MQC0 31: Instrumentation & Quality Control IQC-FINALS PDF

MQC0 31: INSTRUMENTATION & QUALITY CONTROL LESSON 10 Lecturer: Mr. Antonio F. Laude Jr. BS Medical Technology Sy. 2024-2025 Transcribed by: Jose Gabriel A. Manalo 2nd year Quality Control ❖ Practicability...

MQC0 31: INSTRUMENTATION & QUALITY CONTROL LESSON 10 Lecturer: Mr. Antonio F. Laude Jr. BS Medical Technology Sy. 2024-2025 Transcribed by: Jose Gabriel A. Manalo 2nd year Quality Control ❖ Practicability o The degree by which a method is ❖ A system of ensuring accuracy and precision easily repeated in the laboratory by including quality control ❖ Precision or reproducibility reagents in every series of measurements. o The ability of an analytical method to ❖ A process of ensuring that analytical results give repeated results on the same are correct by testing known samples (control sample that agree with one another. solutions) that resemble patient samples. ❖ Accuracy ❖ It involves the process of monitoring the o The nearness or closeness of the characteristics of the analytical processes and assayed value to the true or target detects analytical errors during testing. value ❖ It is one component of the quality assurance ❖ Specificity system. o Is the ability of an analytical method o Statistical process to measure only the analyte of o Used to monitor interest o And evaluate ❖ Sensitivity o The analytical process o Is the ability of an analytical method o That produces patient results to measure the smallest Requirements for Statistical Process concentration of the analyte of interest ❖ Regular testing of quality control procedures along with patient samples Kinds of Quality Control ❖ Comparison of quality control results to 1. Intralab (Internal QC) specific statistical limits (ranges) 2. Interlab (External QC) ❖ Diagnostic test o Result Intralab (Internal QC) ▪ Patient result ❖ It involves the analyses of control samples ▪ Quality control result together with the patient specimens. Quality Control Result ❖ It detects changes in performance between the present operation and the “stable” ❖ Quantitative (a number) operation ❖ Qualitative (positive or negative) ❖ It is important for the daily monitoring of ❖ Semi-quantitative (limited to a few different accuracy and precision of analytical methods values) ❖ Detects both random and systematic errors Quality Results Interlab (External QC) ❖ Are used to validate whether the instrument ❖ It involves proficiency testing programs that is operating within pre-defined specifications periodically provide samples of unknown ❖ Inferring that patient tests results are reliable concentration of analytes to participating Terms to Define laboratories ❖ It is important in maintaining long-term ❖ Reliability accuracy of the analytical methods. o the ability of an analytical method to ❖ It is also used to determine estimates of the maintain accuracy and precision over state-of-the-art interlaboratory performance an extended period of time during ❖ Difference of >2 in the results indicates that a which equipment, reagents and laboratory is not in aggrement with the rest of personnel may change. the laboratories included in the program.  Objectives of Quality Control ❖ Consequently, the statistics and ranges calculated from this data are also specific for ❖ To check the stability of the machine each level of control and reflect the behavior ❖ To check the quality of reagents of the test at specific concentrations. The ❖ To check technical errors most fundamental statistics used by the Quality Control Products laboratory are the mean [x] and standard deviation [s]. ❖ Is a patient-like material ideally made from human serum, urine or spinal fluid Calculating the Mean ❖ It can be a liquid or freeze-dried (lyophilized) ❖ The mean (or average) is the laboratory’s material and is composed of one or more estimate of the analyte’s true value for a constituents (analytes) of known specific level of control. concentration. ❖ The formula for calculating the mean [x] is: ❖ It is tested in the same manner as patient o xn/n samples. o Where:  = sum ❖ Normal control product o xn = each value in the data set o Contains normal levels of the analyte o n = number of values in the data set being tested ❖ To calculate a mean for a specific level of ❖ Abnormal control product control, first, add all the values collected for o Contains the analyte at a that control. Then divide the sum of these concentration above or below the values by the total number of values. normal range for the analyte. Calculating a Standard Deviation Characteristics of an Ideal QC Material ❖ a statistic that quantifies how close numerical 1. Resembles human sample values (i.e. QC values) are in relation to each 2. Inexpensive and stable for long periods other. 