New insight into the comparative power of quality-control rules that use control observations within a single analytical run.
The error detection characteristics of quality-control (QC) rules that use control observations within a single analytical run are investigated. Unlike the evaluation of QC rules that span multiple analytical runs, most of the fundamental results regarding the performance of QC rules applied within a single analytical run can be obtained from statistical theory, without the need for simulation studies. The case of two control observations per run is investigated for ease of graphical display, but the conclusions can be extended to more than two control observations per run. Results are summarized in a graphical format that offers many interesting insights into the relations among the various QC rules. The graphs provide heuristic support to the theoretical conclusions that no QC rule is best under all error conditions, but the multirule that combines the mean rule and a within-run standard deviation rule offers an attractive compromise.
Parvin
C A
CA
Department of Pathology, Washington University School of Medicine, St. Louis, MO 63110.
D002624:Chemistry, Clinical / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D011786:Quality Control; D012680:Sensitivity and Specificity