【Objective】 To establish a quality control mechanism based on the Poisson distribution for monitoring contamination in nucleic acid testing (NAT) laboratories. 【Methods】 The study collected NAT single-reactivity rates and discriminatory test reactivity rates from the Grifols Panther NAT system from 2022 to 2023. The Poisson distribution probability method was used to calculate the daily probability of nucleic acid single reactivity. Sensitivity and specificity of the quality control model were further validated using single-reactivity rates, discriminatory reactivity rates and ROC curve analysis, followed by proposing corresponding multi-rule quality control strategies. 【Results】 Using P=0.05 as the threshold for out-of-control, the Poisson distribution probability quality control model identified 40 out-of-control points with P<0.05. After manual verification using discriminatory reactivity rates, 20 out-of-control points were confirmed. The sensitivity of determining out-of-control was 60.0%, and the specificity was 95.6%. Due to the high number of out-of-control points, it is recommended to combine discriminatory reactivity rates and employ multi-rule quality control methods for quality monitoring. Under the multi-rule quality control, there were 18 warning points and 2 out-of-control points for NAT single reactivity from 2022 to 2023. 【Conclusion】 The multi-rule NAT single-reactivity monitoring mechanism based on the Poisson distribution probability is more suitable for nucleic acid laboratories to monitor and warn of laboratory contamination, thereby enhancing the management capabilities and detection quality of nucleic acid laboratories.