Total quality management (TQM) and Quality Assurance & QAs 1st part

This topic is for medical laboratory

1. Unit 9: Total quality management (TQM) and Quality Assurance & QAs Introduction,  Total Quality Management Framework. o Quality Assessment o Quality Assurance o Quality Laboratory Procedures o Quality Control  Internal Quality Control  External Quality Control  Quality Control charts – L-J chart  Terminologies used in Quality Assurance program/ Selection of analytical methods o Accuracy o Precision o Sensitivity o Specificity o Standard o Control (Positive, Negative, High, normal, low sera) o Standard deviation (SD) o Coefficient of variation (CV) o Mean o Use of control and calibration in laboratory in practices  Sources of error o Pre-analytical o Analytical o Post-analytical  Method of improving laboratory reports

2. Introduction: Total Quality Management (TQM) in medical laboratories is a comprehensive approach focused on consistently delivering accurate, reliable, and timely test results that meet or exceed customer expectations.  It's a shift towards continuous improvement, involving all aspects of the laboratory process, from pre-analytical to post-analytical phases, to minimize errors and enhance patient care.  TQM is a management philosophy that emphasizes customer satisfaction through continuous improvement in all processes.  In a medical laboratory, this means focusing on the quality of every step, from sample collection to reporting results, to ensure accuracy, reliability, and timeliness. 

3. TQM Important in Medical Laboratories Improved Patient Care: Accurate and timely test results are crucial for diagnosis, treatment, and monitoring patient health. TQM helps minimize errors and ensures that patients receive the best possible care.  Increased Efficiency: By streamlining processes and reducing errors, TQM can lead to increased efficiency and productivity in the laboratory.  Reduced Costs: Minimizing errors and waste can lead to cost savings for the laboratory and the healthcare system.  Enhanced Reputation: A commitment to quality can enhance the laboratory's reputation and build trust with patients and other healthcare providers. 

4. Quality Assurance (QA) in a medical laboratory is a system of procedures and processes designed to ensure the accuracy, reliability, and consistency of laboratory testing results.  It encompasses all activities from test ordering to result reporting, aiming to minimize errors and maximize the quality of patient care.  A robust QA program is crucial for informed medical decision-making, regulatory compliance, and maintaining the credibility of laboratory services.  Aspects of Quality Assurance in a Medical Laboratory: Standard Operating Procedures (SOPs): Detailed, written instructions for each laboratory procedure, ensuring consistent execution ( निरन्तर कार्यान्वयन ). 

5. Quality Control (QC): Procedures to monitor test performance during each run, using control samples to detect errors.  Proficiency Testing ( दक्षता परीक्षण ) : Participation in external quality assurance programs to assess laboratory performance against other labs.  Equipment Calibration and Maintenance: Ensuring instruments are properly calibrated and maintained for accurate results.  Staff Training and Competency( योग्यता ) : Providing ongoing training and competency assessments to ensure staff are qualified and proficient ( निपुण ).  Documentation and Record Keeping: Maintaining accurate and complete records of all laboratory activities, including SOPs, QC data, and corrective actions( सुधारात्मक कार्यहरू ).  Error Management and Corrective Action: Implementing procedures to identify, investigate, and correct errors, preventing recurrence ( पुनरावृत्ति ). 

6. Audits and Inspections ( निरीक्षण ) : Conducting regular internal and external audits to assess compliance with quality standards.  Continuous Improvement: Regularly reviewing processes and implementing changes to improve the quality of laboratory services.  Pre-analytical, Analytical, and Post-analytical Phases: QA encompasses all stages of testing, from patient identification and sample collection to result reporting and interpretation. 

7. Benefits of a strong QA program: Improved Patient Care: Accurate and reliable test results lead to better diagnosis and treatment decisions. Reduced Errors: QA programs minimize errors, leading to fewer repeat tests and improved patient safety. Regulatory Compliance ( नियामक अनुपालन ) : Many regulatory bodies require laboratories to implement QA programs. Enhanced Credibility: A strong QA program demonstrates a commitment to quality and builds trust with patients, physicians, and other stakeholders. Cost Efficiency: By reducing errors and repeat testing, QA programs can save time and resources. 

