EDUCATON :: QUALITY CONTROL STRATEGIES
Figure 2.
also on how many patient results are produced before the error condition is detected and corrected. This is illustrated in Figure 2.
In this example, each vertical line rep- resents a patient specimen being tested on the instrument. Each diamond repre- sents a QC event where QC specimens are tested and QC rules are applied. A green diamond implies the QC results are accepted; a red diamond means the QC results are rejected. At a point between the second and third QC event, an out-of- control error condition occurs, causing a sustained shift in the testing process (such as shown in Figure 1). Given the magnitude of this particular out-of-control condition and the power of the QC rules, the error condition isn’t detected until the third QC event after it occurred. Each red asterisk denotes an erroneous patient result that was produced during the existence of the out-of-control error condition.
Notice some of the important relation- ships between QC events, the number of patients tested between QC events, and the number of erroneous patient results illustrated in Figure 2: • Not all the results produced during an error condition are unreliable (the prob- ability of producing an unreliable result during an error condition increases with the magnitude of the error).
• QC events do not always detect an error condition on the first try (the probability of a QC event detecting an error condition depends on the error detection rate of the QC rule, the number of control samples used, and the magnitude of the error).
• If the error condition in the example was smaller, we would expect proportion- ally fewer of the results tested during the undetected error condition to be unreliable (red asterisks in Figure 2), but more QC events needed to detect
it. Conversely, if the error condition in the example was larger, we would expect proportionally more of the results tested during the undetected error condition to be unreliable, and fewer QC events needed to detect it. If the error condi- tion were large enough, all of the patient test results after its occurrence would be unreliable and it would almost certainly be detected at the first QC event (third diamond in Figure 2).
In summary
QC that focuses on the instrument is con- cerned with the likelihood that a QC rule will trigger an alert after an error condi- tion has occurred (the probability of a red diamond in Figure 2). Instrument-focused QC strategies are designed to control the number of QC events required to detect an error condition.
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QC that focuses on the patient, on the other hand, is concerned with how many erroneous patient results are produced while an undetected error condition exists (the number of reds asterisks in Figure 2). Patient-focused QC strategies should be designed to control the number of er- roneous patient results produced before the error condition is detected.
REFERENCES
1. International Organization for Standardization: Medical laboratories - particular requirements for quality and competence. ISO 15189:2012. Inter- national Organization for Standardization (ISO), Geneva.
2. Parvin CA. Assessing the impact of the fre- quency of quality control testing on the quality of reported patient results. Clin Chem. 2008;54:2049-54. doi:10.1373/clinchem.2008.113639.
John Yundt-Pacheco, MSCS, is a scientific fellow who performs research in quality control and patient risk issues in the Informatics Discovery Group at Bio-Rad. He has had the opportunity to work with laboratories around the
world, developing practical real-time, inter-laboratory quality control and proficiency testing systems.
Call 800.321.2313 or visit
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Curtis Parvin, PhD is retired from Bio-Rad, where he was Manager of Advanced Statistical Research. Prior to joining Bio-Rad, Parvin was the Director of Informatics and Statistics at the faculty of Washington
University School of Medicine.
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