scholarly journals Sigma metrics in quality control- An innovative tool

2022 ◽  
Vol 8 (4) ◽  
pp. 253-259
Author(s):  
Juby Sara Koshy ◽  
Afsheen Raza
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Assessment Tool ◽  
Clinical Laboratory ◽  
Density Lipoprotein ◽  
Internal Quality ◽  
Control Procedure ◽  
Gamma Glutamyl Transferase ◽  
Level 1 ◽  
Glutamyl Transferase

The clinical laboratory in today’s world is a rapidly evolving field which faces a constant pressure to produce quick and reliable results. Sigma metric is a new tool which helps to reduce process variability, quantitate the approximate number of analytical errors, and evaluate and guide for better quality control (QC) practices.To analyze sigma metrics of 16 biochemistry analytes using ERBA XL 200 Biochemistry analyzer, interpret parameter performance, compare analyzer performance with other Middle East studies and modify existing QC practices.This study was undertaken at a clinical laboratory for a period of 12 months from January to December 2020 for the following analytes: albumin (ALB), alanine amino transferase (SGPT), aspartate amino transferase (SGOT), alkaline phosphatase (ALKP), bilirubin total (BIL T), bilirubin direct (BIL D), calcium (CAL), cholesterol (CHOL), creatinine (CREAT), gamma glutamyl transferase (GGT), glucose (GLUC), high density lipoprotein (HDL), triglyceride (TG), total protein (PROT), uric acid (UA) and urea. The Coefficient of variance (CV%) and Bias % were calculated from internal quality control (IQC) and external quality assurance scheme (EQAS) records respectively. Total allowable error (TEa) was obtained using guidelines Clinical Laboratories Improvement Act guidelines (CLIA). Sigma metrics was calculated using CV%, Bias% and TEa for the above parameters. It was found that 5 analytes in level 1 and 8 analytes in level 2 had greater than 6 sigma performance indicating world class quality. Cholesterol, glucose (level 1 and 2) and creatinine level 1 showed >4 sigma performance i.e acceptable performance. Urea (both levels) and GGT (level 1) showed <3 sigma and were therefore identified as the problem analytes. Sigma metrics helps to assess analytic methodologies and can serve as an important self assessment tool for quality assurance in the clinical laboratory. Sigma metric evaluation in this study helped to evaluate the quality of several analytes and also categorize them from high performing to problematic analytes, indicating the utility of this tool. In conclusion, parameters showing lesser than 3 sigma need strict monitoring and modification of quality control procedure with change in method if necessary.

scholarly journals Implementing Self Sustained Quality Control Procedures in a Clinical Laboratory

2013 ◽  
Vol 52 (189) ◽  
pp. 233-237 ◽  
Author(s):  
Roshan Khatri ◽  
Sanjay KC ◽  
Prabodh Shrestha ◽  
J N Sinha
Keyword(s):  
Quality Control ◽  
Clinical Laboratory ◽  
Reliability And Validity ◽  
Disease Diagnosis ◽  
Mitigation Measures ◽  
Internal Quality ◽  
Control Procedure ◽  
Random Errors ◽  
Control Rules ◽  
Control Serum

Introduction: Quality control is an essential component in every clinical laboratory which maintains the excellence of laboratory standards, supplementing to proper disease diagnosis, patient care and resulting in overall strengthening of health care system. Numerous quality control schemes are available, with combinations of procedures, most of which are tedious, time consuming and can be “too technical” whereas commercially available quality control materials can be expensive especially for laboratories in developing nations like Nepal. Here, we present a procedure performed at our centre with self prepared control serum and use of simple statistical tools for quality assurance. Methods: The pooled serum was prepared as per guidelines for preparation of stabilized liquid quality control serum from human sera. Internal Quality Assessment was performed on this sample, on a daily basis which included measurement of 12 routine biochemical parameters. The results were plotted on Levey-Jennings charts and analysed with quality control rules, for a period of one month. Results: The mean levels of biochemical analytes in self prepared control serum were within normal physiological range. This serum was evaluated every day along with patients’ samples. The results obtained were plotted on control charts and analysed using common quality control rules to identify possible systematic and random errors. Immediate mitigation measures were taken and the dispatch of erroneous reports was avoided. Conclusions: In this study we try to highlight on a simple internal quality control procedure which can be performed by laboratories, with minimum technology, expenditure, and expertise and improve reliability and validity of the test reports. Keywords: Levey-Jennings charts; pooled sera; quality control; Westgard Rule.

scholarly journals Sigma Metrics: A Powerful Tool for Performance Evaluation and Quality Control Planning in a Clinical Biochemistry Laboratory

