Original Research

The application of sigma metrics in the laboratory to assess quality control processes in South Africa

Marli van Heerden, Jaya A. George, Siyabonga Khoza
African Journal of Laboratory Medicine | Vol 11, No 1 | a1344 | DOI: https://doi.org/10.4102/ajlm.v11i1.1344 | © 2022 Marli van Heerden, Jaya A. George, Siyabonga Khoza | This work is licensed under CC Attribution 4.0
Submitted: 26 July 2020 | Published: 22 June 2022

About the author(s)

Marli van Heerden, National Health Laboratory Service, Johannesburg, South Africa; and, Faculty of Health Sciences, Charlotte Maxeke Johannesburg Academic Hospital, University of the Witwatersrand, Johannesburg, South Africa
Jaya A. George, National Health Laboratory Service, Johannesburg, South Africa; and, Faculty of Health Sciences, Charlotte Maxeke Johannesburg Academic Hospital, University of the Witwatersrand, Johannesburg, South Africa
Siyabonga Khoza, National Health Laboratory Service, Johannesburg, South Africa; and, Faculty of Health Sciences, Charlotte Maxeke Johannesburg Academic Hospital, University of the Witwatersrand, Johannesburg, South Africa


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Abstract

Background: Laboratories use quality control processes to monitor and evaluate analytical performance in terms of precision and bias. Sigma metrics provide an objective assessment of laboratory quality using the total allowable error as an additional parameter.

Objective: This study aimed to determine the sigma metrics of analytes when using different total allowable error guidelines.

Methods: A retrospective analysis was performed on 19 general chemistry analytes at Charlotte Maxeke Johannesburg Academic Hospital in South Africa between January 2017 and December 2017. Sigma metrics were calculated on two identical analysers, using internal quality control data and total allowable error guidelines from the Ricos biological variation database and three alternative sources (the Royal College of Pathologists of Australasia, the Clinical Laboratory Improvements Amendment, and the European Federation of Clinical Chemistry and Laboratory Medicine).

Results: The sigma performance was similar on both analysers but varied based on the guideline used, with the Clinical Laboratory Improvements Amendment guidelines resulting in the best sigma metrics (53% of analytes on one analyser and 46% on the other had acceptable sigma metrics) and the Royal College of Pathologists of Australia guidelines being the most stringent (21% and 23%). Sodium and chloride performed poorly across all guidelines (sigma < 3). There were also month-to-month variations that may result in acceptable sigma despite poor performance during certain months.

Conclusion: The sigma varies greatly depending on the total allowable error, but could be a valuable tool to save time and decrease costs in high-volume laboratories. Sigma metrics calculations need to be standardised.

 


Keywords

quality control; diagnostic errors; laboratories; clinical chemistry tests; sigma metrics; Six Sigma; chemical pathology

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