Precision requirements for cost-effective operation of analytical processes

Abstract

Current performance criteria for analytical methods are often based on recommendations developed many years ago. A common criterion for imprecision requires that two times the standard deviation (s) of the method be less than the allowable total error (TEa). Unfortunately, when this criterion is minimally satisfied, commonly used control procedures cannot achieve reliable detection of medically important errors. Studies of the power functions for statistical quality-control (QC) procedures show that the magnitude of medically important errors must be at least 3s to fall near the plateau of the power curves and be readily detected by current QC procedures. For methods that just meet the precision criterion 2s < TEa, however, medically important errors will fall on the rising portion of the power curves and typically be detected less than half of the time. From a "reverse engineering" perspective, the 2s < TEa criterion is inadequate because it does not allow for the known performance limitations (lack of sensitivity) of commonly used control procedures. A strong case can be made for using a criterion of at least 4s < TEa, which calls for a twofold improvement in imprecision over the current minimum requirements. This recommendation is consistent with current industrial guidelines for process capability and would lead to more reliable detection of medically important errors.