LABORATORY QUALITY CONTROL

LABORATORY QUALITY CONTROL
The concept of quality control in the Clinical Chemistry Laboratory is well established, and it is now a routine requirement to include quality control samples in each batch of tests performed. Laboratory staff must be conscious of how the quality of their work affects the medical diagnosis and treatment of patients. Every biochemical analysis should provide the answer to a question which the clinician has posed about the patient. Course Code RIT 2.2 Revision C RIT 2.2 Revision C

Definitions: Quality Control:- Quality Assurance:-
the process of detecting errors Quality Assurance:- the systems or procedures in place to avoid errors occurring The term Quality Control is often confused with Quality Assurance - which is in effect the quality systems and procedures in place to avoid these errors occurring in the first instance. RIT 2.2 Revision C

… to ensure the reliability of the test results to give the best patient care !
A good laboratory will have both these complementary systems working together to ensure the reliability of the test results and ultimately to give best patient care. RIT 2.2 Revision C

Unreliable Performance ?
Potential consequences include:- patient misdiagnosis delays in treatment increased costs avoidable retests cost US 200million USD per year Even a small calibration bias can effect treatment rates: 1% +ve bias in cholesterol result 5% increase in patients exceeding the treatment cut-off 3% +ve bias 15% increase in patient treatment. So what are the potential consequences of unreliable performance ? The patient could be misdiagnosed, or there could be delays in treatment. The cost to the health care system increases as repeat or other confirmatory tests will have to be run. In the US alone the cost of avoidable follow-up tests could be as high as 200 million USD per year. Studies have indicated that even a small calibration bias can have a dramatic effect on the diagnostic process. For example, a 1% change in bias in the running of a cholesterol test could result in a 5% change in the number of patients exceeding the 200mg/dL cut-off value. This could rise to 15% with a bias of 3%. RIT 2.2 Revision C

Error Classification.. Pre-analytical:- Analytical:- Post-analytical:-
errors before the sample reaches the laboratory Analytical:- errors during the analysis of the sample Post-analytical:- errors occurring after the analysis There are a huge variety of potential errors which can affect the quality of the laboratory results. Effective Quality Assurance will consider them under the three main headings:- pre-analytical analytical post-analytical RIT 2.2 Revision C

Pre - Analytical Errors..
Improper preparation of the patient:- patient fasting glucose test stress and anxiety urinary protein Pre - Analytical errors can occur before the sample ever reaches the laboratory but directly affect the quality and clinical usefulness of the final result. These could include:- Improper Preparation of the Patient:- For example, a glucose test provides more useful data following a period of fasting prior to blood collection. Patient stress or anxiety may affect certain parameters such as urinary protein levels. RIT 2.2 Revision C

Improper preparation of the patient Improper collection of the blood sample:- sample haemolysis LDH, potassium or inorganic phosphate insufficient sample volume unable to carry out all requested tests collection timing 24 hour urine Improper Collection of the Blood Sample:- For example, if the sample is haemolysed, this will effect many tests such as LDH, potassium or inorganic phosphate. Insufficient sample, may make it impossible for a laboratory to measure all of the tests requested. Errors in collection timing. For example, the biggest error in the measurement of any analyte in a 24 - hour urine specimen is collecting an accurately timed volume of urine. RIT 2.2 Revision C

Improper preparation of the patient Improper collection of the blood sample Incorrect specimen container:- serum or plasma fluoride tubes for glucose to inhibit glycolysis EDTA unsuitable anti-coagulant for calcium Incorrect Specimen Container:- For example the choice of the correct tube for the collection of serum or plasma. Samples for glucose should be collected in a tube containing fluoride which inhibits continued glycolysis. Otherwise the time taken for the sample to reach the laboratory before analysis will seriously affect the results. Samples collected with EDTA as an anticoagulant should not be used to perform calcium assays, because of its calcium binding properties. RIT 2.2 Revision C

Improper preparation of the patient Improper collection of the blood sample Incorrect specimen container Incorrect specimen storage:- sample left overnight at room temperature falsely elevated K, Pi and red cell enzymes delay in sample delivery falsely lowered levels of unstable analytes Incorrect Specimen Storage: A blood sample left overnight before being sent to a laboratory will result in falsely elevated potassium, phosphate and red cell enzymes such as AST and LDH due to time dependent leakage of the intracellular fluid into the plasma. Similarly, a delay in sample delivery may cause falsely lowered values for a particularly unstable analyte such as NEFA. Unstable analytes therefore require fast handling and analysis. RIT 2.2 Revision C