8. Total Quality Management Framework A Total Quality Management (TQM) framework in a medical laboratory focuses on systematically improving all aspects of laboratory services to ensure high-quality, reliable, and accurate results that meet or exceed user and patient needs.  It involves a structured approach that integrates quality principles into all processes, from sample collection to result reporting.  Quality Assessment ( गुणस्तर मूल्याङ्कन ) : Quality assessment (QA) in a medical laboratory is a systematic process that ensures the accuracy, reliability, and validity of laboratory testing and results.  It's a crucial component of a comprehensive( व्यापक )  quality management system  (QMS) and involves monitoring( निगरानी ), evaluating( मूल्याङ्कन ), and improving all laboratory processes.  This includes everything from specimen handling to data reporting, aiming to minimize errors and maximize the quality of patient care. 

9. Benefits of Quality Assessment: Improved Accuracy ( शुद्धता ) and Reliability ( विश्वसनीयता ) : QA helps minimize errors and ensures that laboratory results are accurate and reliable, leading to better patient care. Reduced Costs: By preventing errors and improving efficiency ( दक्षता ), QA can help reduce unnecessary costs associated with retesting and corrective actions. Enhanced Credibility ( बढेको विश्वसनीयता ) : Laboratories with robust QA programs are more likely to be trusted by clinicians and patients, enhancing their reputation( प्रतिष्ठा ) and credibility. Compliance with Regulations ( नियमहरु संग अनुपालन ) : QA programs help laboratories comply ( पालना गर्नुहोस् ) with regulatory requirements and accreditation standards ( मान्यता मापदण्ड ). Continuous Improvement ( निरन्तर सुधार ) : QA encourages a culture of continuous improvement, leading to ongoing enhancements ( संवर्द्धनहरू ) in laboratory processes and performance. 

10. Quality Assurance ( गुणस्तर आश्वासन ) Quality assurance (QA) in a medical laboratory is a comprehensive system designed to ensure the accuracy, reliability, and validity of laboratory testing processes and results.  It encompasses a range of activities aimed at preventing errors and maintaining high standards throughout the entire testing process, from pre-analytical to post-analytical phases.  Benefits of QA in medical laboratories: Improved accuracy and reliability of test results: QA helps minimize errors and ensures that results are ( भरपर्दो )and can be used for accurate diagnosis and treatment. 

11. Enhanced patient safety: Accurate test results are crucial for making informed medical decisions, and QA helps ensure patient safety by minimizing the risk of errors.  Reduced costs: By preventing errors and improving efficiency ( दक्षता ), QA can help reduce the costs associated with retesting, wasted reagents, and other issues related to inaccurate results.  Improved laboratory efficiency: QA practices, such as SOPs and document control, can streamline laboratory workflows and improve overall efficiency.  Increased credibility ( विश्वसनीयता ) and reputation ( प्रतिष्ठा ) : Accreditation and certification, which are often based on strong QA systems, can enhance the credibility and reputation of the laboratory. 

12. Quality Laboratory Procedures Quality laboratory procedures in a medical lab encompass a comprehensive system of practices and protocols designed to ensure accuracy ( शुद्धता ), reliability ( विश्वसनीयता ), and safety( सुरक्षा ) in all aspects of testing and analysis.  These procedures cover the entire testing process, from sample collection to result reporting, and are essential for providing trustworthy diagnostic information.  Benefits: Improved Accuracy and Reliability: Quality procedures, including  quality control (QC) and quality assurance (QA) , are essential for verifying the precision and reliability of test results. This reduces the likelihood of errors that could lead to misdiagnosis or inappropriate treatment. 

