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QUALITY CONTROL
- Dr. Pavalaveelzi C.M
Joseph Juran
Edward Deming
 Quality is “uniformity and
dependability”
 Focus on SPC and statistical
tools
 “14 Points” ...
The Absolutes of Quality Management
Crosby defined Four Absolutes of Quality Management, which are,
1. The First Absolute:...
Total Quality Management (TQM) process is also referred to
as total quality control (QC), total quality leadership,
contin...
Total quality management (TQM) view of an organization as a
system of processes.
1. Empowerment of
front line
employees
2....
Total quality management (TQM) framework for managing
quality in a healthcare laboratory
Total quality management (TQM) framework for managing
quality in a healthcare laboratory
Analytical processes,
general pol...
Total quality management (TQM) framework for managing
quality in a healthcare laboratory
Analytical processes,
general pol...
Total quality management (TQM) framework for managing
quality in a healthcare laboratory
Analytical processes,
general pol...
Total quality management (TQM) framework for managing
quality in a healthcare laboratory
Analytical processes,
general pol...
Total quality management (TQM) framework for managing
quality in a healthcare laboratory
Analytical processes,
general pol...
PDCA cycle / the Shewhart Cycle/ the Deming Cycle
Need of quality control in clinical laboratory
1. Support provision of high quality healthcare
- reduce morbidity
- reduce...
Consequences of poor quality
1. Inappropriate action
- over-investigation
- over treatment
- mistreatment
2. Inappropriate...
Quality assurance represent practices that are
generally recommended for ensuring that desired
quality goals are achieved....
• Quality Assurance includes all phases of pre-analytical,
analytical and post analytical
• Quality control is a part of q...
• Quality Assurance includes all phases of pre-analytical,
analytical and post analytical
• Quality control is a part of q...
• Quality Assurance includes all phases of pre-analytical,
analytical and post analytical
• Quality control is a part of q...
 Fundamental requirement for all objective quality control
systems are clearly defined quality goals.
 Each assay and ea...
 Random error, RE - An error that can be either positive or negative,
the direction and exact magnitude of which cannot b...
 Accuracy - Closeness of the agreement between the result of a
measurement and a true value of the measurand.
 Precision...
Variables that may cause imprecision
1. Equipment
• multiple instruments
• Pipettes
• Sporadic maintenance
2. Reagents
• L...
CONTROL OF ANALYTICAL VARIABLES
 Reference Materials and Methods
They are major factors in determining the quality and re...
Secondary reference materials are used to provide
working calibrators for field methods and to assign values to
control ma...
IMPLEMENTING A QC PROGRAM
- Establish written policies and procedures
- Assign responsibility for monitoring and reviewing...
 STANDARD OPERATING PROCEDURES (SOP)
 It is a comprehensively
written document that
describes the
Laboratory procedure
a...
• Method procedures and manuals
should be reviewed annually and
revised whenever changes occur.
• It is also a good practi...
Inventory Control of Materials
• Process of ensuring that appropriate amount of stocks
are maintained so as to be able to ...
 The quality of materials should be
monitored when they are received.
 Patient results from new lots of reagents
and cal...
 Control limits –
• Limits on a control chart which are used as criteria for
indicating the need for action, or for judgi...
Control material
Assayed
- manufacturer
has measured
the values
- control limits
too wide for
use in an
individual
laborat...
• Little vial-to-vial variation should occur, so that
differences between repeated measurements
are attributed to the anal...
 Control chart –
 A graphical method for evaluating whether a process is
or is not in a 'state of statistical control.'
...
 Control limits are usually calculated from the mean (x)
and standard deviation(s) obtained from repeated
measurements on...
 Standard deviation –
- A statistic that describes the dispersion or spread of a set of
measurements about the mean value...
• The initial estimate should be based on measurements
obtained over a period of at least 20 days
 shift in the mean – ac...
• The initial estimate should be based on measurements
obtained over a period of at least 20 days
 shift in the mean – ac...
• It is common practice to plot 1 month’s data on a chart,
usually only one or two points a day.
• Interpretation of the c...
Performance characteristic - A property of a test that is
used to describe it quality.
For a control procedure, the perfor...
Probability refers to the likelihood that an event will occur
 Probability for false rejection (pfr) –
• no analytical er...
