Artificial Cells, Nanomedicine, and Biotechnology (Dec 2019)

Application of biological variation and six sigma models to evaluate analytical quality of six HbA1c analyzers and design quality control strategy

  • Xia Wang,
  • Dongmei Wen,
  • Weijia Wang,
  • Minghuan Suo,
  • Ting Hu

DOI
https://doi.org/10.1080/21691401.2019.1642207
Journal volume & issue
Vol. 47, no. 1
pp. 3598 – 3602

Abstract

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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.

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