Quality Control In Clinical Laboratory Research Articles

QC Constellation: a cutting-edge solution for risk and patient-based quality control in clinical laboratories.

Clinical laboratories face limitations in implementing advanced quality control (QC) methods with existing systems. This study aimed to develop a web-based application to addresses this gap, and improve QC practices. QC Constellation, a web application built using Python 3.11, integrates various statistical QC modules. These include Levey-Jennings charts with Westgard rules, sigma-metric calculations, exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts, and method decision charts. Additionally, it offers a risk-based QC section and a patient-based QC module aligning with modern QC practices. The codes and the web application links for QC Constellation were shared at https://github.com/hikmetc/QC_Constellation, and http://qcconstellation.com, respectively. Using synthetic data, QC Constellation demonstrated effective implementation of Levey-Jennings charts with user-friendly features like checkboxes for Westgard rules and customizable moving averages graphs. Sigma-metric calculations for hypothetical performance values of serum total cholesterol were successfully performed using allowable total error and maximum allowable measurement uncertainty goals, and displayed on method decision charts. The utility of the risk-based QC module was exemplified by assessing QC plans for serum total cholesterol, showcasing the application's capability in calculating risk-based QC parameters including maximum unreliable final patient results, risk management index, and maximum run size andoffering risk-based QC recommendations. Similarly, the patient-based QC and optimization modules were demonstrated using simulated sodium results. In conclusion, QC Constellation emerges as a pivotal tool for laboratory professionals, streamlining the management of quality control and analytical performance monitoring, while enhancing patient safety through optimized QC processes.

Effect of Night Shift Work in Clinical Laboratories on Pediatric Complete Blood Count Results.

There has been much research into the impact of shift systems on clinicians and nurses, but little research into quality control in clinical laboratories. This topic focuses on assessing the impact of shift systems on clinical laboratory scientists. A total of 34,955 CBCs from pediatric patients who visited the hospital during night-time hours over a period of three years were selected for analysis. The quality of routine blood tests was evaluated using four indica-tors: red blood cell count, white blood cell count, platelet count, and hemoglobin levels. The effects of gender, years of experience, and length of the night shift on test results were evaluated separately for each clinical laboratory scientist. The results showed that the gender and years of experience of the clinical laboratory scientists did not affect the CBC results. However, a significant impact was observed as the number of hours worked on night shifts increased. The findings of this study suggest that the night shift schedule of clinical laboratory scientists can have an impact on the accuracy of pediatric CBCs. It is essential for healthcare institutions to consider the length of night shifts for clinical laboratory scientists and implement measures to minimize the impact on test results.

Pooled Sera as an Alternative to Commercial Internal Quality Control in Clinical Laboratories

Introduction: Internal Quality Control (IQC) is run to assess the day-to-day performance of an analytical process, ensuring the reliability of patient results. However, commercial internal quality materials can be expensive and inaccessible for many laboratories. Therefore, there is a need for an effective and economical alternative to commercial IQC. Aim: To evaluate the effectiveness and stability of pooled sera as an IQC material. Materials and Methods: A laboratory study was conducted over a period of 50 days, from January 10 to February 28, 2023, in the Department of Biochemistry at Dr. Rajendra Prasad Government Medical College (DRPGMC), Kangra, Himachal Pradesh, India. Serum samples (150 μL) were collected from 100 leftover samples over a span of 10 days. The serum was thoroughly mixed and distributed into 75 aliquots. Commercial IQC was also reconstituted and distributed into 75 aliquots. Both the commercial and pooled sera IQC were stored at -20°C. One aliquot of pooled sera was analysed daily for 16 routine biochemistry parameters, along with the commercial IQC, for the entire 50-day period. The results from both materials were interpreted using L-J chart and Westgard multirule. The stability of pooled sera for these routine parameters was assessed by comparing the mean values of the biochemical parameters on day 1 and day 50. Data analysis was performed using Statistical Package for the Social Sciences (SPSS) version 20.0 software, and a paired t-test with a p-value <0.05 was considered statistically significant. The bias percentage for each pooled sera parameter was calculated and compared with the desirable bias for clinical significance. Results: Analytical errors were observed during the study period for Alkaline Phosphatase (ALP), urea, sodium, potassium, and chloride. The nature and number of analytical errors observed with both materials were the same, with Westgard rule 13s detecting random errors for ALP and rule 22s detecting systematic errors for urea and serum electrolytes (sodium, potassium, and chloride). Difference in the mean value of alanine transaminase, aspartate transaminase, and bilirubin, on day 1 and day 50 was statistically significant with p-values 0.035, 0.04, and 0.024, respectively. When these parameters were assessed for clinical bias, they were found to be clinically insignificant. Conclusion: Pooled serum is an effective and stable alternative IQC material for daily performance assessment of analytical processes. In-house IQC or pooled sera not only reduces the cost of quality control but also helps maintain continuity in the absence of commercial IQC, preventing any disruptions in the control system over an extended period.