 Different QC procedures have different
sensitivities or capabilities for detecting
analytical errors.
 Practical goals ...
 Power function graph - describe the statistical
power of the control procedure
 Two power
function graphs are
necessary...
Power functions are determined by mathematical
calculations or by computer simulation studies.
USES –
1. evaluating the pe...
 Operating specifications chart (OPSpecs chart)
Relationship between the quality requirement for a
test, the imprecision ...
This OPSpecs chart is derived from the analytical quality planning model
shown earlier, setting ΔRE to 1.0, then rearrangi...
• ΔSEcrit is the critical systematic error that would shift
the distribution enough to cause defined percentage
of the tes...
Step-by-Step Process for Selecting QC Procedures
1. Define the analytical quality requirement in the form of
an allowable ...
6. Select control rules and n’s that provide 90% detection
of the critical systematic error and less than 5% false
rejecti...
These control rules and n’s are
usually implemented by setting up
 a Levey-Jennings control chart or
 a Westgard multiru...
 Levey-Jennings Control Chart
 Otherwise called a single-value chart
 To use a Levey-Jennings control chart the steps b...
2. Construct a control chart
• Label x axis – time (day, run number)
y-axis – control values
• Set the control limit , ± 3...
Eg. Levey-Jennings control chart having control limits set
as the mean ± 3 s
• False rejections are in effect an inherent
property of the control procedure.
• They occur because of the control limits...
Advantages of LJ chart
• Simple data analysis and display
• Easy adaptation and integration into existing
control practice...
Disadvantages
• The use of 2 s control limits are not generally
recommended.
• With the use of 3 s control limits, the fal...
Westgard Multirule Chart
• A series of control rules for interpreting control data
are used.
• The probability of false re...
12s Rule
• One control observation exceeding the mean ± 2 s
• “warning” rule
• initiates testing of the control data by th...
13s Rule
• One control observation exceeding the mean ± 3 s
• It is a rejection rule
• Primarily sensitive to random error.
• Two consecutive control observations exceeding the
same mean plus 2 s or mean minus 2 s limit
• It is a rejection
• sens...
R4S Rule
• One observation exceeding the mean plus 2 s and another
exceeding the mean minus 2 s
• It is a rejection rule
•...
• Four consecutive observations exceeding the mean plus 1 s
or the mean minus 1 s
• It is a rejection rule
• sensitive to ...
100 Rule
• Ten consecutive control observations falling on one side of
the mean (above or below, with no other requirement...
• R4S rule is applied only within a run, so that
between run systematic errors are not
wrongly interpreted as random error...
 WESTGARD MULTIRULE CHART
• Comparison of the probability for error detection
between the multirule procedure and the Levey-
Jennings chart having 3...
Control of analytical quality using patient data
1. Time consuming
2. Less sensitive
3. However, many of the control probl...
1. Monitoring individual patient results with clinical
correlation
2. correlation with other laboratory tests
3. Intra lab...
• When duplicates are obtained from the same
method, this range chart monitors only random error
method.
• When duplicates...
 Delta checks
• Errors detected by comparing laboratory test
results with values obtained on previous
specimens from the ...
 LIMIT CHECKS
• Patient’s test results should be reviewed to check that
they are within the physiologic ranges compatible...
EXTERNAL QUALITY ASSESSMENT
AND PROFICIENCY TESTING PROGRAMS
• To compare the performance of different laboratories
• inte...
• Several external QA programs are offered by professional
societies or by manufacturers of control materials.
• Provided ...
• The basic operation of these programs involves having
all participating laboratories analyze the same lot of
control mat...
• Summary reports are prepared by the program sponsor
and are distributed to all participating laboratories.
• Time consum...
 Proficiency testing (PT) programs are a type of
external quality assessment
 Simulated patient specimens made from a co...
 Six Sigma Principles and Metrics
 Adopted as the universal measure of process
performance
 GOAL - 6 sigma’s or 6 stand...
 For laboratory measurements sigma
performance can be as,
Sigma = (TEa − bias)/SD
 Sigma metrics from 6.0 to 3.0 represe...
ANOREXIC QC –
Limits are too tight, so more outliers more false
rejection
GAMBLER QC –
Repeating the quality control again...