Other Factors.. The sex of the patient The age of the patient
male or female The age of the patient new born / juvenile / adult / geriatric Dietary effects low carbohydrate / fat high protein / fat When the sample was taken early morning urine collection pregnancy testing Patient posture urinary protein in bed-ridden patients Other factors and patient information that may effect interpretation of results include:- The Sex of the patient. Age of the patient. Dietary effects. When the sample was taken, for instance an early morning urine Patient Posture. RIT 2.2 Revision C

Other Factors.. Effects of exercise Medical history Pregnancy
creatine kinase / CRP Medical history heart disease / diabetes / existing medication Pregnancy hormonal effects Effects of drugs and alcohol liver enzymes / dehydration Effects of Exercise. Medical History. Effects of Pregnancy. Effects of Alcohol or Drug Abuse. It may appear on the surface, that these errors have little to do with quality control or quality assurance within the laboratory. However the quality of the final result, will be seriously affected by these outside factors. Therefore it is the responsibility of the laboratory to minimise such risks, by collating adequate information, establishing effective standard operating procedures and providing training for the people using the laboratory service. RIT 2.2 Revision C

Analytical Errors.. The sample: labelling preparation
barcoding / aliquoting preparation centrifugation / aspiration storage temperature short –term refrigeration medium term freezing at –20oC long term freezing at -80oC correct test selection Laboratory Information Management System (LIMS) Once the sample arrives in the laboratory a wide variety of potential analytical errors during the performance of the test may affect the quality of the results obtained. The incorrect preparation, storage or labelling of samples. RIT 2.2 Revision C

Analytical Errors.. The sample: Glassware / pipettes / balances:
used incorrectly contaminated poorly calibrated reuse of pipette tips Errors may arise in conjunction with the use of supplementary analytical equipment such as glassware, pipettes, and balances. Are these being used incorrectly, are they properly washed or poorly calibrated ? RIT 2.2 Revision C

poor quality inappropriate storage correct temperature badly maintained fridges or freezers stability shelf-life / working reagent incorrect preparation The sample: Glassware / pipettes / balances: Reagents / calibrators / controls: The quality of the reagents used to perform the tests together with the relevant calibrators and controls will have a critical influence on the reliability of the data generated. When in use are they being correctly prepared, stored properly when not in use, or are they being used outside the recommended shelf-life or working stability. RIT 2.2 Revision C

incorrect analytical procedures poorly optimised instrument settings The sample: Glassware / pipettes / balances: Reagents / calibrators / controls: The application: No matter how good the reagents are, if they are not used in accordance with the recommended analytical procedures or are run on an analyser with poorly optimised settings, errors will occur. RIT 2.2 Revision C

operational limitations temperature control/read times/mixing/carry-over lack of maintenance worn tubing / optics / cuvettes / probes The sample: Glassware / pipettes / balances: Reagents / calibrators / controls: The application: The instrument: The analytical instrumentation used to perform the tests will obviously have an important effect on potential errors. The instrument’s design may limit it’s operational capabilities. The analyser will not perform at its best if it is not looked after and regularly maintained. RIT 2.2 Revision C

Other Factors.. Calculation errors: Transcription errors:
incorrect factor / wrong calibration values Transcription errors: Dilutions errors: incorrect dilution or dilution factor used Lack of training: The human factor: tiredness / carelessness / stress Again various other factors can result in the generation of mistakes. These could include errors in the calculation or transcription of results. When sample dilutions are required due to linearity limitations, is the dilution performed accurately and results multiplied up by the correct factor. Has the technician undergone sufficient training and gained enough experience to allow him to perform the analysis or use the instrument with confidence. The human factor can also be a problem with tiredness, carelessness and stress all influencing performance. RIT 2.2 Revision C

Post - Analytical Errors..
The prompt and correct delivery of the correct report on the correct patient to the correct Doctor. How the Clinician interprets the data to the full benefit of the patient. Once the tests have been performed potential post - analytical errors can come into play. These are essentially concerned with the prompt and correct delivery of the correct report, on the correct patient, to the correct doctor. And finally how the clinician interprets the data he has received to the full benefit of the patient. RIT 2.2 Revision C