臨床検査室において人工知能は精度管理の有用なツールとなりうるか？―第1回International Young BLS Forumへの取り組み―

臨床検査室において人工知能は精度管理の有用なツールとなりうるか？―第1回International Young BLS Forumへの取り組み―

External clinical laboratory quality control survey of clinical chemistry field from 2016 to 2018 in Aichi

External clinical laboratory quality control survey of clinical chemistry field from 2016 to 2018 in Aichi

The Influence of Quality Control in Clinical Laboratory: Lean and Six-sigma Approaches

The Influence of Quality Control in Clinical Laboratory: Lean and Six-sigma Approaches

Better get moving on laboratory quality assurance.

With recent advances in laboratory hematology automation, emphasis is now on quality assurance processes as they are indispensable for generating reliable and accurate test results. It is therefore imperative to acquire efficient measures for recognizing laboratory malfunctions and errors to improve patient safety. The paper aims to discuss these issues. Moving algorithm is a quality control process that monitors analyzer performance from historical records through a continuous process, which does not require additional expenditure, and can serve as an additional support to the laboratory quality control program. The authors describe an important quality assurance tool, which can be easily applied in any laboratory setting, especially in cost-constrained areas where running commercial controls throughout every shift may not be a feasible option. The authors focus on clinical laboratory quality control measures for providing reliable test results. The moving average appears to be a reasonable and applicable choice for vigilantly monitoring each result.

Quality Assurance and Quality Control in Clinical Laboratories

Health care delivery is no longer a simple process of examining the patient and giving him a prescription. Over the years there has been rapid expansion in the various branches of health care services. As part of this expansion process and explosion of scientific medical knowledge, laboratory diagnosis has gained tremendous importance in today’s practice. Especially in our country since the beginning of 80’s we have been witnessing significant growth in laboratory services. Through quality management process the laboratory can ensure that the result being issued by the laboratory is reliable to allow decisions to be taken with confidence. Quality control and quality assurance are parts of quality management. Quality control is focused on fulfilling quality requirements, whereas quality assurance is focused on providing confidence that quality requirements are fulfilled. By utilizing quality control practices, a laboratory is able to find and correct flaws in the analytical processes of a lab before potentially incorrect patient results are released.Pulse Vol.8 January-December 2015 p.62-65

Six Sigma Metrics and Quality Control in Clinical Laboratory

Quality control in healthcare system is still less understood because of the relative complexity in choosing an appropriate Westgard rule .Six Sigma methodology is a manufacturing strategy first pioneered by Motorola Company in 1980s, with the goal of decreasing the defect rates in production .It has improved the production efficiency of different industries. To achieve the similar high quality and near zero defect rates in healthcare system, six sigma metrics is being used in many clinical laboratories and diagnostic industry. Six sigma metrics is used in combination with total allowable error (CLIA ’88 proficiency testing criteria), method imprecision and bias. The goal is to attain the highest possible sigma scale within the acceptable limits of total allowable error. This article reviews the different Westgard control rules and their implications in pointing towards a particular error, as well as basic principles of Six Sigma methodology & their practical utility in the clinical laboratory

Expression and purification of a functional recombinant aspartate aminotransferase (AST) from Escherichia coli.

