Impact of combining data from multiple instruments on performance of patient-based real-time quality control

It is unclear what is the best strategy for applying patient-based real-time quality control (PBRTQC) algorithm in the presence of multiple instruments. This simulation study compared the error detection capability of applying PBRTQC algorithms for instruments individually and in combination using s...

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Permalink: http://skupnikatalog.nsk.hr/Record/nsk.NSK01001163330/Details
Matična publikacija: Biochemia medica (Online)
31 (2021), 2 ; str. 276-282
Glavni autori: Zhou, Qianqian (Author), Loh, Tze Ping, Badrick, Tony
Vrsta građe: e-članak
Jezik: eng
Online pristup: https://doi.org/10.11613/BM.2021.020705
Elektronička verzija članka
Elektronička verzija članka
Elektronička verzija članka
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024 7 |2 doi  |a 10.11613/BM.2021.020705 
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080 1 |2 2011 
100 1 |a Zhou, Qianqian  |4 aut  |9 HR-ZaNSK 
245 1 0 |a Impact of combining data from multiple instruments on performance of patient-based real-time quality control  |h [Elektronička građa]  |c Qianqian Zhou, Tze Ping Loh, Tony Badrick, Qianqian Zhou. 
300 |b Ilustr. 
504 |a Bibliografija: 
504 |a Summary. 
520 |a It is unclear what is the best strategy for applying patient-based real-time quality control (PBRTQC) algorithm in the presence of multiple instruments. This simulation study compared the error detection capability of applying PBRTQC algorithms for instruments individually and in combination using serum sodium as an example.Four sets of random serum sodium measurements were generated with differing means and standard deviations to represent four simulated instruments. Moving median with winsorization was selected as the PBRTQC algorithm. The PBRTQC parameters (block size and control limits) were optimized and applied to the four simulated laboratory data sets individually and in combination.When the PBRTQC algorithm were individually optimized and applied to the data of the individual simulated instruments, it was able to detect bias several folds faster than when they were combined. Similarly, the individually applied algorithms had perfect error detection rates across different magnitudes of bias, whereas the error detection rates of the algorithm applied on the combined data missed smaller biases. The performance of the individually applied PBRTQC algorithm performed more consistently among the simulated instruments compared to when the data were combined.While combining data from different instruments can increase the data stream and hence, increase the speed of error detection, it may widen the control limits and compromising the probability of error detection. The presence of multiple instruments in the data stream may dilute the effect of the error when it only affects a selected instrument. 
700 1 |a Loh, Tze Ping  |4 aut  |9 HR-ZaNSK 
700 1 |a Badrick, Tony  |4 aut  |9 HR-ZaNSK 
700 1 |a Zhou, Qianqian  |4 aut  |9 HR-ZaNSK 
773 0 |t Biochemia medica (Online)  |x 1846-7482  |g 31 (2021), 2 ; str. 276-282  |w nsk.(HR-ZaNSK)000655372 
981 |b Be2021 
856 4 0 |u https://doi.org/10.11613/BM.2021.020705 
856 4 0 |u https://www.biochemia-medica.com/en/journal/31/2/10.11613/BM.2021.020705  |y Elektronička verzija članka 
856 4 0 |u https://www.biochemia-medica.com/en/journal/31/2/10.11613/BM.2021.020705/fullArticle  |y Elektronička verzija članka 
856 4 1 |y Digitalna.nsk.hr 
856 4 0 |u https://hrcak.srce.hr/258883  |y Elektronička verzija članka