Multivariate interpretation of laboratory tests used in monitoring patients

This study demonstrates an approach to the problem of minimizing false-negative and false-positive laboratory findings. In this approach, we consider the fact that results of laboratory tests are correlated, utilize within-person test results to interpret current results, and minimize the impact of multivariate conservatism by examining test results in small groups. The procedure requires panels of tests to be divided into related subpanels, testing each subpanel independently, and using the Bonferroni inequality to determine whether any of the observed values for a given subpanel is "out-of-range." The procedure is demonstrated, and its limitations are observed and discussed.