This document discusses quality control in clinical laboratory testing. It emphasizes that quality control is essential to provide reliable diagnostic reports and cost-effective patient care. Quality control involves monitoring precision, accuracy, and sources of variation through internal quality control, external quality assessment, and statistical analysis of control values using tools like control charts and Westgard rules. The goal is to minimize laboratory errors and reliably distinguish pathological variations in patient samples.
Quality in clinical laboratory is a continuous journey of improving processes through team work, innovative solutions, regulatory compliance with final objective to meet the evolving needs of clinicians & patients.
This document discusses quality control, quality assurance, and quality assessment in medical laboratories. It defines key terms like quality control, quality assurance, and quality assessment. Quality control refers to analytical measurements used to assess data quality, while quality assurance is an overall management plan to ensure data integrity. Quality assessment determines the quality of results generated by evaluating internal and external quality programs. The document outlines quality assurance and quality control processes like standard operating procedures, equipment and reagent validation, personnel competency, and documentation. It also discusses error types, control chart interpretation, and Westgard rules for evaluating quality control results.
This document discusses quality assurance in blood banking. It outlines that quality is an ongoing process involving planning, doing, checking, and acting in a continuous cycle. Quality control ensures processes, procedures, and products meet requirements through consistency checks. Blood banking requires separate areas for donor selection, collection, processing, storage, and laboratory and auxiliary facilities. Quality requirements involve quality control testing, audits, personnel organization, premises/equipment/materials, documentation, processing, complaints/recalls, and investigating errors/accidents.
This document discusses quality assurance in haematology. It defines quality and introduces the concepts of quality control and quality assurance. Quality control aims to minimize errors through statistical sampling and verification of consistent performance. Quality assurance ensures reliable test results through adherence to standards within and outside the laboratory. This includes internal quality control, external quality assessment, and standardization using reference materials and methods. Several examples are provided of potential pre-analytical errors in sample collection, transport, and handling that can affect test results. Adherence to proper procedures is emphasized to avoid issues like hemolysis, clotting, and dilution.
Quality control in the medical laboratoryAdnan Jaran
This document discusses quality control in medical laboratories. It emphasizes that quality is achieved through determining customer requirements, ensuring necessary resources are available, planning management procedures, training staff, undertaking tasks correctly, taking corrective action when errors occur, conducting regular reviews and audits, and total management commitment. The quality assurance cycle involves various steps from patient preparation to reporting. Achieving high quality requires addressing all aspects of the laboratory, including organization, personnel, equipment, purchasing, process control, information management, documents, occurrence management, assessment, process improvement, customer service, and facilities/safety. The goal is to detect and prevent errors through a quality management system.
This document discusses quality control in clinical laboratory testing. It emphasizes that quality control is essential to provide reliable diagnostic reports and cost-effective patient care. Quality control involves monitoring precision, accuracy, and sources of variation through internal quality control, external quality assessment, and statistical analysis of control values using tools like control charts and Westgard rules. The goal is to minimize laboratory errors and reliably distinguish pathological variations in patient samples.
Quality in clinical laboratory is a continuous journey of improving processes through team work, innovative solutions, regulatory compliance with final objective to meet the evolving needs of clinicians & patients.
This document discusses quality control, quality assurance, and quality assessment in medical laboratories. It defines key terms like quality control, quality assurance, and quality assessment. Quality control refers to analytical measurements used to assess data quality, while quality assurance is an overall management plan to ensure data integrity. Quality assessment determines the quality of results generated by evaluating internal and external quality programs. The document outlines quality assurance and quality control processes like standard operating procedures, equipment and reagent validation, personnel competency, and documentation. It also discusses error types, control chart interpretation, and Westgard rules for evaluating quality control results.
This document discusses quality assurance in blood banking. It outlines that quality is an ongoing process involving planning, doing, checking, and acting in a continuous cycle. Quality control ensures processes, procedures, and products meet requirements through consistency checks. Blood banking requires separate areas for donor selection, collection, processing, storage, and laboratory and auxiliary facilities. Quality requirements involve quality control testing, audits, personnel organization, premises/equipment/materials, documentation, processing, complaints/recalls, and investigating errors/accidents.
This document discusses quality assurance in haematology. It defines quality and introduces the concepts of quality control and quality assurance. Quality control aims to minimize errors through statistical sampling and verification of consistent performance. Quality assurance ensures reliable test results through adherence to standards within and outside the laboratory. This includes internal quality control, external quality assessment, and standardization using reference materials and methods. Several examples are provided of potential pre-analytical errors in sample collection, transport, and handling that can affect test results. Adherence to proper procedures is emphasized to avoid issues like hemolysis, clotting, and dilution.
Quality control in the medical laboratoryAdnan Jaran
This document discusses quality control in medical laboratories. It emphasizes that quality is achieved through determining customer requirements, ensuring necessary resources are available, planning management procedures, training staff, undertaking tasks correctly, taking corrective action when errors occur, conducting regular reviews and audits, and total management commitment. The quality assurance cycle involves various steps from patient preparation to reporting. Achieving high quality requires addressing all aspects of the laboratory, including organization, personnel, equipment, purchasing, process control, information management, documents, occurrence management, assessment, process improvement, customer service, and facilities/safety. The goal is to detect and prevent errors through a quality management system.
