Chapter 1: Introduction to Quality Assurance PDF

Chapter 1: Introduction to Quality Assurance by: fikir alelign (MSC) 1/30/2025 1 Learning Objectives Upon completion of this chapter the student will be able to:  Define quality assurance  List important terms in quality assurance  Discuss...

Chapter 1: Introduction to Quality Assurance by: fikir alelign (MSC) 1/30/2025 1 Learning Objectives Upon completion of this chapter the student will be able to:  Define quality assurance  List important terms in quality assurance  Discuss the basic principles of quality assurance  Describe the different components of quality assurance  Describe the importance and necessity of quality assurance  Classify types of diagnostic tests based on type of result obtained and method of analysis 1/30/2025 2   Describe Accuracy and precision  Describe indicator values of diagnostic tests including sensitivity, specificity, test efficiency, predictive values.  Calculate the following diagnostic values:  Sensitivity  Specificity  Overall Test Efficiency  Predictive values  Use the diagnostic values to determine acceptability of test methods 1/30/2025 3 Chapter Outline  Definitionof important terms in quality assurance  Essential components of quality system  Aspects of quality assurance  Characteristics of quality assurance  Basic components of Quality assurance program  Benefits of Quality assurance  The purpose of health laboratory 1/30/2025 4 Chapter Outline  Errors in the clinical laboratories Clerical Errors Sampling errors Analytical errors  Types of Diagnostic tests  Accuracy and precision 1/30/2025 5 Chapter Outline  Indicators of values of diagnostic test Sensitivity Specificity Test Efficiency Predictive values 1/30/2025 6 What is Quality Assurance? Definition of Quality Assurance (QA): development and implementation of measures to assure reliable laboratory service 1/30/2025 7 What Is “Quality?” The ability of a product or service to satisfy stated or implied needs of a specific customer Achieved by conforming to established requirements and standards. 1/30/2025 8 Quality Assurance vs Quality Control quality assurance (QA)" refers to the proactive system of processes and procedures designed to prevent errors and ensure consistent high quality results throughout the testing process“. quality control (QC)" is the reactive method of monitoring and testing samples to identify and address any deviations from established quality standards, essentially detecting issues after they occur. QA focuses on preventing problems, while QC focuses on identifying and correcting them. 1/30/2025 9 Definitions of Terms Pre-analytical: before testing Analytical: testing phase Post-analytical: after testing Clerical Errors: mistakes in writing results Sampling errors: mistakes in the specimen Accuracy : closeness of result to true result Precision : closeness of replicated results of the same sample to each other 1/30/2025 10 Definition of a Lab Quality System The organizational structure, responsibilities, processes, procedures, and resources for implementing quality management of the laboratory or testing site In other words… all activities which contribute to quality of tests, directly or indirectly 1/30/2025 11 Why is the Quality System Important to Patient Sample Testing? Ensures that quality is the foundation of everything we do Sets the standard for level of quality Meets/exceeds customer expectations Provides means to prevent, detect and correct problems Becomes the core of a monitoring, evaluation, & improvement system Reduces costs 1/30/2025 12 Essential of a Quality System Organizati Personne Equipme on l nt Process Purchasi Control Informatio ,Quality ng & n Control & Specimen Manageme Inventory Managemen nt t Documen Occurrenc e Assessm ts & ent Records Manageme nt Process Custome Facilities Improveme r Service & Safety nt 1/30/2025 13 Quality System Organization Quality Policy Sufficient & Standards Resources Clearly Defined A Culture Roles Committed & Accountability to Quality 1/30/2025 14 Quality System Personnel Human Resource Hiring Retention Planning Performance Training Supervision Management 1/30/2025 15 Quality System Equipment Installation & Selection Acquisition Initial Calibration Maintenance, Troubleshooting Disposition Service & Repair 1/30/2025 16 Quality System Purchasing and Inventory Procurement Receiving Storage Inventory Record Management Keeping 1/30/2025 17  Quality System Process Control Standard Specimen Operating Management Procedures Quality Control 1/30/2025 18 Quality System Documents and Records Standardized Document Document Forms Approval Distribution Document Document Storage/Retrieval Destruction 1/30/2025 19 Quality System: Information Management Information Data Collection Flow & Management Patient Privacy & Computer