A technique for determining the probability of abnormality

Histograms of the results of quantitative clinical laboratory analyses are usually broadly skewed because some of the patients have normal values with respect to the analyte being measured while values for others are below or above normal. We describe a technique for calculating the maximum possible number of individuals in a patient population who will give normal values and, by difference, the minimum possible number of those who will give below-normal and above-normal values. The technique permits estimation of the probability that any given result represents a member of a particular subpopulation, as well as selection of decision limits for patient classification, and estimates the degree of change required for a subject with a normal value to start giving below- or above-normal values.