Harmonization of Laboratory Indicators, 09 03-2017Ola Elgaddar
The document discusses harmonization of quality indicators (QIs) in medical laboratories. It notes that while QIs are important for quality improvement, there is currently no consensus on common QIs or how they should be defined and measured. The Working Group on Laboratory Errors and Patient Safety has developed a Model Quality Indicator (MQI) to address this issue, which defines 53 measurements across 27 QIs. Laboratories can now report results to the MQI website voluntarily. Statistical analysis of early participation in the MQI shows the most widely used QIs relate to pre-analytical errors, analytical test performance, and post-analytical issues. However, broader adoption remains a challenge.
Quality control, quality assurance, and quality assessment are important concepts for ensuring accuracy and reliability in medical laboratory testing. Quality control refers to internal processes like running controls to verify test accuracy during each run. Quality assurance encompasses the overall program to deliver correct results. Quality assessment challenges these programs through external proficiency testing. Proper documentation, trained personnel, validated methods and equipment, and monitoring control rules are key to achieving the goals of quality control, quality assurance and providing quality medical laboratory testing.
This document discusses Westgard rules, which are used to evaluate the quality control of laboratory test results plotted on a Levey-Jennings chart. The Westgard rules define thresholds for rejecting runs based on the number of consecutive measurements that fall outside the mean or on one side of the mean, indicating potential errors. Examples provided include the 13S rule for rejecting a single measurement exceeding 3 standard deviations from the mean and rules for rejecting runs with consecutive measurements exceeding control limits or falling on one side of the mean. Trend shifts are also discussed as potential causes of quality control failures.
Quality control (QC) is a procedure or set of procedures intended to ensure that a manufactured product or performed service adheres to a defined set of quality criteria or meets the requirements of the client or customer. QC is similar to, but not identical with, quality assurance (QA).
QC IN clinical biochemistry labs and hospitals
QUALITY control in hematology by Dr yogeeta.pptxYogeetaTanty1
This document discusses quality control in hematology. It defines quality as freedom from defects achieved through adherence to standards. Quality assurance ensures reliability of lab tests through standardization. Quality control detects, reduces, and corrects deficiencies in the internal analytical process. Important aspects of quality control in hematology include instrument calibration, monitoring accuracy and precision, and verifying reliable test results. Internal quality control uses controls for immediate decision making while external quality control compares results to other labs. Statistical methods like mean, standard deviation, and Levey Jennings charts are used for quality control assessment.
Internal Quality Control Lecture MD General 2014 Course, Clin Path Ain Shams ...Adel Elazab Elged
The document discusses internal quality control in clinical laboratories. It defines key terms like quality control, quality assurance, and quality management. It explains the importance of internal quality control in ensuring accurate and reliable test results. Quality control involves running control samples alongside patient samples and using statistical tools like control charts and Westgard rules to monitor the analytical process and ensure it is in control. Factors that could indicate the process is out of control are also summarized.
Automated cell counters provide several advantages over manual cell counting including objectivity, elimination of errors, higher precision, and ability to measure more parameters. They work using principles of impedance, optical light scattering, or both. Quality control and daily maintenance are important to ensure accurate results. While automated counts are precise, manual review of films is still needed when results are abnormal. Newer automated hematology analyzers can measure over 30 parameters using technologies like flow cytometry.
Calibration and Quality controls of automated hematology analyzerPranav S
This document discusses calibration and quality control of automated hematology analyzers. It begins with a brief history of hematology and automation in the field. Ensuring accurate results through quality assurance is important, involving preventative, assessment, and corrective activities like standardization, internal quality control, and external quality proficiency testing. Proper documentation, training, environment control, and management of preanalytical variables are among the general requirements for quality control and calibration. Calibration must be performed on new or repaired analyzers, and internal and external quality controls help monitor and ensure accuracy of results.
This document provides an overview of laboratory quality management and outlines the essential components of a quality management system for laboratories. It discusses that quality management is a continuous journey, not a destination. It then describes the key quality system essentials which include organization, facilities and safety, personnel, equipment, and processes for management, work, and measurement. The relationship between technical and managerial activities is important for ensuring high quality and effective laboratory operations.
Internal quality control in clinical laboratories hematology(2)NAZAR ABU-DULLA
This document discusses internal quality control in hematology laboratories. It begins with an introduction of the author, Nazar Ahmed Mohamed Abd-Alla, which notes his qualifications and experience in hematology and laboratory administration.
The document then outlines topics that will be covered, including quality definitions, types of errors, specimen handling, method selection, calibration, documentation, and quality programs. It discusses sources of errors like pre-analytical, analytical, and post-analytical errors. It also covers quality assurance, method validation, and specifications for proper specimen collection, transport, and acceptance or rejection. The goal is to provide reliable and accurate test results through effective quality control.
This document discusses laboratory errors, their causes, types, and impacts. It describes that errors can occur in the pre-analytical, analytical, and post-analytical phases of testing and provide examples of errors in each phase. Errors are categorized as either determinate (systemic) errors, which are reproducible and can be identified and corrected, or indeterminate (random) errors, which are caused by uncontrollable variables and cannot be eliminated. The key goals are improving precision by reducing indeterminate errors and improving accuracy by reducing determinate errors.
In the continuous quality journey, Controlling laboratory Errors is an integral part & focusing on analytical, post-analytical process is the first step. Developing a reporting culture followed by thorough analysis and implementation of appropriate corrective, preventive actions is required.
