The reference change value, defined as RCV = 1.96 x 2(1/2) x(s(I)(2) +s A(2))(1/2), where s(I) is within-subject biological variation and s A is analytical variation, has been used for many years to take clinical decisions in patient monitoring. Furthermore, the index of individuality was defined as II = (s(I)(2) +s(A)(2))(1/2)/s(G) , where s(G) is the between-subject biological variation. This index has been simplified by later authors to s(I)/s(G) and has been used in monitoring situations to determine the utility of population-based reference intervals. Harris stated that when the index of individuality is lower than 0.6, the specific reference interval of the individual - when available - is better than the population-based reference interval. However, if a change within a patient is equivalent to the RCV applied for the significant difference between two measurements, the probability of detecting this change is only 50% (the same probability of missing it). Therefore, to obtain a higher probability of detecting a change by the RCV (e.g., 90%) the interpretation of the index of individuality has to be reconsidered. This contribution compares the power of the RCV to the use of cut-off points and population-based reference intervals. The benefits of the RCV compared to the distance to cut-off point or reference limit are also described in relation to the index of individuality.