Confidentiality Skills 1/30/2025 20 Quality System: Occurrence Management Written Corrective Procedures for Actions Addressing Errors Occurrence Occurrence Records Reporting 1/30/2025 21 Quality System Essential: Assessment External Quality Assessment Internal Audit Improvement or Self Measures Evaluation 1/30/2025 22 Quality System Process Improvement On-Going Improvement Data Measures Collection 1/30/2025 23 Quality System: Service and Satisfaction Monitoring Process Customer Improvement Satisfaction Rewards 1/30/2025 24 Quality System Facilities and Safety Testing and Storage Safety Practice Areas Safety Procedures & Records 1/30/2025 25 Total Quality Management TQM addresses all these areas of laboratory practice Lab service and resources 1/30/2025 26 Purpose of Health Laboratory Provide patient laboratory results  Diagnostic  Prognostic( predictive)  Monitor treatment  Monitor disease outbreaks 1/30/2025 27 Characteristics and Aspects of Quality Assurance Three phases affect  Useful patient results Aspects of each phase are shown on next diagram. 1/30/2025 28 The Quality Assurance Cycle Patient/Client Prep Sample Collection Reporting Data and Lab Management Safety Customer Service Sample Receipt and Accessioning Record Keeping Quality Control Sample Transport Testing 1/30/2025 29 Basic Components of QA Internal quality assessment (IQA) External quality assessment (EQA) Standardization of processes and procedures (pre-analytic, analytic and post-analytic phases) Management and 0rganization  In other words as it includes; I(QC),EQA and Quality improvement 1/30/2025 30 CON.. Internal QA includes well designed and implemented specimen collection and handling procedures since a patient lab result is only as good as the specimen provided. A well functioning internal assurance scheme results in good performance in external Quality Assessment. 1/30/2025 31 CON.. External QA includes: objectively checking the laboratory’s results and performance in general by means of an external agency or personnel. EQA is accomplished by implementing the following, either alone or usually combined: through proficiency testing, onsite evaluation of all processes and rechecking or retesting samples. 1/30/2025 32 Benefits of Quality Assurance Helps physicians, patients and clients Creates good reputation Motivates staff Is cost-effective Prevents complaints Builds trust 1/30/2025 33 Three Stages of Analysis Pre-analytic Analytic Post-analytic  Errors in each stage should be prevented 1/30/2025 34 Pre-Analytic Errors Process Potential Errors Test Ordering Wrong test for patient, wrong patient, delay Specimen Requirements not met including patient Collection ID, wrong tube, volume, poor sample or wrong time. Specimen Wrong transport conditions. Handling 1/30/2025 35 Pre-Analytic Specimen Collection Errors Wrong:  Patient ID  Anticoagulant  Volume  Process Haemolysis IV contamination -Intravenous (IV) contamination of blood samples occurs when a blood sample is drawn from a vein that's also receiving IV fluids Prolonged tourniquet -can lead to ischemia, which is reduced blood flow 1/30/2025 to the tissue. 36 Preventing and Detecting Errors – Before Testing Check storage and room temperature Select an appropriate testing workspace Check inventory and expiration dates Review testing procedures Collect appropriate specimen 1/30/2025 37 Analytic Errors These errors occur during the actual testing phase when the sample is processed and analyzed in the laboratory. Instrumental problems:  Faulty calibration, improper functioning, or malfunctioning of equipment can cause inaccurate readings.  Inadequate maintenance or outdated equipment may not provide reliable results. 1/30/2025 38 Analytic Errors Operator error: - Inexperience or lack of training can result in mistakes such as incorrect operation of equipment, incorrect application of procedures, or failure to notice potential issues during testing. Reagent issues: - Using expired, contaminated, or incorrectly prepared reagents can affect the test results. - Improper storage of reagents can also alter their effectiveness. 1/30/2025 39 Analytic Errors Methodological errors: Applying the wrong test method for a particular sample or failing to follow the correct procedure can lead to erroneous results. Errors in test protocol (e.g., incorrect volumes, timing, or temperature) can affect the accuracy of the analysis. Environmental factors: Laboratory conditions like temperature, humidity, or electromagnetic interference can influence results, especially for sensitive instruments or reagents. 