3. No communicable diseases ❖ The term precision is often used 4. No matrix effects/known matrix effects interchangeably with standard deviation. 5. With known analyte concentrations ❖ Another term, imprecision, is used to express 6. Convenient packaging for easy dispensing and how far apart numerical values are from each storage other. Regular Testing ❖ Is calculated for control products from the same data used to calculate the mean ❖ At least daily to monitor analytical process ❖ It provides the laboratory with an estimate of ❖ Test stable for 24 hours or some change has test consistency at specific concentrations. occurred – controls should be assayed more ❖ The repeatability of a test may be consistent frequently (low standard deviation, low imprecision) ❖ Regular testing of QCPs– creates a database ❖ Or inconsistent (high standard deviation, high that the laboratory uses to validate the test imprecision system. ❖ Inconsistent repeatability may be due to the ❖ Validation occurs by comparing daily QC chemistry involved or to a malfunction. results to a laboratory-defined range of QC ❖ If it is a malfunction, the laboratory must values. correct the problem. Calculation and Use of QC Statistics ❖ It is desirable to get repeated measurements of the same specimen as close as possible. ❖ QC statistics for each test performed in the ❖ Good precision is especially needed for tests laboratory are calculated from the QC that are repeated regularly on the same database collected by regular testing of patient to track treatment or disease control products. The data collected is specific progress. for each level of control. ❖ May also be used to monitor on-going day-to- day performance. (𝑥𝑛 −𝑥)2 ❖ √ 𝑛−1 ❖ Where:  = sum ❖ s = standard deviation ❖ x = mean (average) of the QC values ❖ (xn – x)2 = the sum of the squares of differences between individual QC values and the mean ❖ n = the number of values in the data set  MQC0 31: INSTRUMENTATION & QUALITY CONTROL LESSON 11 Lecturer: Mr. Antonio F. Laude Jr. BS Medical Technology Sy. 2024-2025 Transcribed by: Jose Gabriel A. Manalo 2nd year Terminologies Quality Control Charts ❖ Statistics 1. Shewhart Levey-Jennings Chart o is the science of gathering, analyzing, Most widely used system in clinical interpreting and presenting data. laboratory ❖ Mean Allows the laboratorians to apply multiple o a measure of central tendency. It is rule without the aid of a computer. associated with symmetrical or A graphic representation of the normal distribution. acceptable limits of variation in the results ❖ Standard deviation (SD) of an analytical method. o a measure of the dispersion of values 2. Gaussian Curve from the mean. 3. Cumulative Sum Graph (CUSUM) o It helps describe the normal curve. A 4. Youden/Twin Plot measure of the distribution range. ❖ Coefficient of Variation (CV) o a percentile expression of the mean; an index of precision. o CV = SD/mean x 100 ❖ Variance o is called the standard deviation squared; a measure of variability. o V = (SD)2 ❖ Median o is the value of the observation that divides the observations into two groups, each containing equal numbers of observations. It is the midpoint of a distribution; 50th percentile. ❖ Mode o is the most frequent observation. ❖ Inferential Statistics o are used to compare the means or standard deviations of two groups of data. ❖ t-test o is used to determine whether there is a statistically significant difference between the means of two groups of data. ❖ F-test o is used to determine whether there is a statistically significant difference between the standard deviation of two group of data. ❖ Standard Deviation index (SDI) o the difference between the value of a data point and the mean value divided by the group’s SD.  