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This Article Full Text Full Text (PDF) Supplemental Data All Versions of this Article: clinchem.2008.113639v1 54/12/2049    most recent Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Parvin, C. A. Search for Related Content PubMed PubMed Citation Articles by Parvin, C. A.

Assessing the Impact of the Frequency of Quality Control Testing on the Quality of Reported Patient Results

¹ Washington University School of Medicine, Department of Pathology and Immunology, Saint Louis, MO.

Address correspondence to the author at: Washington University School of Medicine, Department of Pathology and Immunology, Saint Louis, MO 63110. Fax (314) 454-5208; e-mail parvin{at}wustl.edu

Background: The traditional measure used to evaluate QC performance is the probability of rejecting an analytical run that contains a critical out-of-control error condition. The probability of rejecting an analytical run, however, is not affected by changes in QC-testing frequency. A different performance measure is necessary to assess the impact of the frequency of QC testing.

Methods: I used a statistical model to define in-control and out-of-control processes, laboratory testing modes, and quality control strategies.

Results: The expected increase in the number of unacceptable patient results reported during the presence of an undetected out-of-control error condition is a performance measure that is affected by changes in QC-testing frequency. I derived this measure for different out-of-control error conditions and laboratory testing modes and showed that a worst-case expected increase in the number of unacceptable patient results reported can be estimated. The laboratory thus has the ability to design QC strategies that limit the expected number of unacceptable patient results reported.

Conclusions: To assess the impact of the frequency of QC testing on QC performance, it is necessary to move beyond thinking in terms of the probability of accepting or rejecting analytical runs. A performance measure based on the expected increase in the number of unacceptable patient results reported has the dual advantage of objectively assessing the impact of changes in QC-testing frequency and putting focus on the quality of reported patient results rather than the quality of laboratory batches.