2021 ◽  
Author(s):  
Trupti Diwan Ramteke ◽  
Anita Shivaji Chalak ◽  
Shalini Nitin Maksane
Keyword(s):  
Quality Control ◽  
Quality Management System ◽  
Clinical Laboratory ◽  
Clinical Biochemistry ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Internal Quality ◽  
Method Performance ◽  
Control Measurement ◽  
Clinical Biochemistry Laboratory

Introduction: Any error in the laboratory testing processes can affect the diagnosis and patient management. Six Sigma is a data driven quality management system for identifying and reducing errors and variations in clinical laboratory processes. Aim: This study was carried out to estimate Sigma metrics of various biochemical analytes in order to evaluate performance of quality control and implement optimum quality control strategy for each analyte. Quality goal index (QGI) was also calculated to identify the problems of inaccuracy and imprecision for parameters having lower sigma values. Materials and Methods: This retrospective, observational study was conducted at the Central Clinical Biochemistry Laboratory of Seth GS Medical College and KEM hospital in Mumbai for a period of six months (July 2019 to December 2019). Sigma metrics for 20 analytes was calculated by using internal quality control and external quality control data. Further, QGI was calculated for analytes having sigma value of <4 to identify imprecision or inaccuracy. Statistical analysis was performed using Microsoft office excel 2010 software. Results: Total protein, Glucose, Urea, Triglyceride (TAG), High Density Lipoprotein (HDL), and Low Density Lipoprotein (LDL) for normal (L1) and pathological (L2) controls achieved excellent performance (>6 sigma). Westgard rule (13s) with two control measurement (N2) per QC event and run size (R1000) i.e. 1000 patient samples between consecutive QC events was adopted for these analytes. For analytes with sigma value of 4-6, more rules (sigma 4-5: Westgardrules-13s/22s/R4s/41s, N4 and R200 and for sigma value 5-6: 13S/22s/R4s, N2 and R450) were adopted. The sigma values of six analytes (Creatinine, Sodium, Potassium, Calcium, Chloride, Inorganic phosphate) were <4 at one or more QC levels. For these analytes, strict QC procedures (Westgard rules-13s/22s/R4s/41s/6x, N4 and R45) were incorporated. QGI of these analytes was <0.8 which indicated the problem of imprecision. Staff training programs and review of standard operating procedures were done for these analytes to improve method performance. Conclusion: Sigma Metrics estimation helps in designing optimum QC protocols, minimising unnecessary QC runs and reducing the cost for analytes having high sigma metrics. Focused and effective QC strategy for analytes having low sigma helps in improving the performance of those analytes.

Quality control of lipid measurements in epidemiological studies: the U.S. Air Force HEART program.

1985 ◽  
Vol 31 (2) ◽  
pp. 261-263 ◽  
Author(s):  
A Hainline ◽  
P Hill ◽  
L Garbaczewski ◽  
C Winn
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Air Force ◽  
Reference Materials ◽  
Internal Control ◽  
Density Lipoprotein ◽  
Quality Assurance Program ◽  
Internal Quality ◽  
Surveillance Program ◽  
The U.S

Abstract A special standardization and quality assurance program, similar to that created for the Lipid Research Clinics Program (LRC), was developed for the American Health Foundation Laboratory by the Centers for Disease Control (CDC) to assure the quality of lipid measurements in the U.S. Air Force Health Evaluation and Risk Tabulation (HEART) Program. This study was designed to test the feasibility of reducing the incidence of heart disease in active-duty U.S. Air Force personnel through life-study intervention. During the 18-month study, CDC provided serum calibrators and reference materials for internal control and an external surveillance program for measurements of total cholesterol (TC) and high-density-lipoprotein cholesterol (HDLC). The Laboratory, using an automated enzymic method to measure cholesterol, achieved an overall goal for accuracy of less than 2% error (av systematic error, -30.6 mg/L) for TC, as measured on nine reference pools for which values were assigned by CDC. The average bias of measurements of HDLC with heparin-manganese to separate the lipoproteins in five CDC reference pools was -4.6 mg/L. Bias was estimated relative to the values assigned to the reference materials by the CDC reference methods for TC and HDLC. The average CV for TC was 0.89%, for HDLC 2.66%. Accuracy of cholesterol measurements can be assured over time with a standardization and quality-assurance program that incorporates accurately labeled reference materials for calibration, internal quality control, and external surveillance.

scholarly journals Application of Sigma Metrics for Evaluating the Analytical Performance of Thyroid Profile and Cortisol in Clinical Biochemistry Laboratory

