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.

Practice of patient based quality assessment procedure in clinical chemistry unit at diagnostic laboratories in Nepal

2013 ◽  
Vol 1 (1) ◽  
pp. 9-17
Author(s):  
P Gyawali ◽  
S Tamrakar ◽  
N Lamsal ◽  
RK Shresta
Keyword(s):  
Quality Control ◽  
Clinical Laboratory ◽  
Clinical Chemistry ◽  
Vital Role ◽  
Control Procedure ◽  
Assessment Procedure ◽  
Random Errors ◽  
Quality Control Procedure ◽  
Total Testing Process ◽  
Analytical Errors

Background: The clinical laboratory is the major producer of information used to diagnose, treat, and monitor patients. Errors in laboratory testing may occur at many different points in the total testing process (TTP). Application of quality control plays a vital role in recognizing probable errors. The current dominant technique for error identification uses quality control materials has several inherent drawbacks; otherwise, patient based quality control procedure ensures the detection of pre-analytical errors, analytical, post-analytical errors, clerical errors, and random errors that cannot be detected using commonly used quality control methods, thereby improving the reliability of clinical tests. Objective: Thus the objective of this study was to evaluate the practice of patient based quality control procedure in clinical chemistry unit at diagnostic laboratories in Nepal. Materials and Methods: The questionnaire based study was conducted in clinical chemistry unit of diagnostic laboratories across the country. Questionnaires were personally dropped in 217 clinical biochemistry laboratories and were asked to complete a practice based questionnaire. The responses of 169 laboratories were analyzed using Microsoft Excel 2007 and expressed in terms of percentage. Results: In foremost study undertaken, a total of 169 laboratories responded to the questionnaire. A total 65.9 % of the laboratories monitored errors using patient based quality control procedure but not as a part of quality control. Very few of participant.s laboratories responded accurately regarding utility and practical aspects of patient based quality control included in the checklist. Conclusion: Practice of patient based quality control procedure was not well established to identify possible errors. Hence, the study extent the existing information and explored that the current classical approaches were not adequate to assure accurate patients test results for specific analytes. DOI: http://dx.doi.org/10.3126/stcj.v1i1.7983 Sunsari Technical College Journal Vol.1(1) 2012 9-17

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 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.

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.

A STATEWIDE Internal quality control procedure for general chemistry: AN UPDATE

Pathology ◽  
2017 ◽  
Vol 49 ◽  
pp. S96-S97
Author(s):  
Gemma M. Daley ◽  
Karen Noy ◽  
Mary Hardwick ◽  
David Clarke ◽  
Nigel Brown
Keyword(s):  
Quality Control ◽  
General Chemistry ◽  
Internal Quality Control ◽  
Internal Quality ◽  
Control Procedure ◽  
Quality Control Procedure

scholarly journals A Quality Control Procedure Based on Bending Angle Measurement Uncertainty for Radio Occultation Data Assimilation in the Tropical Lower Troposphere

2018 ◽  
Vol 35 (10) ◽  
pp. 2117-2131 ◽  
Author(s):  
Hui Liu ◽  
Ying-Hwa Kuo ◽  
Sergey Sokolovskiy ◽  
Xiaolei Zou ◽  
Zhen Zeng ◽  
...  
Keyword(s):  
Quality Control ◽  
Data Assimilation ◽  
Radio Occultation ◽  
Lower Troposphere ◽  
Spectral Width ◽  
Angle Measurement ◽  
Control Procedure ◽  
Random Errors ◽  
Bending Angle ◽  
Occultation Data

AbstractThe fluctuation of radio occultation (RO) signals in the presence of refractivity irregularities in the moist lower troposphere results in uncertainties of retrieved bending angle and refractivity profiles. In this study the local spectral width (LSW) of RO signals, transformed to impact parameter representation, is used for the characterization of the uncertainty (random error) of retrieved bending angle and refractivity profiles. A large LSW has some correlation with the large mean difference (bias) of retrieved refractivity and bending angle from radiosondes and European Centre for Medium-Range Weather Forecasts analyses based on data from 2008 to 2014. An LSW-based quality control (QC) procedure is developed to eliminate low-quality (large random errors and biases) profiles from data assimilation. The LSW-based QC procedure is tested and evaluated in the assimilation of Constellation Observing System for Meteorology, Ionosphere and Climate RO data using the NCAR Data Assimilation Research Testbed and the Weather Research and Forecasting Model. Preliminary results, based on a 2-week data assimilation cycle, show that the LSW-based QC procedure improves water vapor analyses in the moist lower troposphere.