Quality control and quality assurance programs are necessary to ensure reliable and accurate laboratory test results. Quality control involves daily monitoring processes like equipment calibration and testing control samples to verify test accuracy and precision. Quality assessment through external proficiency testing further challenges the quality programs. Proper quality control is implemented through all stages of testing - pre-analytical, analytical and post-analytical. Statistical tools like Levey-Jennings charts and Westgard rules are used to monitor quality control data and identify out of control results. The goal is to minimize errors and validate test results for optimal patient care.
this is just a review of Quality Control Scheme integrated by Dr Westgard and his son, as here in ordinary clinic lab that QA Scheme is followed, and the LH 500 and our ACT5 Diff Coulter Counter, we are able to get the Yearly Sigma Scale performance for each analytes, our TAE for each analytes, I compute based on Rico's accepted biological variation as I deemed it is much pertinent, thus the EQAS in the peer group, cumulative bias average for 6 months and the IQAS's LJ Chart has the CV%. The two instruments are well maintained , with carryover check for each modes, Accuracy / Precision Check By the Engineer, the Calibration, is always Passed the required threshold for each parameter.
This powerpoint presentation is graciously dedicated to the father and son, the WESTGARDS...we owe you this quality assurance for each instruments we have, either in Biochem or Hematology, we salute you and more power, God Bless. From Sis Rina, our simple JPC lab here in the Gulf--thanks so much!
This document discusses Total Quality Management in medical laboratories. It covers key aspects of quality management including defining quality, the core elements of a quality management system, and the seven common tools used in quality control. It also discusses requirements for laboratory accreditation such as establishing quality indicators, documentation, and quality assurance activities like proficiency testing and calibration. The overall goal of quality management in medical laboratories is to provide accurate and reliable test results to customers through an effective quality management system.
This document discusses hematological parameters analyzed in laboratory hematology. It describes the main anticoagulants used in blood collection and how they work. It also summarizes the methods used to analyze red blood cell parameters like red cell count, hemoglobin concentration, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration both manually and using automated hematology analyzers. Key factors that affect the accuracy of these measurements are also highlighted.
Urine analysis is an integral part of a clinical laboratory. automation techniques in urine biochemistry, their priniciplas and microscopy along with their advantages and disadvantages are outlined.
The Paris System for Reporting Urinary CytologyRawa Muhsin
The Paris System for Reporting Urinary Cytology provides standardized diagnostic categories for urine cytology specimens. It divides results into negative for high-grade urothelial carcinoma, positive for high-grade urothelial carcinoma, atypical urothelial cells, and suspicious for high-grade urothelial carcinoma based on the number and features of abnormal cells seen. The system aims to determine whether high-grade urothelial carcinoma is present or not, as this has important implications for patient management and prognosis. Risk of malignancy increases from negative to atypical to suspicious to positive categories.
This document discusses quality control in hematology. It defines quality as meeting specifications and quality control as measures taken during testing to ensure tests are working properly. Quality assurance ensures the correct test is performed and the right result is delivered. Quality control involves analytical measurements to assess data quality while quality assurance is an overall management plan. The key activities of quality assurance are preventive, assessment and corrective measures. The document outlines the importance of accuracy, precision, internal quality control, external quality control and corrective actions when errors are found.
Harmonization of Laboratory Indicators, 09 03-2017Ola Elgaddar
The document discusses harmonization of quality indicators (QIs) in medical laboratories. It notes that while QIs are important for quality improvement, there is currently no consensus on common QIs or how they should be defined and measured. The Working Group on Laboratory Errors and Patient Safety has developed a Model Quality Indicator (MQI) to address this issue, which defines 53 measurements across 27 QIs. Laboratories can now report results to the MQI website voluntarily. Statistical analysis of early participation in the MQI shows the most widely used QIs relate to pre-analytical errors, analytical test performance, and post-analytical issues. However, broader adoption remains a challenge.
Quality control, quality assurance, and quality assessment are important concepts for ensuring accuracy and reliability in medical laboratory testing. Quality control refers to internal processes like running controls to verify test accuracy during each run. Quality assurance encompasses the overall program to deliver correct results. Quality assessment challenges these programs through external proficiency testing. Proper documentation, trained personnel, validated methods and equipment, and monitoring control rules are key to achieving the goals of quality control, quality assurance and providing quality medical laboratory testing.
This document discusses Westgard rules, which are used to evaluate the quality control of laboratory test results plotted on a Levey-Jennings chart. The Westgard rules define thresholds for rejecting runs based on the number of consecutive measurements that fall outside the mean or on one side of the mean, indicating potential errors. Examples provided include the 13S rule for rejecting a single measurement exceeding 3 standard deviations from the mean and rules for rejecting runs with consecutive measurements exceeding control limits or falling on one side of the mean. Trend shifts are also discussed as potential causes of quality control failures.
Quality control (QC) is a procedure or set of procedures intended to ensure that a manufactured product or performed service adheres to a defined set of quality criteria or meets the requirements of the client or customer. QC is similar to, but not identical with, quality assurance (QA).
QC IN clinical biochemistry labs and hospitals
QUALITY control in hematology by Dr yogeeta.pptxYogeetaTanty1
This document discusses quality control in hematology. It defines quality as freedom from defects achieved through adherence to standards. Quality assurance ensures reliability of lab tests through standardization. Quality control detects, reduces, and corrects deficiencies in the internal analytical process. Important aspects of quality control in hematology include instrument calibration, monitoring accuracy and precision, and verifying reliable test results. Internal quality control uses controls for immediate decision making while external quality control compares results to other labs. Statistical methods like mean, standard deviation, and Levey Jennings charts are used for quality control assessment.