How correct your result is.
Accuracy ? How correct your result is. Accuracy refers to the agreement between your value and the 'true' value, that is how correct your result is. Accuracy is generally measured by direct comparison to a reference value or more commonly by using assayed quality control serum, with an accurate value assigned by the manufacturer. When analysed the closer your result obtained is to this target value, the greater your accuracy. RIT 2.2 Revision C

The reproducibility of your results.
Precision ? The reproducibility of your results. Precision refers to the reproducibility of your results, or the agreement between replicate measurements. The closer your results, are to each other, for the same analyte in the same serum, the better your precision. When evaluating a method, precision should be assessed in terms of within run performance (Intra-assay precision) and between run performance (Inter-assay precision). RIT 2.2 Revision C

Accurate and Precise.. Ideally a laboratory should be striving for both good accuracy and precision. In other words, you should be able to get your repeat results close to one another, and the mean of those results should be close to the 'true' value. If a laboratory has confidence in both its accuracy and precision then it should be able to rely on single test analysis and not have to continually repeat tests until they feel they have a correct result. RIT 2.2 Revision C

Imprecise but Accurate !
However, you may have a situation where your results are widely spread giving you poor precision, but the mean of your results is close to the 'true' value giving you apparently good accuracy. In a busy laboratory this is obviously unacceptable as time and resources cannot be wasted on having to run each sample several times to get an acceptable level of accuracy. RIT 2.2 Revision C

Precise but Inaccurate !
You could also get a situation where you have good precision yet poor accuracy: Your results are close together giving you good precision but the mean of your results is not close to the 'true' value, thus accuracy is poor. Generally poor accuracy is relatively easy to solve and would tend to reflect a calibration problem. If, for example, you find that you are always low on albumin by 2 g/L, the standard or calibrator should be reassessed, to bring everything into line. Poor precision, however, is often more difficult to solve. If you find that the spread of values is wide, for a particular analyte it may be due to a variety of problems, such as poor quality of reagents, instrument condition, technologist training etc. as previously discussed. RIT 2.2 Revision C

Specificity ? The ability of a method to measure solely the component of interest. A lack of specificity will affect accuracy falsely elevated values hormones and drugs falsely low values BCP method with bovine albumin The specificity of the assay has an important effect on the accuracy of the results obtained. Specificity refers to the ability of a method to measure solely the component of interest. A lack of specificity could lead to a falsely elevated result where the test is measuring components other than the analyte of interest. This is a particular problem when trying to distinguish structurally similar hormones or drugs. Similarly a falsely low result could be obtained where the test does not measure the analyte completely 100%. For example the lack of specificity of the bromocresol purple method (BCP) for measuring bovine albumin in quality control serum. RIT 2.2 Revision C

Sensitivity ? The ability to detect small quantities of a measured component. will affect both precision and accuracy at the bottom end of the assay range. Sensitivity is the ability to detect small quantities of a measured component, and will subsequently affect both precision and accuracy, when attempting to measure levels at the bottom end of the clinical range. The sensitivity of an assay is established by determining at what point its precision and ultimately the accuracy of the test reaches an unacceptable level. RIT 2.2 Revision C

Values fall randomly about a mean value.
Normal Distribution.. Mean value (x) Frequency If a particular parameter is analysed repeatedly, and the values obtained obey the laws of probability, you will find that the values fall randomly about a mean value. Where the mean (X) is the average result of the set of values. When the results obtained are plotted against the frequency, we get the classical Gaussian Curve or Normal Distribution, with equal numbers of results above and below the mean. Measured value Values fall randomly about a mean value. RIT 2.2 Revision C

Precision ? How disperse the values are.
Quantified by measuring the Standard Deviation (SD) of the set of results. The Precision of the method, is expressed in terms of how disperse the values are. Statistically this is quantified by the measurement of the standard deviation (SD) of the set of results. RIT 2.2 Revision C

