Open AccessEvaluation of clinical biochemical laboratory analytical process performance using sigma metrics and quality goal index
Author(s) -
Rogious Mbasani,
AUTHOR_ID,
Luo Xigang,
Nelson Musilanga,
AUTHOR_ID,
AUTHOR_ID
Publication year - 2021
Publication title -
chinese journal of medical research
Language(s) - English
Resource type - Journals
eISSN - 2663-8053
pISSN - 2618-091X
DOI - 10.37515/cjmr.091x.4403
Subject(s) - six sigma , statistics , external quality assessment , quality (philosophy) , index (typography) , process (computing) , analyte , process capability index , reliability engineering , computer science , pearson product moment correlation coefficient , mathematics , operations management , work in process , engineering , chemistry , chromatography , philosophy , epistemology , lean manufacturing , world wide web , operating system
Background: Application of sigma matrics across clinical laboratory diagnostic process enables identification of errors in methods together with quality goal index can help point out the cause of unacceptable process performance. We believe the analytical performance of the clinical biochemistry laboratory standards do not meet the required quality according to six sigma standards. Aim and Objective: The study aimed at performance evaluation of clinical biochemical laboratory analytical process using sigma metrics and quality goal index. Methods: Sigma (σ) for the 20 analytes performed on HITACHI 7600 - 110 was calculated based on absolute bias, total allowable error (TEa) and coefficient of variation (CV). Two level internal quality control data obtained retrospectively from December 2020 to May 2021 was used to calculate the coefficient of variation. Bias was obtained from six month external quality control data. Total allowable error was obtained from three different sources. Quality goal index (QGI) was calculated to identify the cause of unwanted analyte performance. Results: Different sigma scores were obtained for analytes on different total allowable error standard, only triglyceride showed world class performance along all the three total allowable error standards. However, creatine kinase & total bilirubin showed world class on clinical laboratory improvement amendment (CLIA) and biological variable database (BVD). On the other hand, glucose, and aspertate amino transferase had poor or unacceptable performance on all the total allowable error standards. Conclusion: Six sigma is an excellent tool in evaluating the quality performance of clinical biochemistry laboratory analytical process, quality goal index can help identify the problem and westgard rules can help design individual quality improvement strategy.