A difference between the IFCC HbA1c goals and an HbA1c error grid – continued

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Some more thoughts …

Anyone who’s ever looked at CAP summary statistics knows that CAP deletes outlier data as part of their process. One can view this in several ways…

From a statistics standpoint, it makes sense because the main parameter of interest is imprecision, which would be inflated by outlier data.

But the original goal of six sigma (which also requires a precise estimate of imprecision) was to be able to predict DEFECTS so why in the world would you delete the defects (outliers) that you wish to predict. From that standpoint, the analysis is biased.

Moreover, the outliers could in fact be real analytical problems although whatever their cause, they still are problems and because outliers are by definition large errors, these values could be associated with serious patient harm.

So this is another reason to favor error grids – which always include all data.

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