INTRODUCTION: Total allowable error (TEa) is the analytical quality specification that determines the acceptable limits for a test result. The aim of the present study was to determine whether third-party control data (percentage coefficient of variation (CV), percentage bias, and %TEa) of 26 clinical biochemistry parameters collected over a period of 6 months would meet biological variation (BV)-based analytical quality specifications (minimum, desirable, and optimum) in which BV quality specification might be more appropriate for our laboratory use.
METHODS: The study was conducted for 6 months on tests with the TEa values determined according to BV and using third-party controls, Unity Real Time® software, and Beckman Coulter AU5800 clinical chemistry analyzer.
RESULTS: The BV minimum specification is the easiest target to be performed by laboratories since it has the widest limits. It is also known that the BV already fulfills the other specifications (minimum and desirable) in tests where the optimum specification targets can be achieved, and the test performance classifications of our work are made according to this information. The minimum specification is only in Level 2 control serum total cholesterol test. The optimum specification with the narrowest limits within the BV criteria and the most difficult to achieve was met in nine tests (alanine aminotransferase, direct bilirubin, total bilirubin, creatine kinase, gamma-glutamyl transferase, ferritin, lipase, triglyceride, and uric acid (UA) for both control levels. Outside of these tests, in general, the desirable specification that each laboratory is aiming to fulfill is met.
DISCUSSION AND CONCLUSION: It is very valuable to set the boundaries of quality specifications targeted for analytical performance based on BV. These values are determined by the intra-individual and inter-individual variability of the test and, thus, define a test-specific target. In addition to defining the TEa for each specification of BV, the definition of bias and CV boundaries can give a more objective idea of the source of error.