1/30/2025 40 Quality Assurance vs. Quality Control Quality Assurance Quality Control Activities to ensure process Activities to evaluate a are adequate for a system product or work result Definition to achieve its objectives Establish standard Analyze known QC procedures for sample sample to determine if a collection test is valid Examples Define criteria for Decide if a sample is acceptable samples acceptable for testing 1/30/2025 41 Quality Control Material Assess Analytic phase  Acceptance versus rejection of patient results  2 or 3 control materials 1/30/2025 42 Westgard rules The Westgard rules are a set of statistical quality control guidelines used in laboratories, particularly in clinical and analytical chemistry, to monitor the accuracy and precision of laboratory test results. These rules help ensure the reliability of test results by detecting errors or variations in the testing process. 1/30/2025 43 Rules 1-3s Rule: If one control measurement exceeds 3 standard deviations (SD) from the mean, this is a warning signal that something may be wrong with the test procedure. 2-2s Rule: If two consecutive control measurements exceed 2 SD in the same direction, it suggests a systematic error, and the test should be rejected. R-4s Rule: If the difference between two consecutive control measurements exceeds 4 SD, it indicates random error, prompting rejection of the results. 1/30/2025 44 Example: Imagine you're running a blood glucose test in a lab, and you have control samples (samples with known values) to monitor the accuracy of your testing equipment. You collect control data for the glucose levels at regular intervals, and these measurements are plotted on a control chart. Let's say you have the following control values for a blood glucose test: 110, 112, 115, 113, 111 Mean=sum of all values​/Number of values Mean=561 / 5 ​=112.2 1/30/2025 45  The standard deviation (SD) is a measure of how spread out the values in a data set are around the mean. It gives an idea of the variability or dispersion of the data. Formula for Standard Deviation: 1/30/2025 46  (110−112.2)2=(−2.2)2=4.84 (112−112.2)2=(−0.2)2=0.04 (115−112.2)2=(2.8)2=7.84 (113−112.2)2=(0.8)2=0.64 (111−112.2)2=(−1.2)2=1.44 Sum the squared differences:  4.84+0.04+7.84+0.64+1.44 =14.8 Divide the sum by the number of values (5):  14.8/5=2.96\frac{14.8}{5} = 2.96  Take the square root of the result to find the standard deviation: 2.96≈1.72 1/30/2025 47  The standard deviation helps you understand how much individual test results deviate from the average. In a laboratory, you want results that are consistently close to the mean, so a low standard deviation indicates high precision, while a high standard deviation suggests more variability in your test results. 1/30/2025 48 Preventing and Detecting Errors – During Testing Perform and review Quality Control (QC) Follow safety precautions Conduct test according to written procedures Correctly interpret test results 1/30/2025 49 Post-Analytic Errors Examples include: Clerical errors Report illegible Report sent to the wrong location Information system not maintained Wrong reference ranges Not reporting in a timely manner Not maintaining confidentiality 1/30/2025 50 Types of Diagnostic Test Results Qualitative: positive or negative  Rapid HIV  others Semi-quantitative: estimates the approximate concentration of a substance in a sample, rather than providing a precise numerical value.  Urinalysis biochemical results  ASO Titer 1/30/2025 51 Types of Diagnostic Test Results Quantitative: numerical value with unit  WBC count  CD4 count  Hemglobin g/dL  Glucose mg/dL  Others 1/30/2025 52 Accuracy and Precision Quality Control testing of samples and rules are used to monitor both the precision and the accuracy of the assay in order to provide reliable results. 1/30/2025 53 Accuracy The closeness of the measured result to the true value 1/30/2025 54 Example of Accuracy: Imagine a laboratory is conducting a blood potassium level test for a patient. The true value of potassium in the patient's blood, as determined by a reference method or a gold standard test, is known to be 4.5 mmol/L. Scenario 1: High Accuracy If the laboratory test results for potassium are 4.4 mmol/L, 4.6 mmol/L, and 4.5 mmol/L, the results are considered accurate because they are very close to the true value of 4.5 mmol/L. 1/30/2025 55  Scenario 2: Low Accuracy If the laboratory test results are 3.2 mmol/L, 6.0 mmol/L, and 5.5 mmol/L, the results are inaccurate because they deviate significantly from the true value of 4.5 mmol/L. This could indicate issues with the calibration of the equipment, improper reagents, or other factors that affect the measurement. 