MQC0 31: INSTRUMENTATION & QUALITY CONTROL LESSON 12 Lecturer: Mr. Antonio F. Laude Jr. BS Medical Technology Sy. 2024-2025 Transcribed by: Jose Gabriel A. Manalo 2nd year Levey-Jennings Chart Using a Levey-Jennings Chart to Evaluate Run Quality ❖ A chart illustrating the allowable limits of error in laboratory test performance, the ❖ The laboratory needs to document that limits are a defined deviation from the mean quality control results have been inspected to of a control serum, most commonly 2 assure the quality of the analytical run. standard deviations (Bishop, 2010). ❖ This documentation is accomplished by ❖ The Levey-Jennings Chart (L-J or LJ) is used to maintaining a QC Log and using the Levey- graph successive (run-to-run or day-to-day) Jennings chart on a regular basis. quality control values. ❖ This QC Log can be maintained on a computer ❖ A chart is created for or on paper. o each test and ❖ Once the QC results are entered into the QC o level of control. Log, they should be plotted on the Levey- ▪ Glucose Jennings chart. ▪ Creatinine ❖ When the results are plotted, an assessment ▪ Cholesterol can be made about the quality of the run. ▪ Potassium ❖ The technologist/technician performing the ▪ Sodium test should look for systematic error and ❖ The first step is to calculate decision limits. random error. o These limits are: Summary ▪ + 1s , ▪ +2s and ❖ L-J chart is a chart illustrating the allowable ▪ +3s from the mean. limits of error in laboratory test performance. ❖ Decision limits are used to make the L-J chart. Calculating Quality Control Limits ❖ 68% of all QC values fall within +1 standard ❖ These ranges are used with the mean to deviation (1s). construct the Levey-Jennings Chart. ❖ 95.5% of all QC values fall within +2 standard ❖ Mean +/- SD (limit) = range of limits deviations (2s) of the mean. ❖ Example: ❖ Approximately 99.7% of all QC values are o The mean for the Level I Potassium found to be within +3 standard deviations (3s) control is 4.1 mmol/L and the of the mean. standard deviation is 0.1 mmol/L. ❖ The laboratory needs to document that o +1s range is quality control results have been inspected to ▪ 4.0 to 4.2 mmol/L assure the quality of the analytical run. ▪ 4.1 – (0.1)(1) = 4.0 ❖ The technologist/technician performing the ▪ 4.1 + (0.1) (1) = 4.2 test should look for systematic error and o +2s range is random error. ▪ 3.9 to 4.3 mmol/L Types of Errors ▪ 4.1 – (0.1)(2) = 3.9 ▪ 4.1 + (0.1) (2) = 4.3 1. Random error o +3s range is 2. Systematic error ▪ 3.8 to 4.4 mmol/L 3. Clerical errors ▪ 4.1 – (0.1)(3) = 3.8 ▪ 4.1 + (0.1) (3) = 4.4 Random Error ❖ Is present in all measurements; it is due to chance, can be both positive and negative. ❖ Is the basis for varying differences between repeated measurements. ❖ It is due to instrument, operator and Pre-analytical Errors environmental conditions (variations in 1. Improper patient preparation techniques) 2. Mislabelled specimen o pipeting errors, mislabelling samples, 3. Incorrect order of draw temperature fluctuation, improper 4. Incorrect patient identification mixing of sample and reagent. 5. Wrong specimen container ❖ There is acceptable (or expected) random 6. Incorrect anticoagulant to blood ratio error as defined and quantified by standard 7. Improper mixing of sample and additives deviation. 8. Incorrect specimen preservation ❖ There is an unacceptable (unexpected) 9. Incorrect used of tubes for blood collections random error that is any data point outside 10. Mishandled specimen (transport and storage) the expected population of data (e.g., a data 11. Missed or incorrectly interpreted laboratory point outside the +3s limits). requests. Systematic Error Post-analytical Errors ❖ Is an error that influences observations 1. Unavailable or delayed laboratory results consistently in one direction (constant 2. Incomplete laboratory results difference) 3. Wrong transcription of the patient’s data and ❖ It is detected as either positive or negative laboratory results. bias ❖ often related to calibration problems, Systematic Error deterioration of reagents and control materials, unstable and inadequate reagent ❖ Is evidenced by a change in the mean of the blanks, contaminated solutions, failing control values. instrumentation and poorly written ❖ The change in the mean may be gradual and procedures demonstrated as a trend in control values or ❖ It is a measure of the agreement between the it may be abrupt and demonstrated as a shift measured quantity and the true value. in control values. o Constant error Trend o Proportional/Slope/Percent Error ❖ A trend indicates a gradual loss of reliability in Constant Error the test system. ❖ Refers to a difference