduction of automated serum indices decreased HIL flagging compared to manual flagging. Hemolysis flagging was the greatest in all 3 patient populations, and was successfully reduced for LD, CK and AST by optimized rules that incorporated both the H-index result and the analyte result. Changes in flagging rates were also patient population specific, particularly for icterus which was a problem in hospitalized populations but not in the community. Overall, concordance between manual and automated flagging methods was very low in both laboratories.
  
  
  CONCLUSIONS
  We demonstrate that flagging algorithms may not be universally transferable due to lab specific and population specific factors and demonstrate the benefits of local, a priori testing of algorithms prior to implementation.
authors.affiliation: Department of Pathology and Laboratory Medicine, University of Calgary and Calgary Laboratory Services, Canada.
authors.forename: Jessica M
authors.initials: JM
authors.lastname: Boyd
authors.affiliation: Department of Pathology and Laboratory Medicine, University of Calgary and Calgary Laboratory Services, Canada.
authors.forename: Richard
authors.initials: R
authors.lastname: Krause
authors.affiliation: Gamma-Dynacare Medical Laboratories, Canada.
authors.forename: Gayle
authors.initials: G
authors.lastname: Waite
authors.affiliation: Gamma-Dynacare Medical Laboratories, Canada.
authors.forename: William
authors.initials: W
authors.lastname: Hui
authors.affiliation: Gamma-Dynacare Medical Laboratories, Canada.
authors.forename: Elham
authors.initials: E
authors.lastname: Yazdi
authors.affiliation: Gamma-Dynacare Medical Laboratories, Canada.
authors.forename: David
authors.initials: D
authors.lastname: Wilmink
authors.affiliation: Department of Pathology and Laboratory Medicine, University of Calgary and Calgary Laboratory Services, Canada. Electronic address: Isolde.seidenlong@cls.ab.ca.
authors.forename: Isolde
authors.initials: I
authors.lastname: Seiden-Long
mesh_terms: D000465:Algorithms; D001331:Automation; D064790:Clinical Laboratory Services; D006461:Hemolysis; D006801:Humans; D006949:Hyperlipidemias / Q000097:blood*; D007565:Jaundice / Q000097:blood*
keywords: Automated indices; Hemolysis; Icterus; Lipemia