Repeat-sampling strategies for QC outside 2SD provide an effective balance between false-rejection and error detection rates compared to standard multirules, with only a modest increase in control testing.
Repeat-sampling QC strategies may balance error detection and false rejections in labs; Level 5 evidence leaves open prospective validation before practice change.
BACKGROUND: Repeating a QC that is outside 2SD from the mean (1:2s rule) appears to be a common practice. Although this form of repeat sampling is frowned on by many, the comparative power of the approach has not been formally evaluated. METHODS: We computed power functions mathematically and by computer simulation for 4 different 1:2s repeat-sampling strategies, as well as the 1:2s rule, the 1:3s rule, and 2 common QC multirules. RESULTS: The false-rejection rates for the repeat-sampling strategies were similarly low to those of the 1:3s QC rule. The error detection rates for the repeat-sampling strategies approached those of the 1:2s QC rule for moderate to large out-of-control error conditions. In most cases, the power of the repeat-sampling strategies was superior to the power of the QC multirules we evaluated. The increase in QC utilization rate ranged from 4% to 13% for the repeat-sampling strategies investigated. CONCLUSIONS: The repeat-sampling strategies provide an effective tactic to take advantage of the desirable properties of both the 1:2s and 1:3s QC rules. Additionally, the power of the repeat-sampling strategies compares favorably with the power of 2 common QC multirules. These improvements come with a modest increase in the average number of controls tested.
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Parvin et al. (2012) studied this question.
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