13. Enhanced Patient Safety: Accurate diagnostic information is vital for effective patient management. By minimizing errors, quality laboratory procedures directly contribute to improved patient safety and better treatment decisions.  Streamlined Processes and Increased Efficiency ( क्षमता ) : Well-defined procedures and  standard operating procedures (SOPs)  optimize ( अनुकूलन ) workflows, reduce turnaround times, and improve overall laboratory productivity.  Cost Savings: While implementing quality systems may involve initial investment, the long-term benefits, such as reduced errors and waste, translate to cost savings.  Regulatory Compliance( विनियामक अनुपालन ) : Adhering to quality standards and regulations ensures that laboratories meet the required benchmarks for operation and maintain accreditation.  Enhanced Data Integrity and Traceability: Quality management systems help ensure the integrity ( अखंडता )and traceability ( पता लगाने की क्षमता ) of data, making it easier to track samples, identify trends, and improve processes.  Increased Confidence in Results: Consistent and reliable results build confidence in the laboratory's performance, both internally and among clinicians and patients. 

14. Quality Control Quality control (QC) in a medical laboratory is a system designed to ensure the accuracy, reliability, and timeliness of test results.  It involves monitoring, assessing, and improving the analytical processes involved in testing patient samples.  This is achieved through various procedures like using control materials, proficiency testing, and instrument calibration.  Effective QC helps identify and correct errors, ensuring the overall quality and reliability of laboratory testing.  Benefits: Accurate and Reliable Results: QC ensures that lab procedures are functioning within acceptable ( स्वीकार्य ) ranges, minimizing errors and discrepancies ( भिन्नता ) in test results. This leads to more accurate diagnoses and appropriate treatment decisions. 

15. Improved Patient Safety: Accurate test results are crucial for patient care. By minimizing errors, QC helps prevent misdiagnosis, inappropriate treatment, and potential harm to patients.  Increased Customer Trust: When patients and clinicians trust the accuracy of laboratory results, it fosters ( पालनपोषण ) confidence in the healthcare system. This is especially important when labs handle sensitive and critical tests.  Cost Reduction: While QC involves initial investment, it can lead to cost savings in the long run. By identifying problems early, QC helps prevent costly rework, repeat testing, and unnecessary treatments.  Enhanced Efficiency: Implementing QC procedures can improve overall lab efficiency by streamlining processes, reducing errors, and optimizing workflows.  Compliance with Regulations: Many regulatory bodies require laboratories to implement QC programs. By adhering to these standards, labs can avoid penalties ( दण्ड ) and maintain their accreditation ( मान्यता ).  Continuous Improvement: QC provides a framework for ongoing monitoring ( निरन्तर अनुगमन )and evaluation of lab performance, allowing for continuous improvement in processes and quality. 

16. 9.3 Internal Quality Control Internal quality control (IQC) in medical laboratories ensures the reliability of test results by continuously monitoring the performance of laboratory equipment and procedures.  It involves the regular analysis of control samples with known target values to detect and correct errors before they impact patient care Internal Quality Control (IQC) refers to the measures and procedures implemented within a laboratory or organization to ensure the accuracy, reliability, and consistency of its processes and results.

17. Aspects of IQC include: Monitoring Accuracy ( शुद्धता ) and Precision ( परिशुद्धता ) (quality of being exact, accurate, and careful) : IQC assesses both the accuracy (closeness to the true value) and precision (reproducibility) of laboratory measurements.  Detection of Errors: IQC helps identify random errors (fluctuations) and systematic errors (consistent biases) in testing processes.  Use of Control Materials: Laboratories use control samples (with known analyte concentrations) alongside patient samples to evaluate the performance of testing methods.  Statistical Analysis: Control results are analyzed using statistical rules (like  Westgard rules ) to determine if they fall within acceptable limits.  Troubleshooting and Corrective Action: If control results fall outside acceptable limits, corrective actions are taken, such as recalibrating instruments or repeating tests, before patient results are reported.  Documentation: IQC procedures and results are meticulously( सावधानीपूर्वक ) documented to provide a record of quality assurance.  Frequency of Testing: The frequency of IQC testing depends on the specific test and the laboratory's quality control plan. 