between the target ❖ Trends are usually stable. Causes of trending value and the assay value. may include: ❖ It is independent of sample concentration ❖ Deterioration of the instrument light source ❖ It exists when there is a constant difference ❖ Gradual accumulation of debris in between the comparative method and the sample/reagent tubing test method regardless of the concentration. ❖ Gradual accumulation of debris in electrode surfaces Proportional/Slope/Percent Error ❖ Aging of reagents ❖ Gradual deterioration of control materials ❖ Results in greater deviation from the target ❖ Gradual deterioration of incubation chamber value due to higher sample concentration. temperature (enzymes only) ❖ Exists when the difference between the test ❖ Gradual deterioration of light filter integrity method and the comparative method values ❖ Gradual deterioration of calibration are proportional to the analyte concentration Clerical Error ❖ The highest frequency of clerical errors occurs ❖ with the use of handwritten labels and request forms.  Shift ❖ Abrupt changes in the control mean are defined as shifts. Shifts in QC data represents a sudden and dramatic positive or negative change in test system performance. ❖ Shifts may be caused by: o Sudden failure or change in the light source o Change in reagent formulation o Change of reagent lot o Major instrument maintenance o Sudden change in incubation temperature (enzymes only) o Change in room temperature or humidity o Failure in the sampling system o Failure in reagent dispense system o Inaccurate calibration/recalibration  MQC0 31: INSTRUMENTATION & QUALITY CONTROL LESSON 13A Lecturer: Mr. Antonio F. Laude Jr. BS Medical Technology Sy. 2024-2025 Transcribed by: Jose Gabriel A. Manalo 2nd year Westgard Control Rules Terminologies ❖ It recognized that the use of simple upper and ❖ Analytical Run lower control limits are not enough to identify o Are set of control and patient analytical problems. specimens assayed, evaluated and ❖ Error detection rates can increase without reported together. increasing the false rejection rate. ❖ Delta Check ❖ Westgard used the term control rule to o Is the most commonly used patient- indicate if the analytical process is out of based QC technique. control. o It requires computerization of test data so that current results can be Control Rules compared with past results. ❖ 12s – use as a rejection or warning rule, for o The difference between two screening purposes; random error (reject). consecutive measurements of the ❖ 13s – effective in determining random error. same analytes on the same individual. ❖ 22s – initially applied to the control ❖ Interference experiments observations within the most recent analytical o Are used to measure systematic run errors or inaccuracy caused by o Response most often to systematic substances other than the analyte. errors o Examples: hemoglobin, lipids, ❖ 41s – responsive to systematic errors. bilirubin, anticoagulants, ❖ R4s – responsive to random errors or increased preservatives imprecision ❖ Linear Range/Dynamic Range ❖ 10X – systematic error. o Is the concentration range over which the measured concentration is equal Things to Remember to the actual concentration without ❖ The combination of the control rules used in modification of the method. conjunction with a control chart has been ❖ Physiologic Limit called the Multiple Shewhart procedure. o Is sometimes referred to as absurd ❖ In measuring systematic error or inaccuracy, value. Westgard et al recommended that at least 40 o Helps detect sample contamination or samples, and preferably 100 samples be run dilution, inadequate sample volume, by comparison-of-methods experiment (test inadequate reagent volumes, sudden method and reference method). major problems with the method, or ❖ Duplicate analyses of each sample by each incorrect recording or transmission of method (test method and reference method) the result. are recommended, with the duplicate ❖ Point of Care Testing (POCT) samples analyzed in different runs and in o Analytical testing performed outside different order of analysis on the two runs the confines of the central laboratory, (should be performed within 4 hours) usually by nonlaboratorian personnel ❖ The sensitivity of the multiple procedure can (nurses, respiratory therapists, etc.) be increased to detect smaller systematic o Use of portable whole blood glucose errors