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Reference intervals for healthy subjects and diseased populations are important benchmarks for the clinical interpretation of laboratory test values. It is important that the testing conditions used to collect the reference data be closely matched with the testing conditions used for patient data. Interlaboratory differences and intralaboratory changes, especially changes in analytic set-points, can markedly affect the clinical interpretation of tests. If laboratory testing methods could be harmonized, laboratories could potentially share reference data to make these data more reliable.This chapter illustrates the use of reference intervals for healthy subjects and reference data from diseased populations for medical decisions. One example illustrates the effects of age differences on test result interpretation. Other examples illustrate use of thyroid-stimulating hormone (TSH) and combinations of TSH with free thyroxine measurements for diagnosing thyroid diseases. Both univariate and multivariate reference intervals are discussed. Model systems for using disease prevalence and cost utility functions are provided to illustrate optimization of medical decisions.