18. Benefits of IQC: Improved Patient Safety: Accurate and reliable test results are crucial for proper diagnosis and treatment, minimizing risks associated with incorrect results.  Enhanced Laboratory Efficiency ( दक्षता ) : Detecting and correcting errors early reduces the need for repeat testing, saving time and resources.  Increased Confidence in Results: IQC builds trust in the laboratory's ability to produce reliable results.  Meeting Accreditation Standards: Many accreditation bodies require laboratories to implement robust ( बलियो ) IQC programs. 

19. 9.4 External Quality Control External quality control (EQC) in a medical laboratory, also known as  proficiency( दक्षता ) testing  (PT) or  External Quality Assessment  (EQA), is a system where a laboratory's testing performance is evaluated by an external agency using unknown samples.  This process helps ensure the reliability of laboratory test results by comparing a laboratory's performance against other participating laboratories.  EQA is a crucial component of a comprehensive quality management system, providing objective evidence of testing quality and identifying areas for improvement. 

20. Types of EQA: EQA can be implemented through various methods, including: Proficiency Testing (PT):  Sending unknown samples to laboratories and evaluating their performance.  Rechecking/Retesting:  A reference lab rechecks or retests previously analyzed slides or samples.  On-site Evaluation:  External evaluators visit the laboratory to observe routine practices.  EQC Important: Verification of Internal Quality Control: EQC acts as a verification of a laboratory's  internal quality control (IQC)  system, identifying systematic errors that IQC might miss

21. Identification of Systematic Errors: EQC can detect biases or errors that may not be apparent through IQC alone, such as issues with calibration or reagent problems.  Improvement of Testing Quality: By identifying areas for improvement, EQC helps laboratories enhance their overall testing quality and ensure accurate results.  Accreditation ( मान्यता ) Requirements: Participation in EQA is often a requirement for  laboratory accreditation , demonstrating a commitment to quality ( गुणस्तर प्रति प्रतिबद्धता )and reliability.  Patient Safety: Accurate laboratory test results are essential for patient diagnosis and treatment, making EQC crucial for patient safety.  Confidence in Results: EQA provides confidence to both the laboratory and its users (doctors, patients) that the laboratory's results are reliable.  Continuous Improvement: EQA fosters ( पालनपोषण ) a culture of continuous improvement within the laboratory, encouraging ongoing assessment( निरन्तर मूल्याङ्कन ) and refinement ( परिष्करण ) of practices.  (Refinement : act of improving something, making it more elegant, or removing impurities.)

22. 9.5 Quality Control charts – L-J chart In a medical laboratory, a Levey -Jennings (L-J) chart is a graphical tool used for quality control, visually representing how well a laboratory test is performing over time.  It helps to quickly identify if a test is stable and reliable by plotting control values against established limits.  Purpose: Visual Monitoring: L-J charts provide a visual representation of quality control data, making it easy to see trends and patterns in test results.  Stability Assessment: They help determine if a test method is stable and consistently producing accurate results.  Error Detection: By plotting control values and comparing them to established limits (mean and standard deviations), L-J charts can quickly identify potential errors or shifts in the test system. 

23. How it works: Establish Limits:  First, the mean and standard deviation (SD) of the control material are determined over a period of time.  Create the Chart:  The mean, and +/- 1, 2, and 3 SDs are plotted on the chart.  Plot Data:  Daily or regular control values are then plotted on the chart.  Interpretation:  By observing the plotted points, one can determine if the test is "in control" or if there are issues that need to be addressed.  Features: X-axis:  Typically represents time, such as days or shifts. Y-axis:  Represents the control values. Mean:  The average value of the control material. Standard Deviations:  Lines representing +/- 1, 2, and 3 SDs from the mean. 

