Assessment of sigma metrics results of serum glucose and lipid profile tested by automated chemistry analyzer in medical city hospitals in Iraq

Abstract

Background: A major target of quality assurance is the minimization of error rates in order to enhance patient safety, six sigma or sigma metrics were used to assess the analytical quality of automated clinical chemistry, six sigma metrics is used in combination with total allowable error, method imprecision and bias. The goal is to attain the highest possible sigma scale within the acceptable limits of total allowable error. For assessment of sigma metrics results of serum glucose and lipid profile and verification of reference values for these analytes tested by automated chemistry analyzer in Medical City hospitals.Methods: In the present study, internal quality control (EQA) and external quality assessment (EQA) data were analyzed for the period from May to July 2017 using chemistry autoanalyzer (Siemens Dimension RxL Max) at the Teaching Laboratories of the Medical City. Mean, standard deviation, coefficient of variation, bias, total error and sigma metrics were calculated for glucose, cholesterol, triglycerides and HDL.Results: Excellent sigma values (≥6) were elicited for triglycerides (10.9), Satisfactory sigma values (≥3) were elicited for cholesterol (3.4) and HDL (3.4), while glucose performed poorly (2.3) on the sigma scale.Conclusions: Sigma metrics helps to assess analytical methodologies and augment laboratory performance. It acts as a guide for planning quality control strategy. It can be a self-assessment tool regarding the functioning of clinical laboratory. Triglycerides was the best performer when it was gauzed on the sigma scale, with a sigma metrics value of 10.9 and glucose had the least sigma metrics value of 2.5 so there is need for improvement and the method should be controlled with greater attention to ensure quality.