2020 ◽  
Author(s):  
Smita Natvarbhai Vasava ◽  
Roshni Gokaldas Sadaria
Keyword(s):  
Quality Control ◽  
Six Sigma ◽  
Clinical Laboratory ◽  
Clinical Biochemistry ◽  
Poor Performance ◽  
Analytical Performance ◽  
Internal Quality ◽  
Six Sigma Methodology ◽  
Clinical Biochemistry Laboratory ◽  
Thyroid Profile

Introduction: Now-a-days quality is the key aspect of clinical laboratory services. The six sigma metrics is an important quality measurement method for evaluating the performance of the clinical laboratory. Aim: To assess the analytical performance of clinical biochemistry laboratory by utilising thyroid profile and cortisol parameters from Internal Quality Control (IQC) data and to calculate sigma values. Materials and Methods: Study was conducted at Clinical Biochemistry Laboratory, Dhiraj General Hospital, Piparia, Gujarat, India. Retrospectively, IQC data of thyroid profile and cortisol were utilised for six subsequent months (July to December 2019). Coefficient of Variation (CV%) and bias were calculated from IQC data, from that the sigma values were calculated. The sigma values <3, >3 and >6 were indicated by poor performance procedure, good performance and world class performance, respectively. Results: The sigma values were estimated by calculating mean of six months. The mean sigma value of Thyroid Stimulating Hormone (TSH) and Cortisol were >3 for six months which indicated the good performance. However, sigma value of Triiodothyronine (T3), Tetraiodothyronine (T4) were found to be <3 which indicated poor performance. Conclusion: Six sigma methodology applications for thyroid profile and cortisol was evaluated, it was generally found as good. While T3 and T4 parameters showed low sigma values which requires detailed root cause analysis of analytical process. With the help of six sigma methodology, in clinical biochemistry laboratories, an appropriate Quality Control (QC) programming should be done for each parameter. To maintain six sigma levels is challenging to quality management personnel of laboratory, but it will be helpful to improve quality level in the clinical laboratories.

Applicability of various quality-control sera to assay of high-density lipoprotein cholesterol.

1980 ◽  
Vol 26 (7) ◽  
pp. 903-907
Author(s):  
D G Bullock ◽  
T J Carter ◽  
S V Hughes
Keyword(s):  
Quality Control ◽  
High Density Lipoprotein ◽  
Quality Assessment ◽  
High Density Lipoprotein Cholesterol ◽  
External Quality Assessment ◽  
Density Lipoprotein ◽  
High Density ◽  
Lipoprotein Cholesterol ◽  
Internal Quality ◽  
External Quality

Abstract Effective internal quality control and external quality assessment of high-density lipoprotein cholesterol assay is made difficult by analyte instability, and the suitability of quality-control sera for this purpose has not been studied. We have therefore investigated the properties of 25 different control sera from 15 suppliers by estimating within-batch precision for the two precipitation procedures used most widely (phosphotungstate/Mg2+ and heparin/Mn2+ with enzymic measurement of cholesterol. Some sera had properties similar to those of fresh human serum, but others demonstrated poor precision for one or both procedures or contained apparent high-density lipoprotein cholesterol in unphysiological concentrations. A study of six sera indicated that between-batch precision was consistent with the within-batch findings. We found that eight of the 25 batches of quality-control serum we investigated may be used for internal quality control and external quality assessment of high-density lipoprotein cholesterol assay.

scholarly journals Lifetime duration of lactation and chronic inflammation among middle-aged women with a history of gestational diabetes

2020 ◽  
Vol 8 (2) ◽  
pp. e001229
Author(s):  
Sylvia H Ley ◽  
Jorge E Chavarro ◽  
Stefanie N Hinkle ◽  
Mengying Li ◽  
Michael Y Tsai ◽  
...  
Keyword(s):  
Gestational Diabetes ◽  
Chronic Inflammation ◽  
Density Lipoprotein ◽  
Lipoprotein Cholesterol ◽  
Health Study ◽  
Gamma Glutamyl Transferase ◽  
Middle Aged ◽  
History Of ◽  
Glutamyl Transferase

