Biological Variation (BV) of quantities examined in laboratory medicine can be described as of three types, namely; variation over the span of life, predictable cyclical variation that can be daily, monthly or seasonal in nature, and random variation [1]. Random variations of analytes which consist of random fluctuation around the setting point of each individual is known as the intra-individual biological variation. Additionally, each person’s setting point may be different from another’s, and the overall variation resulting from this difference is known as inter-individual biological variation. In mathematical terms, these are usually expressed as Coefficients Of Variation (CV) and termed as CVw for intra-individual BV and CVg for inter-individual BV [2]. In laboratory medicine, it is essential to take the BV concept into consideration to provide reliable results. Thus, clinical laboratories should minimize all the sources of variations related laboratory processes, estimate the components of BV and appropriately manage them during the entire process leading to the laboratory report. A comprehensive database constituted from BV data of nearly 320 analytes which is updated every 2 years serves as a useful reference for many clinical laboratories [3,4]. Nonetheless, there are still hundreds of constituents for which BV has not yet been estimated. Future work should focus on these specific tests. Clinicians use several approaches in the interpretation of routine laboratory tests of the patients. These include comparison with predetermined cut-off values or reference values, or a comparison between two sequential results for a specific analyte [5]. Comparison between two sequential results is not as straightforward as it seems. It should be remembered that each result has its own inherent random variation associated with laboratory activity (analytical variation, CVa) and Biological Variation (BV) [6]. It has become clear that conventional population based reference values do have serious intrinsic problems and thus, there is a need for revisiting practical applications of conventional population based reference values for getting more useful laboratory data [7]. A major problem with reference values is that biological quantities are not constants that can be measured once in one reference sample group to provide reference values that are applicable in all situations. Knowledge of the underlying BV of analytes examined in laboratories is vital to understanding the proper generation and application of traditional population based reference values. Using the BV data is the best way to detect changes in a patient’s health status through a comparison between serial analytical results rather than comparison with population based reference values. This is because of the marked individuality of the majority of analytes. Hence, values obtained in consecutive analyses of samples from a patient may fall within the reference range, but show a considerable difference. When the difference exceeds a certain value, known as the Reference Change Value (RCV), a change in the patient’s condition is indicated [7,8].