The Online Meeting was presented by Juliana Barroso, biologist, specialist in Clinical Laboratory Sciences and In Vitro Diagnostics (Unigranrio), and Technical Supervisor of Service Management at Controllab.
The session covered the main concepts and applications of Internal Quality Control, focusing on its use for monitoring the stability of analytical processes, identifying deviations, multiple assigned values, documentation, and best practices for implementation in the laboratory routine.
With a practical and application-oriented approach, the meeting helped participants expand their knowledge and strengthen quality monitoring, analytical process control, and the reliability of laboratory results.
Questions & Answers
The following questions were not addressed during the Online Meeting.
Are Internal Quality Controls available for Molecular Biology? What are some examples?
Yes. We currently offer Internal Quality Controls for Molecular Biology covering several pathogens, including Coronavirus (SARS-CoV-2), Dengue, Influenza A and B, Human Bocavirus (HBoV), Rhinovirus, Respiratory Syncytial Virus (RSV), among others.
The complete list of assays is available in the catalog on our website.
If the assay you are looking for is not currently available, please contact us so that we can assess the feasibility of offering it.
When identifying a violated rule, relating it to the cause of the Internal Quality Control error, and making the necessary adjustment, should this be done only using the laboratory's own statistical values rather than those from a peer consensus group?
Westgard rules do not require laboratories to use their own mean and standard deviation (SD). What they do require is the use of valid statistical limits based on the mean and SD for applying the Westgard rules (1₃s, 2₂s, R₄s, etc.).
Using a mean and SD established by the laboratory itself is considered best practice because these parameters reflect the actual performance of the analytical system under its routine operating conditions. This makes the Westgard rules more sensitive to detecting true analytical errors while reducing unnecessary rejections.
The mean and SD values provided by the manufacturer in the product insert are typically derived from interlaboratory studies. As a result, the observed variability may be greater than that of an individual laboratory, depending on the analytical process. Therefore, it is important to evaluate whether these limits accurately represent the laboratory’s performance. If the limits are too wide, the Westgard rules may lose sensitivity in detecting errors; if they are too narrow, they may increase the frequency of false rejections.
