Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.

Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which plots the values of one or more analytical characteristics over time. These characteristics are monitored and measured repeatedly at different times during the analysis. Each measured value is compared to the known value of reference material. An inspection is required if a measured value lies outside the range of controlled limits, typically defined as standard deviation from the reference value. If necessary, modifications to the analysis conditions are required to maintain statistical control of the system.

Proficiency testing is the simultaneous analysis undertaken across multiple laboratories. The mean of results obtained from all labs or a known standard reference value is used to compare the variation in the results from individual labs. The Z score estimates this deflection of values from the reference value.

Documentation and archiving are critical aspects of quality assurance that ensure transparency and traceability in the laboratory process. Every activity related to quality control and assurance should be properly documented, including sample custody, instrument calibration, standard operating procedures, and results. This process involves creating a comprehensive record that serves as a reference for future checks.

Each document must clearly trace back to the individual responsible for its creation or management. This often requires that documents be signed and dated by the person involved, adding accountability to the process. Proper documentation not only supports the statistical control of a system but also plays a key role in identifying variations in quality control processes. An accurate archive ensures that past data can be retrieved, assessed, and used to make informed decisions about future analyses.