ANALYTICAL TRACEABILITY
In 2002, the Joint Committee for Traceability in
Laboratory Medicine (JCTLM) was created.
It provi...
International Organization for Standardization (ISO)
 ISO 9000 is a set of standards for ensuring quality management
and ...
THANKYOU
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Quality control

  1. 1. QUALITY CONTROL - Dr. Pavalaveelzi C.M
  2. 2. Joseph Juran Edward Deming  Quality is “uniformity and dependability”  Focus on SPC and statistical tools  “14 Points” for management PDCA method  Quality is “fitness for use”  Pareto Principle (the 80-20 law)) Cost of Quality  General management approach as well as statistics
  3. 3. The Absolutes of Quality Management Crosby defined Four Absolutes of Quality Management, which are, 1. The First Absolute: The definition of quality is conformance to requirements 2. The Next Absolute: The system of quality is prevention 3. The Third Absolute: The performance standard is zero defects 4. The Final Absolute: The measurement of quality is the price of non- conformance The Quality Vaccine Crosby explained that this vaccination was the medicine for organizations to prevent poor quality which includes, Integrity, Systems, Communication, Operations, Policies. Philip Crosby
  4. 4. Total Quality Management (TQM) process is also referred to as total quality control (QC), total quality leadership, continuous quality improvement, quality management science, or, more generally industrial quality management.  Many healthcare organizations have adopted the concepts and principles o QM. QUALITY is defined as conformance with the requirements of users or customers and the satisfaction to their needs and expectations.
  5. 5. Total quality management (TQM) view of an organization as a system of processes. 1. Empowerment of front line employees 2. Direct involvement
  6. 6. Total quality management (TQM) framework for managing quality in a healthcare laboratory
  7. 7. Total quality management (TQM) framework for managing quality in a healthcare laboratory Analytical processes, general policies, practices & and procedures that define how all aspects of the work are done.
  8. 8. Total quality management (TQM) framework for managing quality in a healthcare laboratory Analytical processes, general policies, practices & and procedures that define how all aspects of the work are done. statistical control procedures, nonstatistical check procedures, such as linearity checks, reagent and standard checks, and temperature monitors.
  9. 9. Total quality management (TQM) framework for managing quality in a healthcare laboratory Analytical processes, general policies, practices & and procedures that define how all aspects of the work are done. statistical control procedures, nonstatistical check procedures, such as linearity checks, reagent and standard checks, and temperature monitors. laboratory performance, such as TAT, specimen identification, patient identification, & test utility.
  10. 10. Total quality management (TQM) framework for managing quality in a healthcare laboratory Analytical processes, general policies, practices & and procedures that define how all aspects of the work are done. statistical control procedures, nonstatistical check procedures, such as linearity checks, reagent and standard checks, and temperature monitors. laboratory performance, such as TAT, specimen identification, patient identification, & test utility. structured problem- solving process to help identify the root cause of a problem and a remedy for that problem
  11. 11. Total quality management (TQM) framework for managing quality in a healthcare laboratory Analytical processes, general policies, practices & and procedures that define how all aspects of the work are done. statistical control procedures, nonstatistical check procedures, such as linearity checks, reagent and standard checks, and temperature monitors. laboratory performance, such as TAT, specimen identification, patient identification, & test utility. structured problem- solving process to help identify the root cause of a problem and a remedy for that problem standardize the remedy, establish measures for performance monitoring, ensure that the performance achieved satisfies quality requirements, and document the new QLP.
  12. 12. PDCA cycle / the Shewhart Cycle/ the Deming Cycle
  13. 13. Need of quality control in clinical laboratory 1. Support provision of high quality healthcare - reduce morbidity - reduce mortality - reduce economic loss 2. Ensure credibility of lab 3. Generate confidence in lab results.
  14. 14. Consequences of poor quality 1. Inappropriate action - over-investigation - over treatment - mistreatment 2. Inappropriate inaction - lack of investigation - no treatment 3. Delayed action 4. Loss of credibility of lab 5. Legal action
  15. 15. Quality assurance represent practices that are generally recommended for ensuring that desired quality goals are achieved. • It is a broad spectrum of plans, policies, and procedures that together provide an administrative structure for a laboratory’s efforts to achieve quality goals. Quality control is often used to represent those techniques and procedures that monitor performance parameters.