Internal Quality Control Lecture MD General 2014 Course, Clin Path Ain Shams ...Adel Elazab Elged
The document discusses internal quality control in clinical laboratories. It defines key terms like quality control, quality assurance, and quality management. It explains the importance of internal quality control in ensuring accurate and reliable test results. Quality control involves running control samples alongside patient samples and using statistical tools like control charts and Westgard rules to monitor the analytical process and ensure it is in control. Factors that could indicate the process is out of control are also summarized.
Automated cell counters provide several advantages over manual cell counting including objectivity, elimination of errors, higher precision, and ability to measure more parameters. They work using principles of impedance, optical light scattering, or both. Quality control and daily maintenance are important to ensure accurate results. While automated counts are precise, manual review of films is still needed when results are abnormal. Newer automated hematology analyzers can measure over 30 parameters using technologies like flow cytometry.
Calibration and Quality controls of automated hematology analyzerPranav S
This document discusses calibration and quality control of automated hematology analyzers. It begins with a brief history of hematology and automation in the field. Ensuring accurate results through quality assurance is important, involving preventative, assessment, and corrective activities like standardization, internal quality control, and external quality proficiency testing. Proper documentation, training, environment control, and management of preanalytical variables are among the general requirements for quality control and calibration. Calibration must be performed on new or repaired analyzers, and internal and external quality controls help monitor and ensure accuracy of results.
This document provides an overview of laboratory quality management and outlines the essential components of a quality management system for laboratories. It discusses that quality management is a continuous journey, not a destination. It then describes the key quality system essentials which include organization, facilities and safety, personnel, equipment, and processes for management, work, and measurement. The relationship between technical and managerial activities is important for ensuring high quality and effective laboratory operations.
Internal quality control in clinical laboratories hematology(2)NAZAR ABU-DULLA
This document discusses internal quality control in hematology laboratories. It begins with an introduction of the author, Nazar Ahmed Mohamed Abd-Alla, which notes his qualifications and experience in hematology and laboratory administration.
The document then outlines topics that will be covered, including quality definitions, types of errors, specimen handling, method selection, calibration, documentation, and quality programs. It discusses sources of errors like pre-analytical, analytical, and post-analytical errors. It also covers quality assurance, method validation, and specifications for proper specimen collection, transport, and acceptance or rejection. The goal is to provide reliable and accurate test results through effective quality control.
This document discusses laboratory errors, their causes, types, and impacts. It describes that errors can occur in the pre-analytical, analytical, and post-analytical phases of testing and provide examples of errors in each phase. Errors are categorized as either determinate (systemic) errors, which are reproducible and can be identified and corrected, or indeterminate (random) errors, which are caused by uncontrollable variables and cannot be eliminated. The key goals are improving precision by reducing indeterminate errors and improving accuracy by reducing determinate errors.
In the continuous quality journey, Controlling laboratory Errors is an integral part & focusing on analytical, post-analytical process is the first step. Developing a reporting culture followed by thorough analysis and implementation of appropriate corrective, preventive actions is required.
Quality control and quality assurance programs are necessary to ensure reliable and accurate laboratory test results. Quality control involves daily monitoring processes like equipment calibration and testing control samples to verify test accuracy and precision. Quality assessment through external proficiency testing further challenges the quality programs. Proper quality control is implemented through all stages of testing - pre-analytical, analytical and post-analytical. Statistical tools like Levey-Jennings charts and Westgard rules are used to monitor quality control data and identify out of control results. The goal is to minimize errors and validate test results for optimal patient care.
this is just a review of Quality Control Scheme integrated by Dr Westgard and his son, as here in ordinary clinic lab that QA Scheme is followed, and the LH 500 and our ACT5 Diff Coulter Counter, we are able to get the Yearly Sigma Scale performance for each analytes, our TAE for each analytes, I compute based on Rico's accepted biological variation as I deemed it is much pertinent, thus the EQAS in the peer group, cumulative bias average for 6 months and the IQAS's LJ Chart has the CV%. The two instruments are well maintained , with carryover check for each modes, Accuracy / Precision Check By the Engineer, the Calibration, is always Passed the required threshold for each parameter.
This powerpoint presentation is graciously dedicated to the father and son, the WESTGARDS...we owe you this quality assurance for each instruments we have, either in Biochem or Hematology, we salute you and more power, God Bless. From Sis Rina, our simple JPC lab here in the Gulf--thanks so much!
This document discusses Total Quality Management in medical laboratories. It covers key aspects of quality management including defining quality, the core elements of a quality management system, and the seven common tools used in quality control. It also discusses requirements for laboratory accreditation such as establishing quality indicators, documentation, and quality assurance activities like proficiency testing and calibration. The overall goal of quality management in medical laboratories is to provide accurate and reliable test results to customers through an effective quality management system.
This document discusses hematological parameters analyzed in laboratory hematology. It describes the main anticoagulants used in blood collection and how they work. It also summarizes the methods used to analyze red blood cell parameters like red cell count, hemoglobin concentration, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration both manually and using automated hematology analyzers. Key factors that affect the accuracy of these measurements are also highlighted.
Urine analysis is an integral part of a clinical laboratory. automation techniques in urine biochemistry, their priniciplas and microscopy along with their advantages and disadvantages are outlined.
