Reference change values (RCV) provide objective tools for assessment of the significance of differences in serial results from an individual. The concept is simple and the calculation easy, since all laboratories know their analytical imprecision (CV(A)) and estimates of within-subject biological variation (CV(I)) are available for a large number of quantities. Generally, CV(I) are constant over time, geography, methodology and in health and chronic stable disease. The formula is RCV=2(1/2) · Z · (CV(A)(2) + CV(I)(2))(1/2), where Z is the number of standard deviations appropriate to the probability. Correct interpretation of the semantics describing the clinical use of RCV is vital for selection of the Z-score. Many quantities of clinically importance exist for which good estimates of RCV are unavailable. Derivation of CV(I) may be difficult for such quantities: flair and imagination are required in selecting populations with chronic but stable disease on whom CV(I) can be determined. RCV can be used for delta-checking and auto-verification and laboratory information management systems (LIMS) can be adapted to do this. Recently, log-normal transformation to obtain unidirectional RCV has been used. Gaps in knowledge of RCV still require filling since the need for measures of change is clearly expressed in guidelines.