Advantages of a Bracketed QC Strategy
As cited in EP23-A, Parvin and colleagues describe the advantages of just such a bracketed QC strategy compared to immediate release of patient results:
- Conventional QC rules originated from batch-oriented testing. There is a direct relationship between the quality of the QC specimen and the quality of the patient specimens in a batch test. The advent of discrete testing has changed this relationship. With a much higher degree of independence between tests, discrete analyzers have a weaker connection between QC specimens and patients. While the quality of a QC specimen may be acceptable, a subsequent malfunction could compromise patient specimens and remain undetected until it is identified with future QC evaluations. The number of patients that are tested between QC specimens directly affects the risk of producing a compromised result. . . . The more frequently QC specimens are evaluated the lower the average number of patients at risk for unacceptable large analytical errors due to an undetected malfunction. Logically, this implies that the way to minimize patient risk is to evaluate control specimens with each patient specimen. . . . Evaluating a QC specimen with each patient will minimize patient risk but is not practical — so, what can be done? One possibility is to consider bracketing patient specimens with QC specimens and not reporting patient results until a QC specimen is successfully evaluated. Bracketed QC offers several attractive design features and restores the dependency relationship between the quality of QC specimens and the quality of patient results. If evaluation of the closing QC specimen in the bracket determines that no grave, persistent error state exists, then the patient specimens were also evaluated with no grave, persistent error state.10
Parvin and colleagues further described the concepts of risk management and of a bracketed QC strategy in a series of articles published in ADVANCE for Administrators of the Laboratory®:
More detailed statistical treatment can be found in:
- Parvin, C.A., Gronowski A.N. “Effect of analytical run length on quality-control (QC) performance and
the QC planning process”, Clinical Chemistry. 1997; 43:11:2149-2154.
- Parvin, C.A., “Assessing the Impact of the Frequency of Quality Control Testing on the Quality of Reported Patient Results”, Clinical Chemistry 2008; 54:12:2049-2054.
10 Yundt-Pacheco, J., Parvin C.A., “The impact of QC Frequency on Patient Results.” MLO Medical Laboratory Observer. 2008;40(9)26-27.
11 See all articles here.