Volume : 4
Issue : 3
Online ISSN : 2394-6377
Print ISSN : 2394-6369
Article First Page : 270
Article End Page : 274
Introduction: Accurate test results are the core of healthcare system since physician's decisions mostly depends on the laboratory results. The evaluation of laboratory performance is critical to maintain accurate laboratory results. Nowadays six sigma is the newest version of total quality management. It is quantitative goal for process performance. We aimed to gauge our clinical biochemistry laboratory performance on sigma metrics.
Materials and Method: Internal Quality control (QC) and proficiency testing data for 12 clinical chemistry analytes for two COBAS 400 Plus clinical biochemistry auto-analyzers were analyzed retrospectively over a period of 12 months from July 2012 to June 2013. For all 12 analytes the coefficient of variation was calculated for both the levels of IQC, percentage bias was calculated from EQAS. Process sigma was calculated using CV%, Percentage bias and TEa values of various parameters were taken from Clinical Laboratories Improvement Act (CLIA) guidelines.
Results: Satisfactory sigma values (> 6) were derived for Alkaline Phosphatase, Aspartate aminotransferase, Alanine aminotransferase (L2), Triglycerides, Uric acid, Glucose (L2) signifying less stringent QC rules in an order to achieve high error detection and low false rejection. For parameters - Albumin, Alanine aminotransferase (L1), Total Cholesterol, Total Bilirubin, Glucose (L1), Total Protein the sigma values were found between 3 & 6, signifying more QC rules to be implemented. Urea and Creatinine analytes performed poorly on the sigma scale with sigma < 3, signifying needs improvement in these methods. No significant difference was found in both COBAS equipments in context to sigma value.
Conclusion: Application of six sigma principles would significantly helps in improving IQC process as well provides the scientific basis for recommendation of amount of QC that is actually needed.
Keywords: Clinical Chemistry, Six sigma, Total allowable error, Bias, Coefficient of variance