  16. 16. • Quality Assurance includes all phases of pre-analytical, analytical and post analytical • Quality control is a part of quality assurance • It is a continual process.
  17. 17. • Quality Assurance includes all phases of pre-analytical, analytical and post analytical • Quality control is a part of quality assurance • It is a continual process.  Continuous is without checks  Continual includes check points to assess the efficiency
  18. 18. • Quality Assurance includes all phases of pre-analytical, analytical and post analytical • Quality control is a part of quality assurance • It is a continual process.  Continuous is without checks  Continual includes check points to assess the efficiency (BEST)
  19. 19.  Fundamental requirement for all objective quality control systems are clearly defined quality goals.  Each assay and each clinical application of each assay logically should have its own optimal and its own acceptable performance limits.  Error - Deviation from the truth or from an accepted, expected true or reference value  Bias - A systematic difference or systematic error between an observed value and some measure of the truth. Generally used to describe the inaccuracy of a method relative to a comparative method in a method comparison experiment
  20. 20.  Random error, RE - An error that can be either positive or negative, the direction and exact magnitude of which cannot be exactly predicted. • Examples – errors in pipetting, changes in incubation period • Can be minimized by training, supervision and adherence to standard operating procedures.  Systematic error, SE - An error that is always in one direction and is predictable • Examples – changes in reagent batch, modifications in testing procedures.  Allowable total error, Tea - An analytical quality requirement that sets a limit for both the imprecision (random error) and inaccuracy (systematic error) that are tolerable in a single measurement or single test result.
  21. 21.  Accuracy - Closeness of the agreement between the result of a measurement and a true value of the measurand.  Precision - Closeness of agreement between quantity values obtained by replicate measurements of a quantity, under specified conditions
  22. 22. Variables that may cause imprecision 1. Equipment • multiple instruments • Pipettes • Sporadic maintenance 2. Reagents • Lot to lot variation 3. Staff • Difference in training, competencies
  23. 23. CONTROL OF ANALYTICAL VARIABLES  Reference Materials and Methods They are major factors in determining the quality and reliability of the analytical values produced by a clinical laboratory. Definitive method, DM - An analytical method that has been subjected to thorough investigation and evaluation for sources of inaccuracy, including nonspecificity. Primary reference materials are those of the highest quality that are used in the 1. development and validation of reference methods, 2. calibration of definitive and reference methods and 3. production of secondary reference materials.
  24. 24. Secondary reference materials are used to provide working calibrators for field methods and to assign values to control materials. Control materials are used only to monitor field methods. Calibration - The process of testing and adjustment of an instrument, kit, or test system, to provide a known relationship between the measurement response and the value of the substance being measured by the test procedure Standard - Material or solution with which the sample is compared in order to determine the concentration or other quantity.
  25. 25. IMPLEMENTING A QC PROGRAM - Establish written policies and procedures - Assign responsibility for monitoring and reviewing - Train staff - Obtain control materials - Collect data - Set target values (mean, SD) - Establish control charts - Plot control data - Establish and implement trouble shooting and corrective action protocols - Establish and maintain system for documentation
  26. 26.  STANDARD OPERATING PROCEDURES (SOP)  It is a comprehensively written document that describes the Laboratory procedure and all related issues.  Essential for ensuring uniformity in laboratory procedures. Documentation of Analytical Protocols
  27. 27. • Method procedures and manuals should be reviewed annually and revised whenever changes occur. • It is also a good practice to retain outdated procedures in an archival file.
  28. 28. Inventory Control of Materials • Process of ensuring that appropriate amount of stocks are maintained so as to be able to meet demands without delay. • Stable operation of laboratory methods is critically dependent on the materials used with the methods. • Storage temperatures for stability should be defined and monitored. • Initiating orders when stock reaches a certain predetermined level reduces required storage
  29. 29.  The quality of materials should be monitored when they are received.  Patient results from new lots of reagents and calibrators be compared with those obtained with previous lots  Establishing pretesting procedures is costly, in terms of both time and money.