by increasing the number of meters for the management of observations considered. patients with diabetes ❖ Once the error is identified and corrected, the o Analytical testing performed outside patient and control specimens are reanalyzed. the confines of the central laboratory, usually by nonlaboratorian personnel (nurses, respiratory therapists, etc.)  o Use of portable whole blood glucose 3. Discrete Analyzer – most popular and versatile meters for the management of analyzer. patients with diabetes Terminologies ❖ Quality Assurance (QA) o Can be envisioned as a tripod with ❖ Batch testing program development, assessment o all samples are loaded at the same and monitoring, and quality time, and a single test is conducted on improvement forming the three legs. each sample. o All systematic actions necessary to ❖ Parallel testing provide adequate confidence that o more than one test is analyzed laboratory services will satisfy the concurrently on a given clinical given medical needs for patient care. specimen. ❖ Quality Patient Care ❖ Random access testing o Includes effective test request forms, o any test can be performed on any clear instruction for patient sample in any sequence. preparation and specimen handling, ❖ Sequential testing appropriate turn around time for o multiple tests analyzed one after specimen processing, testing and another on a given specimen. result reporting, appropriate ❖ Open reagent system reference ranges and intelligent result o a system other than manufacturer’s reports. reagents can be utilized for ❖ Recovery experiment measurement. o It will show whether a method ❖ Closed reagent system measures all the analytes or only part o a system where the operator can only of it. use the manufacturer’s reagents. o It estimates inaccuracy or systematic error. ❖ Reference Limit/ Reference Interval/ Reference Value o A value obtained by observation or measurement of a particular type of quality on a reference individual. o Usual values for a healthy population that represents 95% central tendency. 3 Best Approaches to Automation 1. Increases the number of tests to be performed in a given period. 2. Minimizes variation of result from one laboratorian to another. 3. Eliminates the potential error in manual analyses such as pipetting, calculation and transcription of results. Analyzers 1. Continuous Flow Analyzer – uses a glass coil 2. Centrifugal Analyzer – force generated by centrifugation  MQC0 31: INSTRUMENTATION & QUALITY CONTROL LESSON 13B Lecturer: Mr. Antonio F. Laude Jr. BS Medical Technology Sy. 2024-2025 Transcribed by: Jose Gabriel A. Manalo 2nd year Westgard Rules ❖ The relationship between the value and other control results within the current and ❖ 1981, Dr. James Westgard of the University of previous analytical runs must be examined. Wisconsin published an article on laboratory ❖ If no relationship can be found and no source quality control that set the basis for of error can be identified , it must be assumed evaluating analytical run quality for medical that a single control value outside the +2s laboratories. limits is an acceptable random error. Patient ❖ The elements of the Westgard system are results can be reported. based on principles of statistical process control used in industry nationwide since the Rule 13s 1950s. ❖ This rule identifies unacceptable random error ❖ There are six basic rules in the Westgard or possibly the beginning of a large systematic scheme. error. Any QC result outside +3s violates this ❖ These rules are used individually or in rule. combination to evaluate the quality of analytical runs. ❖ Westgard devised a shorthand notation for expressing quality control rules. ❖ Most of the quality control rules can be expressed as NL o where N = represents the number of control observations to be evaluated o L = represents the statistical limit for evaluating the control observation. ❖ Thus 13s represent a control rule that is violated when one control observation exceeds the +3s control limits. Rule 22s Rule 12s ❖ This rule identifies systematic error only. ❖ This is a warning rule that is violated when a ❖ The criteria for violation of this rule are: single control observation is outside the +2s o Two consecutive QC results limits. o Greater than 2s ❖ 4.5% of all quality control results will fall o On the same side of the mean between the 2s and 3s limits. ❖ 22S Rule = Reject the run