24. Example: If a laboratory runs a glucose test control daily, the control values would be plotted on an L-J chart.  If a point falls outside of the +2SD or -2SD limits, it might indicate a problem with the test method, such as a shift in accuracy.  Here’s your Levey –Jennings chart for daily glucose QC values — the red points mark results falling outside the ±2 SD limits, indicating possible test accuracy issues.

25. This Levey –Jennings (L-J) chart shows the daily glucose quality control (QC) values over 14 days, compared to statistical limits based on the mean and standard deviation (SD). Key Features Blue line with dots → Daily QC results (glucose control values). Green line → Mean QC value (average of the dataset). Orange dashed lines → ±1 SD (normal variation range). Red dashed lines → ±2 SD (warning limits; potential QC problem if exceeded). Purple dashed lines → ±3 SD (control failure; stop testing and troubleshoot). Interpretation Most points are within ±2 SD → Indicates that the glucose test is generally in control. No point exceeds ±2 SD or ±3 SD → No immediate evidence of random or systematic error. Small variation between days → QC process is stable; no trend (gradual drift) or shift (sudden change in average) is visible. Conclusion The glucose testing method appears accurate and precise during this 14-day period. If a point were to fall outside ±2 SD, it would be a warning sign , and if outside ±3 SD, testing should be halted until the cause is identified.

26. How to prepare L-J chart In a medical laboratory, an L-J chart usually refers to a Levey –Jennings chart , which is used in quality control (QC) to monitor test performance over time. It helps detect trends, shifts, or random errors in laboratory results. Steps to Prepare an L–J Chart 1. Collect QC Data Run control samples (usually Normal & Abnormal levels) with your test daily or with each batch. Record the results. 2. Calculate Control Statistics From your initial QC data set (at least 20 runs is ideal): Mean (𝑋̄) Mean=Sum of all QC results​/Number of results

27. Standard Deviation (SD) Where: SD = standard deviation n = number of measurements xi​ = each individual QC value ˉx = mean (average) of all QC values ∑(xi​−xˉ)2 = sum of the squared differences between each value and the mean

28. Step-by-step Explanation Find the Mean (xˉ):xˉ=sum of all values​/n Subtract the Mean from Each Value This gives the deviation of each data point from the mean:(xi​- ˉx ) Square Each Deviation This removes negative signs and emphasizes larger deviations: (xi​- ˉx )2 Sum the Squared Deviations Add all squared differences together:∑(xi−xˉ)2 Divide by (n − 1) This is called the degrees of freedom correction for a sample standard deviation (instead of the population SD, which divides by n). Take the Square Root To bring the value back to the original units of measurement

29. 3. Draw the Chart X-axis → Dates or run numbers. Y-axis → QC measurement values. Draw horizontal lines at: Mean Mean ± 1 SD Mean ± 2 SD Mean ± 3 SD 4. Plot the Data Plot each day's QC result as a point . Connect points with a line for easy visualization. 5. Interpret Use Westgard rules to decide if the test run is “in control” or “out of control”. Look for: Random error (points scattered irregularly) Shift (6 or more points on one side of the mean) Trend (progressive rise/fall over ≥ 6 points)

30. Example L–J Chart Layout: Date QC Value Mean +1SD -1SD +2SD -2SD +3SD 1 Jan 105 100 102 98 104 96 106 2 Jan 101 ... ... ... ... ... ... 9.6 Phases in IQC Internal Quality Control (IQC) is implemented in three main phases: pre-analytical, analytical, and post-analytical.  These phases encompass the entire testing process, ensuring accuracy and reliability of laboratory results.   Preventive phases  Retrospective phases

31. Preventive phases Preventive phases are crucial for ensuring accurate and reliable test results. These phases, often categorized as pre-analytical, analytical, and post-analytical, focus on preventing errors at each stage of the testing process.  By implementing robust quality control measures and error prevention strategies in each phase, laboratories can minimize the risk of errors and improve patient care, according to research studies.  1. Pre-analytical Phase: This phase encompasses all activities before the actual analysis of the sample, starting from test ordering to sample collection and preparation.  Errors in this phase can significantly impact test results, making it a critical ( आलोचनात्मक ) area for preventive measures. 

