Evaluation of the clinical chemistry tests analytical performance with Sigma Metric by using different quality specifications - Comparison of analyser actual performance with manufacturer data

Abstract

Introduction The interest in quality management tools/methodologies is gradually increasing to ensure quality and accurate results in line with international standards in clinical laboratories. Six Sigma stands apart from other methodologies with its total quality management system approach. However, the lack of standardization in tolerance limits restricts the advantages for the process. Our study aimed both to evaluate the applicability of analytical quality goals with Roche Cobas c 702 analyser and to determine achievable goals specific to the analyser used. Materials and methods The study examined under two main headings as Sigma laboratory and Sigma analyser . Sigma laboratory was calculated using internal and external quality control data by using Roche Cobas c 702 analyser for 21 routine biochemistry parameters and, Sigma analyser calculation was based on the manufacturer data presented in the package inserts of the reagents used in our laboratory during the study. Sigma values were calculated with the six sigma formula. Results Considering the total number of targets achieved, Sigma analyser performed best by meeting all CLIA goals, while Sigma laboratory showed the lowest performance relative to biological variation (BV) desirable goals. Conclusions The balance between the applicability and analytical assurance of “goal-setting models” should be well established. Even if the package insert data provided by the manufacturer were used in our study, it was observed that almost a quarter of the evaluated analytes failed to achieve even “acceptable” level performance according to BV-based goals. Therefore, “state-of-the-art” goals for the Six Sigma methodology are considered to be more reasonable, achievable, and compatible with today’s technologies.

Evaluation of Measurement Performance of Routine Chemistry Analytes by Application of Sigma Metrics, Method Evaluation Decision (MEDx) Charts and Quality Goal Index (QGI)

“…A few authorities have proposed to raise the allowable limits to make it possible to strive for some reasonable and achievable goals. Turkish medical authorities have proposed to set TEa values at 9% for Na, K and Chloride each [3]. Even with these TEa values it is diffi cult to achieve high sigma levels without regular maintenance of the equipment, high quality type I water, well trained laboratory staff and a very tight IQC.…”

“…Laboratory staff can exercise full control only on the analytical phase of the total testing process [3]. During the analytical phase, however, the defects do not occur as discrete events but rather as a degree of variation from the actual/true value, therefore detecting and then counting a defect is more diffi cult.…”

Supply Chain Resilience Meets Quality Management

“…It is centered on quality and aims for long-term success through customer satisfaction and benefits to all members of the organization and society (Danuri et al, 2021). On the other hand, Six Sigma is a methodology that focuses on reducing defects and improving process performance (Keleş, 2022). The integration of Lean and Six Sigma, known as Lean Six Sigma (LSS), combines the waste reduction principles of Lean with the defect reduction principles of Six Sigma (Scheller et al, 2018).…”

Bias, the unfinished symphony

“…To the Editor, I read the paper "Bias estimation for Sigma metric calculation: Arithmetic mean versus quadratic mean" written by Ercan et al with great interest (1). In the paper, the author criticized the approach of taking the arithmetic mean of the multiple biases to obtain a single bias and proposed a new method (quadratic mean) to estimate the overall bias using external quality assurance services (EQAS) data for sigma metric (SM) calculation (2). The bias issue has been a kind of unfinished symphony and is rarely evaluated correctly.…”