The Paris System for Reporting Urinary CytologyRawa Muhsin
The Paris System for Reporting Urinary Cytology provides standardized diagnostic categories for urine cytology specimens. It divides results into negative for high-grade urothelial carcinoma, positive for high-grade urothelial carcinoma, atypical urothelial cells, and suspicious for high-grade urothelial carcinoma based on the number and features of abnormal cells seen. The system aims to determine whether high-grade urothelial carcinoma is present or not, as this has important implications for patient management and prognosis. Risk of malignancy increases from negative to atypical to suspicious to positive categories.
This document discusses quality control in hematology. It defines quality as meeting specifications and quality control as measures taken during testing to ensure tests are working properly. Quality assurance ensures the correct test is performed and the right result is delivered. Quality control involves analytical measurements to assess data quality while quality assurance is an overall management plan. The key activities of quality assurance are preventive, assessment and corrective measures. The document outlines the importance of accuracy, precision, internal quality control, external quality control and corrective actions when errors are found.
This document discusses quality assurance and quality control in clinical laboratories. It defines quality assurance as ensuring a specified quality is achieved and maintained through all steps of laboratory testing. Quality control specifically monitors analytical accuracy and precision. Laboratories should implement both internal quality control methods like Levey-Jennings charts to monitor daily performance, as well as participate in external quality assurance programs for benchmarking and improvement. The goal is reliable test results that can be correctly interpreted for patient care.
QUALITY
Conformance to the requirements of users or customers satisfaction of their needs and expectations.
Total Quality Management
A management approach that focuses on processes and their improvement.
Quality assurance and quality control programs are necessary to ensure the reliability and accuracy of analytical environmental data. An inter-laboratory study by the EPA showed wide variation in nutrient concentration measurements between laboratories. Measurement of total dissolved solids and electrical conductivity also showed significant variation between laboratories. Shewhart control charts can be used to monitor the statistical control of analytical procedures and identify sources of random and systematic error by tracking the spread and displacement of results from control samples over time. Control limits on the charts indicate thresholds for corrective action to maintain method accuracy.
Quality assurance and quality control programs are necessary to ensure the validity and reliability of analytical environmental data. Several studies have shown large variations in results for identical samples analyzed by different laboratories. AQC programs establish procedures for sample collection, analysis, calibration, quality control checks, and data reporting. Key aspects include standard methods, analyst training, instrument maintenance, calibration verification, internal quality control samples, and inter-laboratory sample exchanges to check for accuracy. Control charts can be used to monitor results and identify any loss of statistical control that could indicate errors have been introduced. Both precision and accuracy are important to consider when evaluating results.
Quality assurance and quality control programs are necessary to ensure the reliability and accuracy of analytical environmental data. An inter-laboratory study by the EPA showed wide variation in nutrient concentration measurements between laboratories. Measurement of total dissolved solids and electrical conductivity also showed significant variation between laboratories. Shewhart control charts can be used to monitor the statistical control of analytical procedures and identify issues by tracking results from quality control samples against mean values and standard deviations. Key aspects of a quality assurance program include sample handling procedures, standardized analytical methods, analyst training, instrument maintenance, calibration procedures, analytical quality control tests, data management, and control chart monitoring.
This content is suitable for medical technologists/technicians/lab assistants/scientists writing the SMLTSA board exam. The content is also suitable for biomedical technology students and people also interested in learning about test methodologies used in medical technology. This chapter describes test quality assurance (QA) and quality control (QC). Please note that these notes are a collection I used to study for my board exam and train others who got distinctions using these.
Disclaimer: Credit goes to those who wrote the notes and the examiners of each exam question. Please use only as a reference guide and use your prescribed textbook for the latest and most accurate notes and ranges. The material here is not referenced as it is a collection of pieces of study notes from multiple people, and thus will not be held viable for any misinterpretations. Please use at your own discretion.
Control of analytical quality using stable control materials postgradMedhatEldeeb2
This document discusses quality control basics for analytical testing methods. It defines internal and external quality control and describes how control materials of known concentration are used to monitor test performance. The key aspects covered include:
- Types of errors such as random errors and systematic errors
- Criteria for selecting stable control materials with acceptable concentration ranges
- Calculations for mean, standard deviation, and quality control limits
- The Levey-Jennings chart for graphing quality control results over time
- Westgard rules for identifying errors based on the number of controls tested
- Identifying trends or shifts that indicate problems requiring troubleshooting
Quality Control for Quantitative Tests by Prof Aamir Ijaz (Pakistan)Aamir Ijaz Brig
This document provides an overview of quality control and quality assurance processes in a chemical pathology laboratory. It discusses key terms like quality control, quality assurance, internal quality control, external quality assurance. It also describes different types of errors like random error and systematic error. The document explains statistical concepts like measures of central tendency, standard deviation, coefficient of variation. It discusses the Westgard rules for evaluating quality control results and triggering investigations into potential errors. The goal of the lecture is to describe the processes involved in quality management for chemical pathology laboratories.
Internal quality control in blood bank testingSanjeew Yadav
Internal quality control is essential for blood bank testing to continuously monitor laboratory work and results. It involves running both quantitative and qualitative controls to check for issues like drift, dispersion, or shifts that could indicate problems. Quantitative tests have controls run to establish mean, standard deviation, and target ranges using statistical analysis. Qualitative rapid card tests have positive and negative controls run daily. Equipment and reagents also have defined internal quality checks run daily or weekly. Control values are monitored using Levy-Jennings charts and Westgard rules to ensure precision and accuracy and identify any issues requiring troubleshooting or corrective action.
