title: Selecting Statistical Procedures for Quality Control Planning Based on Risk Management.
abstract: According to the traditional approach to statistical QC planning, the performance of QC procedures is assessed in terms of its probability of rejecting an analytical run that contains critical size errors (PEDC). Recently, the maximum expected increase in the number of unacceptable patient results reported during the presence of an undetected out-of-control error condition [Max E(NUF)], has been proposed as an alternative QC performance measure because it is more related to the current introduction of risk management concepts for QC planning in the clinical laboratory.
  
  
  
  We used a statistical model to investigate the relationship between PEDC and Max E(NUF) for simple QC procedures widely used in clinical laboratories and to construct charts relating Max E(NUF) with the capability of the analytical process that allow for QC planning based on the risk of harm to a patient due to the report of erroneous results.
  
  
  
  A QC procedure shows nearly the same Max E(NUF) value when used for controlling analytical processes with the same capability, and there is a close relationship between PEDC and Max E(NUF) for simple QC procedures; therefore, the value of PEDC can be estimated from the value of Max E(NUF) and vice versa. QC procedures selected by their high PEDC value are also characterized by a low value for Max E(NUF).
  
  
  
  The PEDC value can be used for estimating the probability of patient harm, allowing for the selection of appropriate QC procedures in QC planning based on risk management.
authors.affiliation: Laboratory of Biochemistry, Hospital General de Requena, Valencia, Spain. martinyago.lopez@gmail.com.
authors.forename: Martín
authors.initials: M
authors.lastname: Yago
authors.affiliation: Laboratory of Biochemistry, Hospital General de Requena, Valencia, Spain.
authors.forename: Silvia
authors.initials: S
authors.lastname: Alcover
mesh_terms: D064790:Clinical Laboratory Services; D006801:Humans; D015233:Models, Statistical; D011786:Quality Control; D012308:Risk Management