Methods and approaches to determine "optimal" quality for clinical chemical data.

Although clinical reasoning and decision-making may be very complex, there are methods to perform both piecemeal and more complete optimizations with regard to the use of clinical chemical data and for assessing quality specification. Some methods and approaches are described and illustrated with examples: (i) rules for propagation of errors in simple algebraic/statistical transformations; (ii) systems and sensitivity analysis using biochemical/pathophysiological simulation models; (iii) systems and sensitivity analysis of simulated clinical classification and decision processes. It is concluded that the possible gain of useful information by improving analytical and pre-analytical quality should be related to the often more important aspects of test selection test and test combination, period and frequency of observation, and the use of correct conceptual models for transformation of data.