Atypicality indices as reference values for laboratory data.

Abstract

There have been several methods suggested for relating laboratory results to relevant reference values; none has been completely satisfactory. The method described in this paper is referring to atypicality indices for uniform reporting and feasible interpretation of laboratory data. The index associated with a measurement is defined as the probability of finding a results closer to the mean of the reference population than the one actually observed. Thus the larger the index, the less likely the measured value would be in the reference population and the more atypical it becomes. The proposed method, unlike any other, keeps the same simple and desirable features when extended to multivariate situations, that is when several tests are to be interpreted simultaneously.