when 2 consecutive ❖ This rule merely warns that random error or control measurements exceed the same systematic error may be present in the test +2SD or -2SD control limit system. ❖ There are two applications to this rule: within- run and across run. The within-run application  affects all control results obtained for the Westgard Rule current analytical run. ❖ Violation of any of the following rules does ❖ For example, if normal (level I) and abnormal not necessarily require rejection of the (Level II) control are assayed in this run and analytical run. both levels of control are greater than 2s on ❖ These violations typically identify smaller the same side of the mean, this run violates systematic error or analytical bias that is not the within-run application for systematic often clinically significant or relevant. error. Analytical bias may be eliminated by ❖ If however, Level I is -1s and Level II is +2.5s (a performing calibration or instrument violation of the 12s rule), the Level II result maintenance. from previous run must examined. If Level II in the previous run was at +2.0s or greater, then Rule 31s the across run application for systematic error is violated. ❖ The criteria which must be met to violate this ❖ Violation of the within-run application rule are: indicates that systematic error is present and o Three consecutive results that it affects potentially the entire analytical o Greater than 1s curve. Violation of the across run application o On the same side of the mean indicates that only a single portion of the Rule 41s analytical curve is affected by the error. ❖ The criteria which must be met to violate this Rule R4s rule are: ❖ This rule identifies random error only o Four consecutive results ❖ It is applied only within the current run. o Greater than 1s ❖ If there is at least a 4s difference between o On the same side of the mean control values within a single run, the rule is violated for random error. ❖ For example, assume both level I and level II have been assayed within the current run. Level I is +2.8s above the mean and Level II is - 1.3s below the mean. ❖ R4S Rule = Reject the run when 1 control measurement exceed the +2SD and the other exceeds the -2SD control limit ❖ There are two applications to the 31s and 41s rule. ❖ These are within control material (e.g. all Level I control results) or across control materials (e.g., Level I, II, and III control results in combination). ❖ Within control material violations indicate systematic bias in a single area of the method ❖ The total difference between the two control curve while violation of the across control levels is greater than 4s (e.g.[+2.8s – (-1.3s)] = measures application indicates systematic 4.1s). error over a broader concentration.  Rules 7x|8x|9x|10x|12x ❖ Rule 12x ❖ These rules are violated when there are: ❖ 7 or 8, or 9 or 10, or 12 control results ❖ On the same side of the mean regardless of the specific standard deviation in which they are located. ❖ 10x Rule = Reject the run when 10 consecutive control measurements fall on one side of the mean When a Rule is Violated ❖ Warning rule = use other rules to inspect the control points ❖ Rejection rule = “out of control” o Stop testing o Identify and correct problem o Repeat testing on patient samples and controls o Do not report patient results until ❖ Each of these rules also has two applications: problem is solved and controls o Within control material (e.g., all Level indicate proper performance I control results) or across control materials (e.g. Level I, II, and III Solving “Out-of-Control” Problems control results in combination). ❖ Policies and procedures for remedial action o Within control material violations ❖ Troubleshooting indicate systematic bias in a single ❖ Alternatives to run rejection area of the method curve while violation of the across control Summary materials application indicates ❖ Why QC program? systematic bias over a broader o Validates test accuracy and reliability concentration. ❖ How to implement a QC program? o Establish written policies and procedures o Assign responsibility for monitoring and reviewing o Train staff o Obtain control materials o Collect data o Set target values (mean, SD) o Establish Levey-Jennings charts o Routinely plot control data o Establish and implement troubleshooting and corrective action protocols o Establish and maintain system for documentation