  30. 30.  Control limits – • Limits on a control chart which are used as criteria for indicating the need for action, or for judging whether a set of data does or does not indicate a state of control • refer to the defined limits or ranges of results expected  Control materials – • Specimens that are analyzed for QC purposes • It is available, often commercially, liquid or lyophilized, and packaged in aliquots that can be prepared and used individually.
  31. 31. Control material Assayed - manufacturer has measured the values - control limits too wide for use in an individual laboratory. Unassayed - less expensive - Must perform data analysis Homemade or in-house - Pooled sera collected in the lab
  32. 32. • Little vial-to-vial variation should occur, so that differences between repeated measurements are attributed to the analytical method alone. • The concentration of analyte should be in normal and abnormal intervals, corresponding to concentrations that are critical in the medical interpretation of test results.
  33. 33.  Control chart –  A graphical method for evaluating whether a process is or is not in a 'state of statistical control.'  The determinations are made through comparison of the values of some statistical measure(s) for an ordered series of samples, or subgroups, with control limits.  In healthcare laboratories, the Levey-Jennings chart is commonly used to plot the result observed for a stable control material versus time, usually the day or run number.
  34. 34.  Control limits are usually calculated from the mean (x) and standard deviation(s) obtained from repeated measurements on known specimens by the particular analytical method that is to be controlled.  Mean – - The arithmetic average of a set of values. - A measure of central tendency of the distribution of a set of replicate results. - Often abbreviated by an x with a bar over it.
  35. 35.  Standard deviation – - A statistic that describes the dispersion or spread of a set of measurements about the mean value of a gaussian or normal distribution. - The standard deviation is not a valid statistic if a distribution is not Gaussian.  The control limits are set to include most of the control values, usually 95 to 99.7%, which correspond to the mean ±2 or 3 SDs.
  36. 36. • The initial estimate should be based on measurements obtained over a period of at least 20 days  shift in the mean – accuracy problem = SE  increase in the SD – precision problem = RE
  37. 37. • The initial estimate should be based on measurements obtained over a period of at least 20 days  shift in the mean – accuracy problem = SE  increase in the SD – precision problem = RE
  38. 38. • It is common practice to plot 1 month’s data on a chart, usually only one or two points a day. • Interpretation of the control data is guided by certain decision criteria or control rules, which define when an analytical run is judged “in control” (acceptable) or “out of control” (unacceptable). • Analytical run - segment of data for which a decision on acceptability is to be made. • The different control procedures have different performance capabilities
  39. 39. Performance characteristic - A property of a test that is used to describe it quality. For a control procedure, the performance characteristics are the probabilities for error detection and false rejection, or the average run lengths for rejectable and acceptable quality. For a measurement procedure, the performance characteristics include analytical range, precision, accuracy, interference, recovery, and also the frequency and duration of analytical errors.
  40. 40. Probability refers to the likelihood that an event will occur  Probability for false rejection (pfr) – • no analytical errors are present except for the inherent imprecision or inherent random error of the analytical method. • The probability for false rejection should be zero.  Probability for error detection (ped) – • there is an analytical error, in addition to the inherent or background random error. • The probability for error detection should be high (near 1) Critical performance characteristics
  41. 41.  Different QC procedures have different sensitivities or capabilities for detecting analytical errors.  Practical goals are to achieve a probability of error detection of 0.90 (i.e., a 90% chance of detecting the critically sized systematic error), while keeping the probability of false rejection at 0.05 or less
  42. 42.  Power function graph - describe the statistical power of the control procedure  Two power function graphs are necessary to describe, 1. The performance for random error (RE) 2. The performance for systematic error (SE).
  43. 43. Power functions are determined by mathematical calculations or by computer simulation studies. USES – 1. evaluating the performance capabilities of individual control procedures, 2. for comparing the performance of different control procedures, and 3. for designing new procedures with improved performance characteristics.  Best control procedure – one with the lowest probability for false rejection and the highest probability for detecting errors.
  44. 44.  Operating specifications chart (OPSpecs chart) Relationship between the quality requirement for a test, the imprecision and inaccuracy that are allowable, and the QC that is necessary This OPSpecs chart is derived from the analytical quality planning model Z – chance of exceeding the quality requirement. When z is 1.65, a maximum defect rate of 5% may occur before an analytical run is rejected.