Introduction to Analytical Analysis InstrumentationM.T.H Group
This document provides an introduction to analytical analysis instrumentation. It discusses the learning outcomes which include reviewing analytical strategies, instrumental analysis methods, basic instrumental measurement, preparation of standards, blanks and controls, and laboratory data acquisition. It then discusses key concepts in analytical chemistry including qualitative and quantitative analysis. It also discusses analytical errors, elementary statistics, parameters characterizing instrumental techniques such as detection limit, selectivity, sensitivity, and the analytical strategy process. Finally, it discusses common instrumental analysis methods, preparation of standards, and the use of blanks and controls.
The document discusses key concepts for interpreting clinical biochemical data, including:
1. Calculating measures of central tendency like the mean and measures of variability like the standard deviation and range to establish normal reference values.
2. Factors that determine the validity and reliability of analytical tests, and the importance of quality assurance and quality control.
3. Methods for describing data distribution including the coefficient of variation and using critical differences to determine the clinical significance of changes in serial measurements.
4. Concepts related to screening tests like sensitivity, specificity, and the ability to correctly identify individuals with and without the disease.
clm for HO Student (1).pptx wggrhhgfyudduMoviePics
This document provides an overview of a clinical laboratory methods course for health sciences students. The course objectives are to teach students how to appropriately use medical laboratory equipment, perform routine laboratory tests, and interpret laboratory test results. The document outlines the topics that will be covered in the course, including microscopy, hematological tests, liver and kidney function tests, serological tests, blood grouping, staining procedures, urinalysis, and parasitological tests. It also introduces some key laboratory equipment and provides background on hematology, focusing on the composition of blood and the main blood cell types.
The document discusses internal quality control procedures in a medical laboratory. It defines internal quality control and explains the three main stages - pre-analytical, analytical, and post-analytical - that need to be controlled. It describes the process for internal quality control, including using control materials, establishing statistical limits, and interpreting quality control data using rules like Westgard's multi-rules. The document emphasizes the importance of root cause analysis when quality control is out of control and comparing internal quality control with external quality assessment.
This document discusses quality management systems in medical laboratories. It defines key terms like quality control, accuracy, precision, and quality assurance. It describes the goals of internal and external quality control. The document also explains sources of error like pre-analytical, analytical, and post-analytical phases. It provides details on Levey-Jennings charts, including how they are used to evaluate quality control results over time using statistical process control rules like Westgard rules.
The document discusses quality control in clinical laboratories. It begins by describing how automated analyzers have modernized clinical laboratories by generating large numbers of test results quickly through integrated technologies. Quality control is then discussed, noting that statistical quality control (SQC) involves monitoring a minimum number of samples to check quality rather than individually checking every sample. SQC can be applied to clinical laboratories by using control samples rather than patient samples. The document outlines key terms used in quality control such as precision, accuracy, random errors, and systematic errors. It describes the use of internal quality control, using daily quality checks with laboratory equipment and materials, and external quality control using periodic proficiency testing with external organizations.
In tech quality-control_in_clinical_laboratoriesMillat Sultan
The document discusses quality control in clinical laboratories. It begins by describing how automated analyzers have modernized clinical laboratories by generating large numbers of test results quickly through integrated technologies. Quality control is then discussed, noting that statistical quality control (SQC) involves monitoring a minimum number of samples to check quality rather than individually checking every sample. SQC can be applied to clinical laboratories by using control samples rather than patient samples. The document outlines key terms used in quality control such as precision, accuracy, random errors, and systematic errors. It describes the use of internal quality control, using daily quality checks with laboratory equipment and materials, and external quality control using periodic proficiency testing with external organizations.
Quality control and quality assurance are important for ensuring accurate lab results. Quality control involves regularly testing controls of known values to monitor a test's performance. Key quality control statistics include the mean and standard deviation, which are used to calculate control limits on a Levey-Jennings chart. Westgard rules provide standards for determining when a test is out of control based on control values. Quality assurance encompasses the overall programs and procedures that a lab follows to ensure accurate and reliable results. It has strategic, tactical, and operational levels.
Quality assurance in the department of clinical biochemistryDipesh Tamrakar
This document discusses quality assurance and control in clinical laboratories. It explains that quality control aims to ensure test results are correct by monitoring performance through tools like internal quality control and external quality assessment. The document outlines the pre-analytical, analytical and post-analytical phases of testing and discusses specific quality control procedures used at each stage like storage of controls, monitoring control data, and troubleshooting out of control errors. Westgard rules for determining if quality control is in or out of control are also explained.
Similar to Basics of Quality Assurance-Medical Laboratory Services (20)
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Cell Therapy Expansion and Challenges in Autoimmune DiseaseHealth Advances
There is increasing confidence that cell therapies will soon play a role in the treatment of autoimmune disorders, but the extent of this impact remains to be seen. Early readouts on autologous CAR-Ts in lupus are encouraging, but manufacturing and cost limitations are likely to restrict access to highly refractory patients. Allogeneic CAR-Ts have the potential to broaden access to earlier lines of treatment due to their inherent cost benefits, however they will need to demonstrate comparable or improved efficacy to established modalities.
In addition to infrastructure and capacity constraints, CAR-Ts face a very different risk-benefit dynamic in autoimmune compared to oncology, highlighting the need for tolerable therapies with low adverse event risk. CAR-NK and Treg-based therapies are also being developed in certain autoimmune disorders and may demonstrate favorable safety profiles. Several novel non-cell therapies such as bispecific antibodies, nanobodies, and RNAi drugs, may also offer future alternative competitive solutions with variable value propositions.
