The importance of quality planning tools in clinical chemistry laboratory

Objective: Quality planning in a laboratory can be defined as designing quality wanted or required for a test. The objective of a suitable choice is to determine the most efficient quality control rules and the number of control measurements. The aim of this study is to evaluate the features of the tools of quality planing while choosing quality control procedure. Methods: In this study, the tools of quality planing used to choose quality control procedure were operated for the data generated by simulation. These tools were created for both clinical decision interval and total analytical error model. EZ Rules 3.0 programme was used to obtain OPSpecs chart and critical error chart for both models. Results: In critical error chart, in clinical decision interval model, N=4, R=1 as control procedures, probability of detecting error is over 90% and probability of refusing wrong is less than 5%, in total analytical error model, probability of error detecting is almost 100%, probability of refusing wrong is less than 5%. Procedures applicable to total analytical error model and clinical decision interval model of OPSspecs model are N=4 and R=1. Conclusion: As a result, the number of control measurements required based on random and systematic error observed in the measurement procedure, and the above mentioned approaches, which facilite selecting control rules are important for quality control evaluations in clinical chemistry laboratories. In addition they are difficult to comment and to obtain without software.