scholarly journals Standards versus Standardised Methods in Enzyme Assay

1983 ◽  
Vol 20 (1) ◽  
pp. 52-59 ◽  
Author(s):  
R T P Jansen ◽  
A P Jansen
Keyword(s):  
Quality Control ◽  
Alkaline Phosphatase ◽  
Creatine Kinase ◽  
Lactate Dehydrogenase ◽  
Alanine Aminotransferase ◽  
Enzyme Assay ◽  
Control Program ◽  
Internal Quality ◽  
Quality Control Program ◽  
Control Serum

In a trial of the Netherlands coupled external/internal quality control program a control serum and an enzyme standard were analysed over a period of eight weeks, five times each week. Five enzymes were determined: alkaline phosphatase, creatine kinase, lactate dehydrogenase, alanine aminotransferase, and γ-glutamyltransferase. The measured values in the serum were converted to the standards. Those laboratories using the recommended methods also submitted their non-transformed serum values. The following standardisation techniques have been compared: ( a) no standardisation of methodology but use of enzyme standards; ( b) standardisation of methodology; ( c) standardisation of methodology combined with use of an enzyme standard. Results were submitted to analysis of variance. Standardisation of methodology did not yield smaller interlaboratory variation than the standardisation with enzyme standards. In this trial a combination of both standardisation techniques yielded generally better results. Results for γ-glutamyltransferase indicate that standardisation of substrate may be necessary apart from the use of an enzyme standard. The preparation of stable enzyme standards is stressed.

scholarly journals Appraisal of the domestic kit «MICMICRO » for antimicrobial susceptibility testing by serial microdilution method

2020 ◽  
pp. 231-236
Author(s):  
Anna A. Samoilova ◽  
L.A. Kraeva ◽  
I.V. Likhachev ◽  
E.V. Rogacheva ◽  
V.N. Verbov ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Quality Control ◽  
Susceptibility Testing ◽  
New Technologies ◽  
Clinical Laboratory ◽  
Clinical Isolates ◽  
Internal Quality ◽  
Diagnostic Efficiency ◽  
Microdilution Method ◽  
Reference Strains

Objective. To assess efficiency of the “MIC-MICRO” kit developed in the Department of New Technologies of the Saint-Petersburg Pasteur Institute, on reference strains and clinical bacterial isolates. Materials and Methods. In order to assess the “MIC-MICRO” kit, several options of its execution were used, including different groups of antibiotics: aztreonam, amikacin, gentamicin, colistin, meropenem, nitrofurantoin, chloramphenicol, cefotaxime, ceftriaxone, ciprofloxacin, erythromycin. In order to determine the range of antibiotic values, the EUCAST-2020 database was used. The quality control of adsorbed antibiotics was carried out using reference strains: Escherichia coli ATCC 25922, Staphylococcus aureus ATCC 29213 and Escherichia coli NCTC 13846 (colistin-resistant). Acceptable and target ranges of MIC values for control strains are evaluated according to “Regular and extended internal quality control for determining MIC and disk diffusion according to EUCAST recommendations” (v10.0). A total of 28 clinical isolates of K. pneumoniae obtained from patients with nosocomial infections in St. Petersburg hospitals in 2018–2019 was used in the study. The coordination of test results was obtained in accordance with GOST R ISO 20776-1-2010. Susceptibility testing results were interpreted in accordance with EUCAST recommendations (v10.0). Results. The MIC values in relation to the reference strains obtained using the “MIC-MICRO” kit were determined in the range of recommended values of the EUCAST-2020 standard. The results obtained in relation to clinical isolates of K. pneumoniae showed that the sensitivity categories determined using the developed kit and the serial microdilution method were the same for all the studied strains. The percentage of colistin-resistant isolates (MIC > 2 mg/ml) in the serial microdilution method and determined using the “MIC-MICRO” kit was 35.7%. The percentage of susceptible strains was also similar for two types of methods (64.3%). Conclusions. Colistin susceptibility testing of K. pneumoniae strains using the “MIC-MICRO” diagnostic kit and the reference serial microdilution method in a tablet, showed comparable results. Diagnostic efficiency, ease to use and simple interpretation of results make it possible to use the developed “MIC-MICRO” kit in clinical laboratory practice.

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