Widespread adoption of cell therapies will not only require strong efficacy and safety data, but also adapted pricing and access strategies. At oncology-based price points, CAR-Ts are unlikely to achieve broad market access in autoimmune disorders, with eligible patient populations that are potentially orders of magnitude greater than the number of currently addressable cancer patients. Developers have made strides towards reducing cell therapy COGS while improving manufacturing efficiency, but payors will inevitably restrict access until more sustainable pricing is achieved.
Despite these headwinds, industry leaders and investors remain confident that cell therapies are poised to address significant unmet need in patients suffering from autoimmune disorders. However, the extent of this impact on the treatment landscape remains to be seen, as the industry rapidly approaches an inflection point.
Muktapishti is a traditional Ayurvedic preparation made from Shoditha Mukta (Purified Pearl), is believed to help regulate thyroid function and reduce symptoms of hyperthyroidism due to its cooling and balancing properties. Clinical evidence on its efficacy remains limited, necessitating further research to validate its therapeutic benefits.
Integrating Ayurveda into Parkinson’s Management: A Holistic ApproachAyurveda ForAll
Explore the benefits of combining Ayurveda with conventional Parkinson's treatments. Learn how a holistic approach can manage symptoms, enhance well-being, and balance body energies. Discover the steps to safely integrate Ayurvedic practices into your Parkinson’s care plan, including expert guidance on diet, herbal remedies, and lifestyle modifications.
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...Oleg Kshivets
Overall life span (LS) was 1671.7±1721.6 days and cumulative 5YS reached 62.4%, 10 years – 50.4%, 20 years – 44.6%. 94 LCP lived more than 5 years without cancer (LS=2958.6±1723.6 days), 22 – more than 10 years (LS=5571±1841.8 days). 67 LCP died because of LC (LS=471.9±344 days). AT significantly improved 5YS (68% vs. 53.7%) (P=0.028 by log-rank test). Cox modeling displayed that 5YS of LCP significantly depended on: N0-N12, T3-4, blood cell circuit, cell ratio factors (ratio between cancer cells-CC and blood cells subpopulations), LC cell dynamics, recalcification time, heparin tolerance, prothrombin index, protein, AT, procedure type (P=0.000-0.031). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and N0-12 (rank=1), thrombocytes/CC (rank=2), segmented neutrophils/CC (3), eosinophils/CC (4), erythrocytes/CC (5), healthy cells/CC (6), lymphocytes/CC (7), stick neutrophils/CC (8), leucocytes/CC (9), monocytes/CC (10). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; area under ROC curve=1.0).
Our backs are like superheroes, holding us up and helping us move around. But sometimes, even superheroes can get hurt. That’s where slip discs come in.
Rasamanikya is a excellent preparation in the field of Rasashastra, it is used in various Kushtha Roga, Shwasa, Vicharchika, Bhagandara, Vatarakta, and Phiranga Roga. In this article Preparation& Comparative analytical profile for both Formulationon i.e Rasamanikya prepared by Kushmanda swarasa & Churnodhaka Shodita Haratala. The study aims to provide insights into the comparative efficacy and analytical aspects of these formulations for enhanced therapeutic outcomes.
8 Surprising Reasons To Meditate 40 Minutes A Day That Can Change Your Life.pptxHolistified Wellness
We’re talking about Vedic Meditation, a form of meditation that has been around for at least 5,000 years. Back then, the people who lived in the Indus Valley, now known as India and Pakistan, practised meditation as a fundamental part of daily life. This knowledge that has given us yoga and Ayurveda, was known as Veda, hence the name Vedic. And though there are some written records, the practice has been passed down verbally from generation to generation.
Histololgy of Female Reproductive System.pptxAyeshaZaid1
Dive into an in-depth exploration of the histological structure of female reproductive system with this comprehensive lecture. Presented by Dr. Ayesha Irfan, Assistant Professor of Anatomy, this presentation covers the Gross anatomy and functional histology of the female reproductive organs. Ideal for students, educators, and anyone interested in medical science, this lecture provides clear explanations, detailed diagrams, and valuable insights into female reproductive system. Enhance your knowledge and understanding of this essential aspect of human biology.
2. 1. Diagnosis purposes (to confirm or rule out a
disease.
Purposes of laboratory investigations
- LFT for patients with jaundice to confirm
hepatitis
- Brucella or widal test to rule out brucellosis
or typhoid fever.
2. Prognosis purposes
- Tumor markers for early detection of
malignancy.
- Microalbuminuria for early detection of
diabetic nephropathy
4. The types of laboratory investigations
1. Qualitative investigations.
2. Semi quantitative investigations.
3. Quantitative investigations.
5. 1. Patient samples:
Blood, serum, plasma, urine, stool, CSF,
swabs for cultures, biopsy, body fluids.
There are certain specifications for the
collection, handling and storage of each
specimen, e.g.:
- 24 hours urine sample.
- Fresh early morning sample.
- Random urine sample.
Samples of laboratory investigations
6. 2. Standard sample:
Is the substance of sufficient purity and
stability and of fixed concentration used for
comparison purpose
7. 3. Control sample:
Is the substance which is chemically and
physically similar to the unknown sample and
of known concentration.
it is essential that lyophilized control samples
be reconstituted and handled with good
quantitative technique and must be allowed to
dissolve completely.
Reconstituted control samples must be
protected from deterioration due to bacterial
action (glucose), expose to light (bilirubin)
and evaporation (all analytes)
8. Variations in repeated investigations are due
to errors that may take place at any stage
involved in requesting, performing and
evaluating these investigations.