IntroductionLonger duration of lactation is associated with lower cardiometabolic disease risk, but pathogenic pathways involved in the disease progression are unclear, especially among high-risk women. We aimed to examine the associations of lifetime lactation duration with cardiometabolic biomarkers among middle-aged women with a history of gestational diabetes (GDM).Research design and methodsWomen with a history of GDM participating in the Nurses’ Health Study II, a prospective cohort study, were identified and followed through biennial questionnaires beginning in 1991. Lactation history was asked in three follow-up questionnaires to calculate lifetime duration. In 2012–2014, fasting blood samples were collected through the Diabetes & Women’s Health Study to measure inflammatory (C-reactive protein (CRP), interleukin (IL) 6), liver enzyme (alanine aminotransferase, aspartate aminotransferase, and gamma-glutamyl transferase), and lipid biomarkers (total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol).ResultsAt follow-up blood collection, women were at median age 58.2 (95% CI 51 to 65) years and 26.3 (95% CI 15.7 to 34.1) years since GDM index pregnancy. After multiple adjustment including prepregnancy body mass index (BMI), longer duration of lactation was significantly associated with lower CRP (least squares (LS) mean 1.90 mg/L (95% CI 1.47 to 2.45) for 0-month lactation, 1.98 mg/L (95% CI 1.68 to 2.32) for up to 12-month lactation, 1.67 mg/L (95% CI 1.42 to 1.97) for 12–24 month lactation, and 1.39 mg/L (95% CI 1.19 to 1.62) for >24-month lactation; p trend=0.003) and IL-6 (1.25 pg/L (95% CI 0.94 to 1.68), 1.19 pg/L (95% CI 0.99 to 1.42), 1.04 pg/L (95% CI 0.87 to 1.25), and 0.93 pg/L (95% CI 0.78 to 1.11); p trend=0.04). Longer duration of lactation was associated with lower risk for chronic inflammation using CRP 3 mg/L cut-off in middle-aged women (OR 0.81 (95% CI 0.69 to 0.940 per 1-year increase) with multiple adjustment.ConclusionsLonger lifetime duration of lactation was associated with favorable inflammatory biomarker concentrations in middle-aged women with a history of GDM. Chronic inflammatory pathways may be responsible for previously reported associations between lactation and long-term risk for cardiometabolic diseases.

Internal Quality Control of PCR-based Genotyping Methods in Research Studies and Patient Diagnostics

2002 ◽  
Vol 87 (05) ◽  
pp. 812-816 ◽  
Author(s):  
Jørgen Gram ◽  
Jørgen Jespersen ◽  
Moniek de Maat ◽  
Else-Marie Bladbjerg
Keyword(s):  
Quality Control ◽  
Clinical Laboratory ◽  
Dna Amplification ◽  
Restriction Enzymes ◽  
Control Programme ◽  
Internal Quality Control ◽  
Internal Quality ◽  
Reagent Blank ◽  
Thrombosis Research ◽  
Control Programmes

SummaryGenetic analyses are increasingly integrated in the clinical laboratory, and internal quality control programmes are needed. We have focused on quality control aspects of selected polymorphism analyses used in thrombosis research. DNA was isolated from EDTA-blood (n = 500) by ammonium acetate precipitation and analysed for 18 polymorphisms by polymerase chain reaction (PCR), i. e. restriction fragment length polymorphisms, allele specific amplification, or amplification of insertion/deletion fragments. We evaluated the following aspects in the analytical procedures: sample handling and DNA-isolation (pre-analytical factors), DNA-amplification, digestion with restriction enzymes, electrophoresis (analytical factors), result reading and entry into a database (post-analytical factors). Furthermore, we evaluated a procedure for result confirmation. Isolated DNA was of good quality (42 µ.g/ml blood, A260/A280 ratio >1.75, negative DNAsis tests), and the reagent blank was contaminated in <1% of the results. Occasionally, results were re-analysed because of positive reagent blanks (<1%) or because of problems with the controls (< 5%). On confirmation, we observed 4 genotyping discrepancies. Control of data handling revealed 0.1% reading mistakes and 0.5% entry mistakes. Based on our experiences we propose an internal quality control programme for widely used PCR-based haemostasis polymorphism analyses.

Design of internal quality control for reference value studies

2004 ◽  
Vol 42 (7) ◽  
Author(s):  
James O. Westgard
Keyword(s):  
Quality Control ◽  
Systematic Error ◽  
Total Error ◽  
Reference Value ◽  
Internal Quality Control ◽  
Internal Quality ◽  
Control Procedure ◽  
Graphical Tool ◽  
Critical Error ◽  
Power Curves

AbstractInternal quality control should assure that the desired quality goals are achieved during reference value studies. Quality goals are often stated in the form of allowable limits of error, such as an allowable total error or an allowable bias. For reference value studies, it may be more appropriate to utilize a goal for allowable bias. In either case, it is possible to calculate a metric in the form of the critical systematic error that can be used to guide selection or design of the internal quality control procedure. A graphical tool, called the critical-error graph, facilitates the selection by superimposing the calculated critical systematic error on the power curves of different control rules and numbers of control measurements. Examples are provided to illustrate the calculation of the critical systematic error from both an allowable total error goal and an allowable bias goal, using figures from an extensive tabulation of available total error and bias goals.

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