  45. 45. This OPSpecs chart is derived from the analytical quality planning model shown earlier, setting ΔRE to 1.0, then rearranging as follows: analytical quality requirement of 10% (Tea) and an analytical quality assurance for systematic error of 90%.
  46. 46. • ΔSEcrit is the critical systematic error that would shift the distribution enough to cause defined percentage of the test results to exceed TE. • detected to maintain a defined quality requirement. Calculated as [(TEa - biasmeas)/smeas] - 1.65 Critical Systematic Error
  47. 47. Step-by-Step Process for Selecting QC Procedures 1. Define the analytical quality requirement in the form of an allowable total error (TEa). 2. Evaluate method performance to obtain estimates of imprecision and inaccuracy 3. Obtain power function graphs for the control rules and n’s of interest, or OPSpecs charts for the defined TEa. 4. Calculate the critical systematic error 5. Assess the probabilities for error detection and false rejection.
  48. 48. 6. Select control rules and n’s that provide 90% detection of the critical systematic error and less than 5% false rejections. 7. Select a total QC strategy to provide an appropriate balance between statistical and nonstatistical process improvement and preventive maintenance QC procedures. 8. Reassess for changes in method performance as necessary.Cost-effective QC depends on doing the right QC to ensure that the desired quality is achieved at minimum cost
  49. 49. These control rules and n’s are usually implemented by setting up  a Levey-Jennings control chart or  a Westgard multirule chart,
  50. 50.  Levey-Jennings Control Chart  Otherwise called a single-value chart  To use a Levey-Jennings control chart the steps below are to be followed. 1. Analyze samples of the control material by the analytical method to be controlled on at least 20 different days during stable method performance. -The mean and standard deviation are to be Calculated.
  51. 51. 2. Construct a control chart • Label x axis – time (day, run number) y-axis – control values • Set the control limit , ± 3 s, n >= 2 ± 2 s, n = 1 3. Introduce control specimens into each analytical run, record the values, and plot each value on the control chart.
  52. 52. Eg. Levey-Jennings control chart having control limits set as the mean ± 3 s
  53. 53. • False rejections are in effect an inherent property of the control procedure. • They occur because of the control limits that have been selected—not because of any problems with the analytical method.
  54. 54. Advantages of LJ chart • Simple data analysis and display • Easy adaptation and integration into existing control practices • A low level of false rejections
  55. 55. Disadvantages • The use of 2 s control limits are not generally recommended. • With the use of 3 s control limits, the false rejection problem is eliminated, but unfortunately error detection is also reduced.
  56. 56. Westgard Multirule Chart • A series of control rules for interpreting control data are used. • The probability of false rejections is kept low by selecting only those rules whose individual probabilities for false rejection are very low (0.01 or less). • The probability for error detection is improved by selecting those rules that are particularly sensitive to random and systematic errors.
  57. 57. 12s Rule • One control observation exceeding the mean ± 2 s • “warning” rule • initiates testing of the control data by the other control rules.
  58. 58. 13s Rule • One control observation exceeding the mean ± 3 s • It is a rejection rule • Primarily sensitive to random error.
  59. 59. • Two consecutive control observations exceeding the same mean plus 2 s or mean minus 2 s limit • It is a rejection • sensitive to systematic error. 22S Rule
  60. 60. R4S Rule • One observation exceeding the mean plus 2 s and another exceeding the mean minus 2 s • It is a rejection rule • sensitive to random error.
  61. 61. • Four consecutive observations exceeding the mean plus 1 s or the mean minus 1 s • It is a rejection rule • sensitive to systematic error. 41S Rule
  62. 62. 100 Rule • Ten consecutive control observations falling on one side of the mean (above or below, with no other requirement on size of the deviations) • It is a rejection rule • sensitive to systematic error.
  63. 63. • R4S rule is applied only within a run, so that between run systematic errors are not wrongly interpreted as random errors. • 22S, 41S, and 100 rules can be applied across runs and materials. • However, the false rejections do increase as n increases, limiting n to a maximum of 4 to 6.
  64. 64.  WESTGARD MULTIRULE CHART
  65. 65. • Comparison of the probability for error detection between the multirule procedure and the Levey- Jennings chart having 3 s limits shows improved error detection for the multirule procedure. • The R4S rule improves the detection of random error • The 22S, 41S, and 100 rules improve the detection of systematic error.