Variations in repeated investigations
9. 1. Pre-instrumental sources:
Sources of variations
- Preparation of the patient.
- Obtaining the specimen.
- Processing the specimen
- Specimen interference.
- Storing the specimen prior to the
measuring step.
10. 2. Instrumental sources:
- Dispensing a sample aliquot into a reaction
vessel.
- Combining the sample with one or more
reagents.
- Recording some physical-chemical
consequence of the reaction.
- Calculating the value of the quantity measured.
11. 3. Post-instrumental sources:
- Accepting the result of the test by the
technician as being of good quality.
- Sending the report of the test to the requesting
physician.
12. It is a statistical study of errors that could be
due to patient preparation, laboratory
personnel, laboratory technique, or used
reagent in order to recognize and minimize
them. It is the study of imprecision and
inaccuracy.
Quality Control
13. Factors affecting quality control
1. Control on laboratory supplies.
2. Control on quality of patient specimen.
3. Selection and continuing education of
laboratory personnel.
4. Selection and maintenance of equipment.
5. Communications.
6. Evaluation of new laboratory procedure.
7. Implementation of quality control programme.
14. 1. Mean value (X):
It is the total score of all measurements
divided by the number of measurements.
2. Standard Deviation (SD):
It is the degree of dispersion of results of the
repeated laboratory investigations around the
mean value, i.e. the degree of reproducibility.
3. Coefficient of variation (CV):
It is the standard deviation expressed in
percentage.
Statistical features involved in quality
control implementation
15. 4. Allowable limit of error (ALE):
It is the accepted error expressed in
percentage.
5. Deviation index (DI):
It is the difference between the individual
laboratory’s result and the mean calculated
from the results of all laboratory.
16. 1. Imprecision:
The degree of dispersion of repeated
laboratory results around their mean value,
expressed as: SD, CV or DI.
2. Inaccuracy:
The degree of dispersion of repeated
laboratory results around the true value.
Interpretation of quality control results
17. 3. Random errors:
Are those errors in the results of the repeated
analysis of the same sample due to
variations in apparatus, temperature,
weighing, … etc., which are either positive or
negative errors, and are usually equally
distributed.
These random errors can be reduced by more
précised method and more accurate
equipment, but can never be completely
avoided.
18. 4. System errors:
Are those errors in the results of the repeated
analysis of the same sample due to variations
in analytical method, technical performance,
reagents, equipment or technicians which
may cause too high or too low, continuous
increasing or continuous decreasing results,
and are generally avoidable and detectable.
5. Trend in the quality control chart:
Is the gradual decrease or increase in the
results of the repeated analysis of the control
sample.
19. 6. Shift in the quality control chart:
Is the sudden consistent change in the
results of the repeated analysis of the control
sample in either side of the mean.
7. Dispersion in the quality control chart:
Is a wide range of scatter of the results of the
repeated analysis of the control sample
around their value due to random errors.
20. 8. Specificity:
Is the ability of method to determine only the
substance which is supposed to measure.
The greater the specificity of a test, the fewer
the number of false-positive results.
Total number of negative results
Specificity = --------------------------------------------------
Total number of uninfected patients
95
= ------------------------------------------------- = 95%
100
21. 9. Sensitivity:
Is the ability of method to determine the
lowest single value after which the lower
value is not detected. The greater the
sensitivity of a test, the fewer the number of
false-negative results.
Total number of Positive results
Sensitivity = ------------------------------------------------
Total number of infected patients
22. 10. Analytical range:
The lowest and highest values that method
can measure.
11. Detection limit:
The smallest single result that can be
distinguished from blank.
12. Linearity:
The minimal and maximal values at which
the method can produce a reliable result due
to linear reaction without sample dilution or
concentration.
23. A variety of statistical control techniques have
been used in clinical laboratories.
Tabular records with appropriate calculations
can be used to implement the techniques, but
graphical displays are often easier to interpret.
Therefore, control charts have been accepted as
a more effective way to implement most control
techniques.
The Levey-Jennings chart has been the most
widely used technique.
Interpretation of quality control chart
24. Levey-Jennings Control Chart:
The control results are plotted on the Y-axis
versus time on the X-axis. This chart shows the
expected mean value by the solid line in the
centre and indicates the control limits or range
of acceptable values by the dashed lines.
The usual way of interpreting this control chart
is to consider the run to be in control when the
control values fall within the control limits, and
to be out of control when a result exceeds the
control limits.
25. When changes in control data indicate that the
performance of an analytical method has
deteriorated, the analyst must determine the
cause of the problem.
It is generally useful first to try to classify the
error as random or systematic, because the
different kinds of errors suggest different
sources. Random errors show a wider range of
scatter of the points on the control chart, while
systematic error can be seen when the points
drift or shift to one side of the central line.
Further information on the nature of the
systematic and random errors were previously
mentioned.
28. +2SD
+1 SD
X
-1 SD
-2SD
Days
Figure 3 - Levey-Jennings chart showing a shift of more than 5
values on the same side of the mean and therefore out of control
34. Internal quality assurance
Make sure that:
1. Normal and abnormal control samples are
available as frozen aliquots.
2. Control charts are available and updated.
3. Control results are analyzed by the technician
on monthly basis.
35. External quality assurance
1. Should be performed on quarterly basis.
2. Results are to be discussed with technicians.
3. Should be reported to SLSO.