In this fifth article in a series on internal quality control, Stephen MacDonald focuses on the importance of the methods to detect, at an early stage, potentially medically important errors, which is the cornerstone of what is hoped to be achieved.
In the first four articles of this series, statistical quality control (SQC) was introduced along with model properties of internal quality control (IQC) materials. Performance specifications were defined, chosen and implemented. In the next stage of design, we must ensure we detect non-conformity to expected performance. There is a fine balance between error detection and false alarms. This balance is maintained using quality control (QC) rules. The challenge we face in the laboratory is deciding what rules best suit each process. We need to:
During process stability, we expect our IQC to perform as shown in Figure 1a. Data points should be equally distributed across the target mean and around 95% of points are within two standard deviations (SD) of the target. Error can manifest itself in our processes in different ways.
Increased random error
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