Application of six sigma model to evaluate the analytical performance of hematology analytes, aims to establish a personalized quality control schemes and quality improvement measures for hematology analytes.

The data of external quality assessment (EQA) of hematology analytes from Jiangsu center for clinical laboratories in 2020 and its internal quality control (IQC) results were collected. And the quality specification derived from the "desirable" biological variation was used as allowable total error (TEa) to calculate the sigma value of each item. Meanwhile, analytical performance of each item was demonstrated on the standardized sigma performance verification chart. According to the Westgard sigma rules with batch length and the quality goal index (QGI), personalized IQC schemes and quality improvement measures for each item were formulated respectively.

With biological variation data as laboratory quality goal, the analytical performance of the WBC reached the "world-class" level, while the remaining projects ranged from "marginal" to "excellent". According to the Westgard sigma rules with batch length, 1_3s rule (N=2) with batch length of 1 000 patient samples was selected as IQC scheme for WBC. Multi-rules of 1_3s/2_2s/R_4s/4_1s (N=4) with batch length of 200 patient samples was selected as IQC scheme for RBC. Multi-rules of 1_3s/2_2s/R_4s (N=2) with batch length of 450 patient samples was selected as IQC scheme for Hb. Multi-rules of 1_3s/2_2s/R_4s/4_1s/6_x (N=6) with batch length of 45 patient samples was selected as IQC scheme for HCT and PLT. In addition, based on the calculation of QGI, Hb and HCT need priority to improve the precision; While RBC and PLT need to improve both precision and accuracy at the same time.

The six sigma model can objectively evaluate the analysis performance of clinical hematology analytes, which has important guiding significance in helping the design of laboratory quality control strategies and quality improvement.