부산대학교 도서관

Objective: To apply biological variation and six Sigma models to evaluate analysis performance of 6 HbA1c analyzers and design the new quality control strategy. Method: We collected data of imprecision and inaccuracy from routine internal quality control (June 2017–December 2017) and proficiency test of NGSP, respectively. The coefficient of variance (CV)% and bias% were plotted in the biological variation and six sigma models. The new quality control strategy was designed by the sigma value and OPSpecs. The quality improvement was guided by the QGI. Results: The analytical performance of 6 HbA1c analyzers in our laboratory were good in the routine model, However, 50% (3/6) and 67% (4/6) of the HbA1c analyzers reached the acceptable level in the biological variation and six Sigma model, respectively. We also design personalized control strategy and promote quality improvement by combining the sigma value, OPSpecs, and QGI. Conclusions: Biological variation model and six sigma model could visually display the performance of 6 HbA1c analyzers and personalized control strategy could be designed based on the sigma value, OPSpecs, and QGI. [ABSTRACT FROM AUTHOR]