Theoretic and practical contribution of bayesian inference to statistical process control: The experience of the Lyon Hospitals Board hemostasis laboratory

Abstract

Laboratories need to set up effective overall management of their internal quality control (IQC) and external quality assessment (EQA) results as key elements in statistical process control. Quality targets need to be defined, with methods to ensure durable control with respect to the relevant specifications. The hemostasis laboratory of the Lyon Hospitals Board (HCL, Lyon, France) uses model 3 from the Milan consensus conference, which is the state of the art in terms of quality targets, and uses a common EQA provider supplying as many real patient samples as possible. Giving priority to adopted methods, the lab optimizes the use of manufacturers' prior data: maximum acceptable inter assay coefficient of variation (CV) and prior IQC target values. Bayesian inference brings the method under control with respect to the manufacturers' prior data without the need for a preliminary phase. It links the IQC and EQA plans by the maximum acceptable CVs defined by the manufacturer.