  66. 66. Control of analytical quality using patient data 1. Time consuming 2. Less sensitive 3. However, many of the control problems detected with these techniques may not be evident with conventional QC systems.
  67. 67. 1. Monitoring individual patient results with clinical correlation 2. correlation with other laboratory tests 3. Intra laboratory duplicates • simple quality control procedure that does not require stable control materials • differences between duplicates are plotted
  68. 68. • When duplicates are obtained from the same method, this range chart monitors only random error method. • When duplicates are obtained from two different laboratory methods, then the range chart actually monitors both random and systematic errors • very effective in identifying biases between methods that may indicate the need to recalibrate a method or instrument.
  69. 69.  Delta checks • Errors detected by comparing laboratory test results with values obtained on previous specimens from the same patient. • Particularly errors in specimen identification • The expected variability of test results depends on both the analyte and the time interval between determinations.
  70. 70.  LIMIT CHECKS • Patient’s test results should be reviewed to check that they are within the physiologic ranges compatible with life. • Detecting clerical errors, such as transposed digits or misplaced decimal points.
  71. 71. EXTERNAL QUALITY ASSESSMENT AND PROFICIENCY TESTING PROGRAMS • To compare the performance of different laboratories • internal QC being necessary for the daily monitoring of the precision and accuracy of the analytical method and • external quality assessment being important for maintaining long-term accuracy of the analytical methods.
  72. 72. • Several external QA programs are offered by professional societies or by manufacturers of control materials. • Provided by CMC Vellore, AIIMS Delhi • Increases the lab confidence • May be needed for accreditation
  73. 73. • The basic operation of these programs involves having all participating laboratories analyze the same lot of control material, usually daily as part of the internal QC activities. • The mean of all results or the mean of results from peer laboratories (those performing the test with similar methods) is taken as the target value and is used for comparison with the individual laboratory’s result. • Results are sent to the sponsoring group for the data analysis.
  74. 74. • Summary reports are prepared by the program sponsor and are distributed to all participating laboratories. • Time consuming. • Thus the data analysis is not available in real time • Useful only for monthly reviews and periodic problem- solving activities. • However, with advances in telecommunications and the arrival of the World Wide Web, real-time external QC is a possibility
  75. 75.  Proficiency testing (PT) programs are a type of external quality assessment  Simulated patient specimens made from a common pool are analyzed by the laboratories enrolled in the program. Results are returned to a central facility and are evaluated to determine the “quality” of each laboratory’s performance.  Government and licensing agencies are increasingly using PT as an objective method for accrediting laboratories, thereby giving them official authorization to operate.
  76. 76.  Six Sigma Principles and Metrics  Adopted as the universal measure of process performance  GOAL - 6 sigma’s or 6 standard deviations of process variation should fit within the tolerance limits for the process
  77. 77.  For laboratory measurements sigma performance can be as, Sigma = (TEa − bias)/SD  Sigma metrics from 6.0 to 3.0 represent the range from “best case” to “worst case.”  Methods with Six Sigma performance are considered “world class”  Methods with sigma performance less than 3 are not considered acceptable for production.
  78. 78. ANOREXIC QC – Limits are too tight, so more outliers more false rejection GAMBLER QC – Repeating the quality control again and again until the value falls with in range BLIND MAN QC – Taking SD or limits from outside. Poor quality
  79. 79. ANALYTICAL TRACEABILITY In 2002, the Joint Committee for Traceability in Laboratory Medicine (JCTLM) was created. It provides a, • Worldwide platform to promote and give guidance on internationally recognized and accepted equivalence of measurements in laboratory medicine and traceability to appropriate measurement standards and, • To review and list reference methods, materials, and laboratories that provide higher order measurement methods.
  80. 80. International Organization for Standardization (ISO)  ISO 9000 is a set of standards for ensuring quality management and quality assurance in manufacturing and service industries ISO 9001 : 2015 – set out requirements for quality management ISO 9001 : 2015 – covers basic concepts and language services ISO 13485 : 2016 – medical devices (2016 - revised every 5 years) ISO 19011 : 2011 – guidance on international audits of QMS. ISO 15189 : 2012 – accreditation bodies and autoverification
  81. 81. THANKYOU
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