Original Research
The application of sigma metrics in the laboratory to assess quality control processes in South Africa
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 AfricaJaya 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
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
Metrics
Total abstract views: 3397Total article views: 7354
Crossref Citations
1. Application of the six sigma model to evaluate the analytical performance of serum lipid analytes and design quality control strategies: A multi-centre study
Qian Liu, Yu Lin, Fang Yang, Yaping Dai, Huan Hang, Menglin Wang, Ming Hu, Fumeng Yang
Annals of Clinical Biochemistry: International Journal of Laboratory Medicine vol: 63 issue: 1 first page: 3 year: 2026
doi: 10.1177/00045632251350503
2. Beyond Total Error: An Observational Comparative Study of Sigma Metrics in Long-Term Arterial Blood Gas Analyzer Performance
Hussien Hamid, Mousa Al-Wafi, Mohamed H Ahmida, Abdulla M Elmansoury, Mohamed Najah
Cureus year: 2025
doi: 10.7759/cureus.77236
3. The Evaluation of the Quality Performance of Biochemical Analytes in Clinical Biochemistry Laboratory Using Six Sigma Matrices
Chhabi R Panda, Suchitra Kumari, Manaswini Mangaraj, Saurav Nayak
Cureus year: 2023
doi: 10.7759/cureus.51386
4. Sigma performance evaluations for clinical chemistry and immunoassays in a tertiary care hospital laboratory based on Clinical Laboratory Improvement Amendments (CLIA) 1988 and 2024 Guidelines
Bhavana Bais, Kriti Singh, Varijendra Tripathi
International Journal of Clinical Biochemistry and Research vol: 11 issue: 2 first page: 129 year: 2024
doi: 10.18231/j.ijcbr.2024.020
5. Analysis of hematology quality control using six sigma metrics
Shreya Goel, Amit R. Nisal, Ankita Raj, Ravindra C. Nimbargi
Indian Journal of Pathology and Microbiology vol: 67 issue: 2 first page: 332 year: 2024
doi: 10.4103/ijpm.ijpm_352_23
6. Six sigma in the evaluation of quality indicators using Roche Cobas c501 biochemistry analyzer
Vu Dinh Pham
Journal of Laboratory Physicians first page: 1 year: 2025
doi: 10.25259/JLP_285_2025
7. Comparison of the sigma metrics using the total error allowable algorithm with variation of bias source
Sonny Feisal Rinaldi, Anisa Agustia Ibadurrahmah, Surya Ridwanna, Harianto Harianto
Indonesian Journal of Medical Laboratory Science and Technology vol: 6 issue: 1 first page: 27 year: 2024
doi: 10.33086/ijmlst.v6i1.4930
8. Discrepancies in Sigma Metrics Driven by Total Allowable Error Variability: Implications for QC Strategy and Laboratory Efficiency
Mariem Othmani, Yessine Amri, Siwar Chelbi, Sondess Hadj Fredj, Taieb Messaoud, Rym Dabboubi
The Journal of Applied Laboratory Medicine vol: 11 issue: 1 first page: 48 year: 2026
doi: 10.1093/jalm/jfaf177