Aspartate aminotransferase (AST; E.C. 2.6.1.1), a vitamin B6-dependent enzyme, preferentially promotes the mutual transformation of aspartate and α-ketoglutarate to oxaloacetate and glutamate. It plays a key role in amino acid metabolism and has been widely recommended as a biomarker of liver and heart damage. Our study aimed to evaluate the extensive preparation of AST and its application in quality control in clinical laboratories. We describe a scheme to express and purify the 6His-AST fusion protein. An optimized sequence coding AST was synthesized and transformed into Escherichia coli BL21 (DE3) strain for protein expression. Ideally, the fusion protein has a volumetric productivity achieving 900 mg/l cultures. After affinity chromatography, the enzyme activity of purified AST reached 150,000 U/L. Commutability assessment between the engineered AST and standard AST from Roche suggested that the engineered AST was the better candidate for the reference material. Moreover, the AST showed high stability during long-term storage at -20ºC. In conclusion, the highly soluble 6His-tagged AST can become a convenient tool for supplying a much better and cheaper standard or reference material for the clinical laboratory.

Establishment of an assigned value and its uncertainty for tumour markers in proficiency testing in China

Proficiency testing (PT) is an important aspect of clinical laboratory quality control for tumour markers. To evaluate the performance of an individual laboratory, the assigned value and the standard uncertainty of each tumour marker must be determined. However, no data about the standard uncertainty of the assigned value of any analyte in PT is available in China. The aim of this paper is to introduce a new approach for establishment of assigned value and its standard uncertainty for tumour markers. Five sets of control materials at different concentrations were assigned to each laboratory that participated in PT for tumour markers in 2012. We collected the data from each laboratory using the Clinet-EQA reporting system V1.5 and Clinet-EQA evaluation system V1.0 and developed a software program to calculate the assigned value and its uncertainty according to ISO 13528 (Statistical methods for use in proficiency testing by interlaboratory comparisons. ISO 13528. International Standards Organisation, Geneva, 2005). The assigned value and inter-laboratory CV calculated by the new approach was compared with that obtained by the current approach used in PT in our country. No significant difference between the two outcomes was found in our study. Most assigned values had a standard uncertainty that can meet the criterion: \( u_{X} \le \, 0.3\hat{\sigma } \), which meant the new approach for establishment of the assigned value was acceptable. It is expected that the new approach to determination of the assigned value and its standard uncertainty for PT for tumour markers in China will enable participants to evaluate their measurement uncertainty.

Patient result median monitoring for clinical laboratory quality control

BackgroundStatistical process control is foundational in laboratory medicine. It typically uses artificial control specimens and can detect some, but not all, analytical defects. A practical, robust method to more directly detect trends in patient results, such as monitoring mean or median patient results, is desirable. MethodsWe generated a simulated set of laboratory results from a normal distribution, and also downloaded sequential patient results for serum sodium and CA 19–9. For each of the three data sets we calculated the standard error of the mean and estimated the standard error of the median by bootstrapping. ResultsThe standard error of the mean is a practical, easily calculated summary statistic that can be used to construct control charts. The standard error of the median, cannot be reliably estimated without using bootstrap methods, but is more resistant to outliers. Our study confirms a simple relationship between the variance of the median and the variance of the mean, i.e., for Gaussian distributions, Var[Median]Var[Mean]=π2 We also confirm that for skewed distributions, the median is more stable than the mean, implying Var[Median]Var[Mean]<1. Finally, we establish a sample size of 200 individual patient results as sufficient for monitoring medians for data from approximately Gaussian distributions. ConclusionsMonitoring patient result medians represents a practical, statistically self-consistent approach to laboratory quality control.

Toward standardization of quality assessment in laboratory medicine by using the same matrix samples for both internal and external quality assessments

The main purpose of quality assurance procedures in clinical laboratories is to ensure that test results are appropriate to maintain excellence in the diagnosis, monitoring, and treatment of disease. However, in current practice, no standardized procedure or frequency for the evaluation of methods exists, particularly in external quality assessment. Furthermore, different quality control materials are typically used for internal and external quality assessment. To overcome these discrepancies, we used samples with the same matrix for both internal and external quality assessments of a group test performed in our laboratory. We then calculated total error using real bias (target value obtained by reference method) and the imprecision of each test and compared our results with the total error allowable, derived from biological variation data. We suggest that the strategy of using the same matrix samples for both internal and external quality assessment is cost-effective, can be readily used by staff, and will facilitate the standardization of quality control in clinical laboratories.

