The definition of “normal” values for common laboratory tests often governs the diagnosis, treatment, and overall management of tested individuals. Some test results may depend on demographic traits of the tested population including age, race, and sex. Ideally, laboratory test results should be interpreted in reference to a population of “similar” “healthy” individuals. In many settings, however, it is unclear exactly who these individuals are. How much population stratification and what criteria for healthy individuals are optimal? In particular, with the evolution of medicine into fully personalized or “precision” medicine and the availability of large-scale data sets, there may be interest in trying to match each person to an increasingly granular normal reference population. Is this precision feasible to obtain in reliable ways and will it improve practice?