32. Areas of focus: Test ordering:  Ensuring the correct tests are ordered based on clinical needs, appropriate test selection, and proper documentation.  Patient identification:  Implementing procedures for accurate patient identification to prevent misidentification errors.  Sample collection:  Using correct techniques for sample collection, including proper site preparation, collection method, and appropriate containers.  Sample handling and transportation:  Ensuring proper handling, storage, and transportation of samples to maintain their integrity.  Documentation:  Meticulous ( सावधानीपूर्वक )documentation of all pre-analytical steps to track samples and ensure traceability ( पत्ता लगाउने क्षमता ). 

33. Preventive actions: Standardized procedures and protocols for each step.  Training and competency assessment ( योग्यता मूल्याङ्कन )for staff involved in sample collection and handling.  Use of electronic health records and barcoding systems to minimize manual errors.  Regular audits and monitoring of pre-analytical processes.  2. Analytical Phase: This phase involves the actual testing of the sample in the laboratory.  Preventive measures in this phase focus on ensuring the accuracy ( शुद्धता ) and reliability ( विश्वसनीयता )of the testing process. 

34. Areas of focus: Quality control (QC):  Implementing QC procedures, including daily calibration, controls, and proficiency testing ( दक्षता परीक्षण ), to ensure instrument accuracy and reliability. Method validation:  Validating new testing methods before implementation ( कार्यान्वयन ) to ensure they are accurate, precise ( सटीक ), and reliable. Proficiency testing:  Participating in external proficiency testing programs to assess the laboratory's performance against other labs. Equipment maintenance:  Implementing a rigorous maintenance ( कडा मर्मतसम्भार ) schedule for all laboratory equipment to prevent malfunctions. Preventive actions: Regular calibration and maintenance of equipment. Use of appropriate QC materials and controls. Implementation of standard operating procedures (SOPs) for all testing procedures. Participation in proficiency testing programs.

35. 3. Post-analytical Phase: This phase includes the reporting of results and interpretation. Preventive actions in this phase focus on ensuring timely and accurate reporting of results to the appropriate individuals.  Areas of focus: Result verification:  Implementing procedures for verifying results before reporting, including checking for outliers ( बाहिरीहरू )and inconsistencies ( असंगतिहरू ). Reporting:  Ensuring timely and accurate reporting of results to the requesting physician or healthcare provider. Critical result reporting:  Implementing procedures for timely communication of critical results that require immediate attention. Preventive actions: Reviewing results by qualified personnel before reporting. Utilizing electronic reporting systems to minimize errors. Implementing a system for tracking and reporting critical results.

36. Retrospective phases Retrospective phases in internal quality control (IQC) of a medical lab involve reviewing past performance to identify potential issues and areas for improvement.  This process typically includes analyzing past  control data ,  error logs , and  quality indicator data  to assess the effectiveness of the laboratory's quality control system and identify trends or patterns that may indicate problems.  1. Data Collection and Review: Control Data Analysis: Reviewing past  Levey -Jennings charts  and other control data to assess the stability and performance of analytical processes. 

37. Error Log Review: Examining past  error reports  and  incident reports  to identify recurring problems or patterns of errors.  Quality Indicator Review: Analyzing historical  quality indicator data ( गुणस्तर सूचक डाटा ), such as  turnaround time ( परिवर्तन समय ),  rejection rates ( अस्वीकार दरहरू ), and  repeat testing rates ( परीक्षण दरहरू दोहोर्याउनुहोस् ), to assess overall performance and identify areas of concern.  2. Identification of Issues ( मुद्दाहरू ) and Trends ( प्रवृत्तिहरू ) : Trend Analysis: Looking for patterns or trends in the data that may indicate a problem, such as a gradual drift in control values or a consistent increase in error rates for a specific test.  Root Cause Analysis: Investigating the underlying causes of identified problems to determine the factors contributing to the errors. 

