Regression-Adjusted Real-Time Quality Control.

Autor:	Duan X; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University., Wang B; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University., Zhu J; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University., Zhang C; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University., Jiang W; IT Center, Zhongshan Hospital, Fudan University., Zhou J; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University., Shao W; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University., Zhao Y; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University., Yu Q; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University., Lei L; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University., Yiu KL; Roche Diagnostics, China, Shanghai., Chin KT; Roche Diagnostics, China, Shanghai., Pan B; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University., Guo W; Department of Laboratory Medicine, Zhongshan Hospital, Fudan University.
Jazyk:	angličtina
Zdroj:	Clinical chemistry [Clin Chem] 2021 Oct 01; Vol. 67 (10), pp. 1342-1350.
DOI:	10.1093/clinchem/hvab115
Abstrakt:	Background: Patient-based real-time quality control (PBRTQC) has gained increasing attention in the field of clinical laboratory management in recent years. Despite the many upsides that PBRTQC brings to the laboratory management system, it has been questioned for its performance and practical applicability for some analytes. This study introduces an extended method, regression-adjusted real-time quality control (RARTQC), to improve the performance of real-time quality control protocols. Methods: In contrast to the PBRTQC, RARTQC has an additional regression adjustment step before using a common statistical process control algorithm, such as the moving average, to decide whether an analytical error exists. We used all patient test results of 4 analytes in 2019 from Zhongshan Hospital, Fudan University, to compare the performance of the 2 frameworks. Three types of analytical error were added in the study to compare the performance of PBRTQC and RARTQC protocols: constant, random, and proportional errors. The false alarm rate and error detection charts were used to assess the protocols. Results: The study showed that RARTQC outperformed PBRTQC. RARTQC, compared with the PBRTQC, improved the trimmed average number of patients affected before detection (tANPed) at total allowable error by about 50% for both constant and proportional errors. Conclusions: The regression step in the RARTQC framework removes autocorrelation in the test results, allows researchers to add additional variables, and improves data transformation. RARTQC is a powerful framework for real-time quality control research. (© American Association for Clinical Chemistry 2021. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Databáze:	MEDLINE
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