Abstract
Introduction: One of the most popular quality management system tackle employed for process perfection is six sigma. When the process outcome is measurable, six sigma can be used to assess the quality. Aim: Present study was conducted with the objective to apply six sigma matrices and quality goal index for the assessment of quality assurance in a clinical biochemistry laboratory. Materials and methods: Present study is a retrospective study. Internal and external quality control data were analyzed retrospectively during July 2020 to December 2020. Descriptive statistics like laboratory mean ± standard deviation; bias and coefficient of variation (CV) were calculated for the parameters glucose, urea, creatinine, ALT (SGPT), AST (SGOT), cholesterol, triglyceride and HDL. Sigma value was calculated for both level I & level II of internal quality control (IQC). Results: Satisfactory sigma values (≥3) were elicited for blood glucose, cholesterol, triglyceride, HDL, urea and creatinine, while ALT (SGPT) and AST (SGOT) performed poorly (<3) on the sigma scale. The quality goal index (QGI) ratio was found (> 1.2) for only 2 parameters SGPT and SGOT (with sigma value <3) for both levels 1 and 2, indicating inaccuracy. Conclusion: Results of present study focuses on meticulous appraisal and execution of quality measures to improve sigma standards of all the analytical processes. Even though six sigma provides benefits over former approaches to quality assurance, it also opens newer challenges for laboratory practitioners. Therefore, sigma metric analysis provides a point of reference to design a protocol for IQC for the laboratory; address poor assess performance, and assess the existing laboratory process efficiency.
Highlights
One of the most popular quality management system tackle employed for process perfection is six sigma
Sigma metric analysis provides a point of reference to design a protocol for internal quality control (IQC) for the laboratory; address poor assess performance, and assess the existing laboratory process efficiency
The data obtained for the study are coefficient of variation percent (CV%) from internal quality data and Bias (%) for parameters glucose (Hexokinase method), urea (Urease method), creatinine (Enzymatic Creatinine method), alanine aminotransferase (ALT or SGPT) (IFCC Kinetic method), aspartate aminotransferase (AST or SGOT) (IFCC Kinetic method), cholesterol total (Cholesterol oxidase and peroxidase method), triglyceride (GPO - TOPS endpoint method) and HDL (Direct method)
Summary
One of the most popular quality management system tackle employed for process perfection is six sigma. When the process outcome is measurable, six sigma can be used to assess the quality. Laboratory error can be defined as any defect or deviation of result from true value. Internal Quality Control (IQC) and External Quality Assurance Service (EQAS) are presently the procedures that are being used for quality control in the analytical phase. The IQC shows the amount of variation that occurs in our results in the form of imprecision while EQAS helps in evaluating the accuracy or trueness of our results. All Production processes always have a certain tendency for error generation. The quantification of error in the analytical process cannot be expressed through IQC or EQAS procedures.
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