38. 3. Implementation of Corrective Actions: Developing Solutions: Based on the findings of the retrospective analysis, developing and implementing corrective actions to address the identified issues and prevent future occurrences. Monitoring Effectiveness: Monitoring the effectiveness of the corrective actions by continuing to collect and analyze data to ensure that the implemented solutions are successful.  4. Continuous Improvement: Regular Review: Regularly reviewing the retrospective analysis process and its findings to ensure that the laboratory's quality control system is continuously improving and adapting to changing needs. Adapting Strategies: Adapting the IQC strategy based on the retrospective analysis results to optimize the laboratory's performance and ensure the delivery of accurate and reliable test results. 

39. 9.7 Terminologies used in Quality Assurance program/ Selection of analytical methods Accuracy ( शुद्धता ): Accuracy refers to how closely a test result reflects the true value of what is being measured. It's a crucial aspect of laboratory testing, impacting patient diagnosis and treatment. Accuracy is often evaluated by comparing laboratory results to a reference method or a "gold standard".  Precision ( परिशुद्धता ): Precision refers to the consistency or reproducibility of measurements. A precise test produces similar results when repeated multiple times under the same conditions.

40. Sensitivity( संवेदनशीलता ): Sensitivity refers to a test's ability to correctly identify individuals who have a disease (true positive rate). A highly sensitive test minimizes false negative results, meaning it's good at detecting the presence of a disease when it's actually there.  Specificity( विशिष्टता ): Specificity refers to a test's ability to correctly identify individuals who do not have a particular condition or disease. It's the proportion of true negatives correctly identified as such. A high specificity means the test produces few false positive results, which is crucial for avoiding unnecessary and potentially harmful follow-up procedures. 

41. Control ( Positive , Negative , High, normal , low sera) Controls are essential for ensuring the accuracy and reliability of test results.  Positive and negative controls are used to validate( प्रमाणित )the assay ( परख ) and reagents, while high, normal, and low controls are used to assess the performance of quantitative assays ( मात्रात्मक परीक्षण ).  These controls help identify potential errors, contamination, and ensure that the test is functioning as expected ( अपेक्षित ).  Positive Control: Confirms the assay is working correctly and that the reagents are functional.  Provides a known positive result, indicating that the test can detect the analyte of interest.  For example, in an  ELISA  for antibodies, a positive control would be a sample known to contain the antibody.  Helps verify that negative results are truly negative and not due to assay malfunction ( परख खराबी )

42. Negative Control: Ensures that the test does not produce a false positive result due to contamination or non-specific reactions.  Serves as a baseline for comparison and helps identify any background noise or interference.  For example, in an ELISA, a negative control would be a sample that is known not to contain the analyte ( विश्लेषक ).  Helps validate the specificity of the assay. Quantitative Controls (High, Normal, Low): These are used in assays that measure the quantity of a substance. High, normal, and low control sera are used to assess the accuracy and precision of the quantitative assay. They help determine if the assay is working within acceptable limits across the range of expected values. For example, in a blood glucose test, high, normal, and low glucose controls would be used to ensure the accuracy of the glucose measurement.  

43. Importance of Controls: Ensures Test Validity: Controls validate the entire testing process, from reagent preparation to instrument performance.  Detects Errors: Controls help identify errors that might occur during the testing process, such as reagent contamination or improper technique.  Improves Accuracy and Precision: Controls help ensure that the test results are accurate and precise, leading to reliable diagnoses and treatment decisions.  Quality Assurance: Controls are a crucial part of laboratory quality assurance programs, ensuring that the lab is producing reliable results.  Troubleshooting ( समस्या निवारण ) : If a control fails, it signals a problem with the assay or reagents, allowing for troubleshooting and correction before patient samples are tested