1/30/2025 56 Precision Reproducibility or closeness of results to each other 1/30/2025 57 Reliability of Measurement Ability to maintain both precision and accuracy Accuracy: refers to the closeness of the measured result to the true value Precision: refers to the reproducibility or consistency of the result when repeatedly measured 1/30/2025 58 Inaccurate and Imprecise 1/30/2025 59 Comparison of Accuracy and Precision 1/30/2025 60 Precision Calculations Precision is determined by standard deviation and % coefficient of variation (%CV) The standard deviation is a direct measure of precision. A lower SD means the data points are closer to the mean, indicating higher precision. A higher SD indicates more variability, meaning less precision. % CV = (standard deviation x 100%)/ mean Acceptable %CV < 5% (method dependent) 1/30/2025 61  E.g : Study was performed for 50 uL pipette with the following results: Volumes obtained from gravimetric testing of distilled water. Mean of volumes = 49.2 uL standard deviation = 3 uL. Low SD or CV indicates high precision. High SD or CV means more variability, so precision is low. 1/30/2025 62 Accuracy Calculations Accuracy can be determined from bias: bias is the difference between the average of multiple measurements and the true value.  |True value-mean| / True Value x 100%  % Accuracy error should be < 5%  Practice calculating % accuracy error  Study was performed for 50 uL pipette with the following results: Volumes obtained from gravimetric testing of distilled water. Mean of volumes = 49.2 uL standard deviation = 3 uL. 1/30/2025 63 Indicators of Diagnostic Tests Clinicians rely on the laboratory to provide accurate test results  Aidin diagnosis of disease  Determine the patient’s prognosis  Determine effectiveness of treatment  Determine relative risk of contracting disease 1/30/2025 64 Indicators of Diagnostic Tests There are several statistical assessments that can be of value in evaluating the diagnostic usefulness a test This process relates the patient’s test results with the presence or absence of disease The ability of the screening test to differentiate between those who are disease free from those who are affected is called the test validity. Reliability Vs Validity ???? 1/30/2025 65  Reliability is about consistency. A reliable test will consistently produce the same results each time it is administered, assuming the conditions remain the same. Validity is about accuracy. A valid test will measure what it is intended to measure (e.g., accurately diagnosing the presence of a disease). 1/30/2025 66 Indicators of Diagnostic Tests and Medical Usefulness All methods have an inherent amount of error present that will affect test results No method is able to detect all persons with disease accurately No method is able to detect all persons without disease accurately  Is there any test with 100% specific and sensitive ? 1/30/2025 67 Four Possible Outcomes to Test Results and Disease Diagnosis True positive (TP)  A positive test result for patients who have the disease True negative (TN)  A negative test result for patients who do not have the disease False positive (FP)  A positive test result for patients who do not have the disease False negative (FN)  A negative test result for patients who do have the disease 1/30/2025 68 Results of Disease Screening Testing: Possible Outcome A = true positive (TP) b = false-positive (FP) C = false negative (FN) d= true negative (TN) 1/30/2025 69  Positive Predictive Value (PPV): PPV=True Positives / True Positives+False Positives A higher PPV means that a positive test result is more likely to be correct (i.e., the person has the condition). Negative Predictive Value (NPV): NPV=True Negatives / True Negatives+False Negatives A higher NPV means that a negative test result is more likely to be correct (i.e., the person does not have the condition). 1/30/2025 70  Example: Let’s say we have a screening test for a disease (e.g., a new diagnostic test for a type of cancer). We use a sample of 1,000 people, where the true status of the disease is known (either they are diseased or disease-free). After the test is performed, the results can be categorized as follows: 1/30/2025 71  True Positives (TP): 80 (80 diseased people correctly identified as diseased). False Positives (FP): 50 (50 healthy people incorrectly identified as diseased). True Negatives (TN): 870 (870 healthy people correctly identified as disease-free). False Negatives (FN): 0 (0 diseased people incorrectly identified as healthy). 1/30/2025 72 Indicators of Diagnostic Values of Test Definitions Test Sensitivity = Diagnostic Sensitivity  Percentage of patients who have a disease that test positive (true positive) Test Specificity = Diagnostic Specificity  Percentage of patients who do not have disease that test negative (true negative) No test is 100% sensitive and 100% specific Test Efficiency is the relationship between specificity and sensitivity of a test. 1/30/2025 73  Sensitivity=True Positives​ / True Positives+False Negatives Specificity=True Negatives / True Negatives+False Positives 1/30/2025 74