2018
DOI: 10.1373/clinchem.2017.278291
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Planning Risk-Based SQC Schedules for Bracketed Operation of Continuous Production Analyzers

Abstract: Continuous production analyzers that demonstrate high σ performance can be effectively controlled with multistage SQC designs that employ a startup QC event followed by periodic monitoring or bracketing QC events. Such designs can be optimized to minimize the risk of harm to patients.

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Cited by 63 publications
(40 citation statements)
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“…The difference in Urea on the Beckman analyser, however, may have been the result of periodic biases with different signs averaged to an ignorable long-term bias. In practice, laboratories must take caution when implementing “Westgard Sigma Rules” in quality control based on σ values, because these values may change continuously with respect to precision and bias arising, for example, from calibrations, reagents, or personnel ( 4 ). As described previously, σ value between different periods for some analytes may differ, laboratory should monitor the σ level continuously when using individualized quality control rules based on the σ evaluation.…”
Section: Discussionmentioning
confidence: 99%
“…The difference in Urea on the Beckman analyser, however, may have been the result of periodic biases with different signs averaged to an ignorable long-term bias. In practice, laboratories must take caution when implementing “Westgard Sigma Rules” in quality control based on σ values, because these values may change continuously with respect to precision and bias arising, for example, from calibrations, reagents, or personnel ( 4 ). As described previously, σ value between different periods for some analytes may differ, laboratory should monitor the σ level continuously when using individualized quality control rules based on the σ evaluation.…”
Section: Discussionmentioning
confidence: 99%
“…When considering continuous laboratory production processes, bracketed internal QC (iQC) is applied for analytical quality assurance [39]. In current practice with short turn-around times, continuous analysis and the release of multiple diagnostic test results, many laboratory results will be released before a confirmatory QC is performed.…”
Section: Ma Qc To Support Statistical Qcmentioning
confidence: 99%
“…When a continuous production process is analytically controlled using scheduled iQC, there is a risk of reporting erroneous results by either rapid onset of (large) error in between the scheduled QC [3] or temporary assay failure in between the scheduled iQC, as demonstrated for a sodium MA alarm case [9]. Furthermore, by design, statistical QC is limited in its ability to detect clinically relevant errors for low sigma processes [39,40]. Interestingly, these low sigma processes (characterized by a low biological variation/analytical variation ratio) generally have the characteristics for optimal MA performance [19].…”
Section: Ma Qc To Support Statistical Qcmentioning
confidence: 99%
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“…The practice of using the σ to improve clinical laboratory quality has been in place for nearly two decades. 2 Sigma metric has become a useful tool to monitor quality indicators, 1 to assess the analytical quality of assays, 3,4 to set quality control rules, [5][6][7][8] to describe assay analytical performance for external quality assessment participants, 9 and to help manufacturers choose product requirements. 10 Analytical quality of assays is quantitatively estimated as a sigma metric based on 3 parameters: allowable total error (TEa), bias, and imprecision.…”
Section: Introductionmentioning
confidence: 99%