Experimental Validation of Peptide Immunohistochemistry Controls

Peptide immunohistochemistry (IHC) controls are a new quality control format for verifying proper IHC assay performance, offering advantages in high throughput automated manufacture and standardization. We previously demonstrated that formalin-fixed peptide epitopes, covalently attached to glass microscope slides, behaved (immunochemically) in a similar fashion to the native protein in tissue sections. To convert this promising idea into a practical clinical laboratory quality control tool, we tested the hypothesis that the quality assurance information provided by peptide IHC controls accurately reflects IHC staining performance among a diverse group of clinical laboratories. To test the hypothesis, we first designed and built an instrument for reproducibly printing the controls on microscope slides and a simple software program to measure the color intensity of stained controls. Automated printing of peptide spots was reproducible, with coefficients of variation of 4% to 8%. Moreover, the peptide controls were stable at <or=4 degrees C for at least 7 months, the longest time duration we tested. A national study of 109 participating clinical laboratories demonstrated a good correlation between a laboratory's ability to properly stain formalin-fixed peptide controls to their ability in properly staining a 3+ HER-2 formalin-fixed tissue section mounted on the same slide (r=0.87). Therefore, peptide IHC controls accurately reflect the analytical component of an IHC stain, including antigen retrieval. Besides its use in proficiency survey testing, we also demonstrate the feasibility of applying peptide IHC controls for verifying intralaboratory IHC staining consistency, using Levy-Jennings charting.

Technical standards and guidelines: Prenatal screening for open neural tube defects: This new section on “Prenatal Screening for Open Neural Tube Defects,” together with the new section on “Prenatal Screening for Down Syndrome,” replaces the previous Section H of the American College of Medical Genetics Standards and Guidelines for Clinical Genetics Laboratories

Technical standards and guidelines: Prenatal screening for open neural tube defects: This new section on “Prenatal Screening for Open Neural Tube Defects,” together with the new section on “Prenatal Screening for Down Syndrome,” replaces the previous Section H of the American College of Medical Genetics Standards and Guidelines for Clinical Genetics Laboratories *

Technical standards and guidelines: Prenatal screening for Down syndrome: This new section on “Prenatal Screening for Down Syndrome,” together with the new section on “Prenatal Screening for Open Neural Tube Defects,” replaces the previous Section H of the American College of Medical Genetics Standards and Guidelines for Clinical Genetics Laboratories

Technical standards and guidelines: Prenatal screening for Down syndrome: This new section on “Prenatal Screening for Down Syndrome,” together with the new section on “Prenatal Screening for Open Neural Tube Defects,” replaces the previous Section H of the American College of Medical Genetics Standards and Guidelines for Clinical Genetics Laboratories *

Quality control for nucleic acid tests: common ground and special issues.

Traditional clinical laboratory quality control practices are being applied to new technologies for the detection and quantitation of nucleic acids in clinical samples, often with limited knowledge of the probability for clinically significant error detection or for false run rejection of such practices. This article reviews traditional quality control practices, discusses the possibilities for a more rational approach to quality control for nucleic acid tests and suggests some steps that can lead to quality improvement for these tests.

Clinical laboratory quality control: a costly process now out of control

We studied laboratory internal quality control (QC) processes using the College of American Pathologists Q-Probes program. Over 500 institutions participated, providing practices based on approximately 710 000 cholesterol, 880 000 calcium, 400 000 digoxin, and 1 180 000 hemoglobin QC results. The costs of QC included participant median control sample rates comprising 9.1, 9.4, 37.0, and 6.8% for the four analytes respectively, repeat patient test rates of 0.36% for hemoglobin to 0.65% for digoxin, and median delays in reporting results when QC exceptions occurred of 15.8 min for calcium to 24.7 min for hemoglobin. Quality control practices were complex and highly variable among participants and frequently differed from internal laboratory protocols and from long-established quality guidelines. We conclude that QC is costly, and laboratorians frequently do not follow established QC practices, in part because they are complex. To improve compliance, we believe QC practices must be simplified.