Quality control (QC) is a foundational practice in the clinical laboratory and is a routine and mandatory task. QC encompasses the analysis of QC materials and comparison of the observed values to the expected distribution under stable operating conditions.
QC materials act as surrogates for clinical samples and are measured in laboratories on a daily basis in the same manner as patient specimens. QC materials are generally commercially available in liquid or lyophilized form, and are usually packaged in bottles that enable routine and repeated use. Laboratories can obtain QC materials from the same manufacturer as the equipment and/or reagents that the laboratory uses, or purchase them from third-party vendors that specialize in producing QC materials.
For non-waived tests, laboratory regulations require, at the minimum, analysis of at least two levels of control materials once every 24 hours for chemistry tests, and once every 8 hours for blood gases, hematology, and coagulation tests. A good practice for laboratories is to define the number of levels of QC material to be assayed for each analyte, ensuring that analyte concentrations are present in the control materials at clinically relevant levels. In addition, laboratories should define analytical run length, and in turn, frequency of QC material analysis. There is no standard protocol or guideline to establish analytical run length, so practice varies across different laboratory settings. Labs should define these parameters based on the expected stability of the analytical system, the number of patient specimens analyzed, cost of patient lookback, and access to patient data in the event of QC failure. Workflow patterns, internal resource capabilities, and the clinical impact of undetected errors that may occur before the next QC measurement also are important considerations in determining the analytical run length and frequency of QC material analysis.
Every laboratory should obtain appropriate initial mean and standard deviation values for each level of control material. These values provide meaningful information about method performance within the laboratory under stable conditions. The ultimate goal of establishing QC values is to collect as much information as possible about the control material before starting to utilize it to monitor the performance of a particular method. Different variables that need to be captured during this data collection period include: different operators; reagent changes; maintenance event; environmental effects; and calibration events.
Repetitive testing of the control material yields the mean and the standard deviation. The current recommendations (according to the CLSI 24-A3 guidelines) are to measure the QC material a minimum of 20 times on 20 separate days. The goal is to obtain a valid and reliable target mean value that includes several sources of variability, and an appropriate standard deviation that represents the inherent imprecision of the method when it is performing as expected.
In practice, the ideal 20 measurements performed on 20 different days may not be possible and all laboratories face situations or scenarios that could hinder fulfilling this requirement. Some examples include: unexpectedly running out of control material as a result of problematic methods or other factors; unexpected loss of QC material; delayed shipment of QC material; and miscalculation of sequestered lots.
There are viable and acceptable alternatives to collecting preliminary data, or as much data as possible, in less than 20 days. A possible approach includes four measurements a day for 5 consecutive days and establishment of preliminary control values until sufficient internal data is available. Another option is to use manufacturers’ provided data, which should only be done temporarily until sufficient internal data is available. Labs should exercise caution when they use a manufacturer’s provided data, as the published limits come from analysis of the QC materials at multiple laboratories that utilize different methods. This practice can result in higher variability than that observed within an individual laboratory. Long-term use of a manufacturer’s QC values is discouraged as it greatly reduces a laboratory’s ability to detect clinically significant errors.
The best practice is to establish control values (mean and SD) that reflect the actual performance of the method in the laboratory.
M. Laura Parnas, PhD, DABCC, is director of clinical science at Sutter Health Shared Laboratory in Livermore, California.
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