Risk Analysis for Quality Control Part 3: Practical Application of the Precision Quality Control Model

Abstract

AbstractBackgroundWe developed a theoretical framework (Precision Quality Control [PQC]) to minimize the cost of quality, but it is not known whether the method can be applied in practice.MethodsWe used data for 2 analytes, cadmium and carbohydrate-deficient transferrin (CDT), and applied the PQC framework to find the optimal control limits. These analytes were selected because they differed with respect to sigma values that are major determinants of control limits. We explored different ways to visualize the results: (a) risk trade-off (false-positive risk vs false-negative risk), (b) cost–risk trade-off (false-positive cost vs false-negative risk), and (c) cost minimization.ResultsWe were able to use the PQC limit to produce 3 different visualizations to suggest control limits. The risk-based analysis was the simplest to apply, but the most difficult to interpret. The cost vs risk method was easy to apply but was still difficult to interpret. The cost minimization method was easy to interpret but required users to declare a willingness to pay that may be difficult to estimate.ConclusionsThe PQC method can be used to find control limits that minimize the cost of quality.