44. Standard deviation ( SD): In a medical laboratory, standard deviation (SD) is a crucial statistical measure that quantifies the precision or repeatability of a test or measurement.  It indicates how much individual results vary from the average (mean) value.  A lower standard deviation signifies greater precision, meaning results are clustered closely around the mean, while a higher standard deviation indicates less precision, with results spread further from the mean. It measures:  Precision( परिशुद्धता ) :  Standard deviation primarily reflects the precision of a test, indicating how consistent ( सुसंगत ) or reproducible ( पुन: उत्पादन गर्न सकिने ) the results are. Spread of data:  It quantifies the dispersion ( फैलावट ) or spread of data points around the mean. Repeatability:  A low SD suggests that repeated measurements on the same sample will likely yield similar results, which is essential for tracking patient progress or monitoring treatment effectiveness. 

45. Example in Lab QC: Suppose a lab runs a glucose control sample 5 times and gets results in mg/ dL : 100, 102, 99, 101, 98 Mean : xˉ = 100+102+99+101+98​/5= 100 Deviation from mean : (0,2,−1,1,−2) Squared deviations : (0,4,1,1,4) Variance : 0+4+1+1+4​/4= 2.5 Standard deviation : SD= 2.5​≈1.58 mg/ dL Deviation from mean: Step 1 – Find the mean (average): xˉ = 100+102+99+101+98/5=100 Step 2 – Find deviation from mean for each value: Deviation= xi​-xˉ 100 − 100 = 102 − 100 = +2 99 − 100 = −1 101 − 100 = +1 98 − 100 = −2 Deviations from mean = 0, +2, −1, +1, −2

46. Variance : Squared deviations = 0, 4, 1, 1, 4 Step 1 – Sum of squared deviations: 0+4+1+1+4=10 Step 2 – Divide by n−1 (sample variance formula in lab QC): Here n=5 measurements. Variance= Sum of squared deviations/ n−1=10/5-1 =10/4= 2.5

47. Coefficient of variation (CV): In medical laboratories, the Coefficient of Variation (CV) is a crucial statistical measure that indicates the precision of a test or assay.  It is calculated as the standard deviation divided by the mean, expressed as a percentage, and represents the relative variability of data points around the mean.  A lower CV signifies better precision, meaning the test results are more consistent and reliable.  CV%= Standard Deviation (SD)/Mean= ×100 Example with our glucose QC data Glucose readings: 100, 102, 99, 101, 98 Mean = 100 mg/ dL SD = 1.58 mg/ dL (from earlier calculation) CV%= 1.58/100= =1.58%

48. Mean: In medical laboratories, the "mean" refers to the arithmetic average of a set of data points, calculated by summing all values and dividing by the number of values.  It's a fundamental statistical measure used to represent the central tendency of a dataset, providing a single value that summarizes the typical value within a set of laboratory test results or measurements.  Importance: The mean is crucial for quality control and establishing reference ranges in medical laboratories. By analyzing the mean of control samples, labs can ensure their instruments and procedures are performing accurately and consistently.

49. Use of control and calibration in laboratory in practices: In medical laboratories, control and calibration are essential practices for ensuring the accuracy and reliability of test results.  Calibration establishes a relationship between instrument readings and actual substance concentrations, while quality control monitors the performance of tests and procedures over time. By understanding the differences and proper application of these concepts, laboratories can minimize errors and maintain high standards of quality.  Importance: Proper calibration reduces bias in instrument readings, ensuring that the instrument provides accurate measurements.  Example: A spectrophotometer used for measuring bilirubin levels in blood samples needs to be calibrated regularly using calibrators with known bilirubin concentrations to ensure accurate readings. 

50. Use of control: Quality control in the medical laboratory is a statistical process used to monitor and evaluate the analytical process that produces patient results. QC results are used to validate whether the instrument is operating within pre-defined specifications, inferring that patient test results are reliable.