探讨六西格玛（6σ）质量管理理论和生物学变异规范在中孕期母血清学产前筛查检测的方法性能评估中的应用价值。

统计2022年1—12月在镇江市妇幼保健院参加中孕期母血清学产前筛查孕妇检测结果的室内质控数据。分析参加国家卫生健康委员会临床检验中心（NCCL）的室间质量评价（EQA）结果、江苏省产前筛查质量管理系统的EQA数据，计算变异系数（CV）、偏倚（bias），分别以NCCL的EQA计划的允许总误差（TEa）和基于生物学变异导出的TEa计算各项目的σ值，绘制标准化σ验证图，对于σ<6的项目计算质量目标指数（QGI），根据结果分析原因及时纠偏。

NCCL标准下甲胎蛋白（AFP）和游离β绒毛膜促性腺激素（free β-hCG）σ值均>6，为“世界一流”水平；在生物学变异合适TEa标准下σ值>6，为“世界一流”水平；最佳TEa标准下，AFP σ值=4~5，为“良好”的实验室水平，此时QGI值<0.8，提示该标准下精密度超出允许范围，需分析该项目的影响因素，优先提高精密度。

6σ质量管理理论和生物学变异规范可作为传统质控方法的补充，直观提示实验中可能存在的不良因素，以优化质控方案，提高检测效率。

To investigate the application value of Six Sigma (6σ) quality management theory and biological variation criteria in the performance evaluation of maternal serological prenatal screening tests during the second trimester.

From January to December 2022, the indoor quality control data of prenatal serological screening for pregnant women during the second trimester at Zhenjiang Maternal and Child Health Care Hospital were collected. The results of external quality assessment (EQA) from National Center for Clinical Laboratories (NCCL) and the EQA data from Jiangsu Prenatal Screening Quality Management System were analyzed. The coefficient of variation (CV) and bias were calculated. The sigma (σ) values of each item were calculated based on the allowable total error (TEa) of the NCCL EQA program and the TEa derived from biological variation. Standardized σ verification charts were plotted, and the quality goal index (QGI) was calculated for items with σ <6. Reasons for the results were analyzed and timely corrections were made.

The σ values of alpha-fetoprotein (AFP) and free β-human chorionic gonadotropin (free β-hCG) under the NCCL standard were all>6, which was the "world-class" level. If the TEa standard is suitable for biological variation, the σ value is more than 6, which is the "world-class" level. Under the optimal TEa standard, the σ value of AFP was 4~5, indicating "good" laboratory performance. At this time, the QGI value<0.8, suggesting that the precision under this standard exceeds the permissible range. Therefore, it is necessary to analyze the influencing factors of this item and prioritize improving the precision.

6σ quality management theory and biological variation specification can be used as a supplement to traditional quality control methods, visually indicating potential adverse factors in the experiment, so as to optimize the quality control scheme and improve the detection efficiency.