Standard Deviation (SD)..
It is defined as the square root of the sum of the squares of the single value deviations from the mean, divided by the number of the values minus one. This is in effect the average deviation for the set of results. A standard deviation is quoted in the same unit of measurement and the lower the SD the better the precision. The lower the SD the better the Precision. RIT 2.2 Revision C

Example: Mean result (x) = 100 mmol/L
Standard deviation (SD) = 1.0 mmol/L Number of results (n) = 100 If we use the following data as an example. RIT 2.2 Revision C

Mean +/- 1SD.. x -1SD +1SD 68% Frequency If we were to create a range based on the mean +/- 1SD , statistically 68% of all results should fall within this range. 99  101 mmol/L 99 100 101 Values fall randomly about a mean value. RIT 2.2 Revision C

Mean +/- 2SD.. x -2SD +2SD 95% Frequency If we were to widen the range to the mean +/- 2SD, then statistically 95% of all results or 19 out of every 20, should fall within this range. 98  102 mmol/L In statistical terms, this would mean that it would be acceptable for 5% or one in every twenty results to fall outside this range. 98 100 102 Values fall randomly about a mean value. RIT 2.2 Revision C

Which is more Precise ? Potassium SD = 0.1 mmol/L
Sodium SD = 2.0 mmol/L From the information given, is it possible to determine which of these two methods is performing more precisely ? What other information do we require ? RIT 2.2 Revision C

Coefficient of Variation..
The standard deviation does not take into consideration the magnitude of the overall results, which in this case are quite different. By calculating the coefficient of variation (%CV), which in effect expresses the SD as a percentage of the mean, it is possible to compare the precision of different sets of data. The lower the %CV the better the precision. A %CV takes into consideration the magnitude of the overall result. RIT 2.2 Revision C

Potassium %CV = (0.1 / 5.0) x 100% = 2.0%
Example: Potassium %CV = (0.1 / 5.0) x 100% = 2.0% Sodium %CV = (2.0 / 140) x 100% = 1.4% Assuming a mean of 5.0 mmol/L for potassium and a mean of 140 mmol/L for sodium, the CVs would be as follows: Thus although potassium has a smaller SD, sodium has the better CV and in this example, is performing better than potassium. Sodium has the better CV and in this example is performing better than potassium. RIT 2.2 Revision C

10  40 unacceptable performance
Interpretation.. 10  40 unacceptable performance 41  50 need for improvement 51  70 acceptable 71  good 101  excellent Target scores will range from 10 (very poor) through to 120 (excellent) and will allow laboratories to assess their performance at a glance. If the calculated Target Score is... < 10, the score is set to a minimum score of 10. > 120, the score is set to a maximum score of 120. RIQAS TRAINING MANUAL RIT 2.4 Revision E

V = (Result - Mean for Comparison) x 100
TS Calculations V = (Result - Mean for Comparison) x 100 Mean for Comparison The mean for comparison could be either: the all method mean your method mean your instrument mean A series of mathematical calculations are performed to generate a Target Score for each parameter analysed. Firstly the Variance (V) is calculated according to the above equation. This in effect, determines by what percentage your result deviates from the mean. Generally the instrument mean will be used. However at least 20 values are required to be statistically valid. If there is insufficient data, then your method mean will be used. Similarly if there are less than 20 values in this group, the all method mean will be used. RIQAS TRAINING MANUAL RIT 2.4 Revision E

TCV is Target Coefficient of Variation
TS Calculations TS = Log10 (3.16 x TCV) x 100 V The variance is then used to calculate the Target Score, as above, where the TCV is the Target Coefficient of Variation. TCV’s are determined for most analytes based on achievable performance standards. TCV’s are assigned over a five year period from the massive database of results generated by the various programmes. They are periodically reviewed. TCV is Target Coefficient of Variation RIQAS TRAINING MANUAL RIT 2.4 Revision E

TS Calculations TS = Log10 (3.16 x TCV) x 100 V
3.16 is selected as a constant because: the log10 of 3.16 is 0.5 so if V = TCV, then the target score will be 50 3.16 is selected as a constant because the log10 of 3.16 is 0.5. RIQAS TRAINING MANUAL RIT 2.4 Revision E

TS = log x TCV x 100 V = log x x 100 3.7 = log10 (3.16) x 100 = 50 As the calculation illustrates, if V equals or exceeds the Target Coefficient of Variation (TCV), then the target score will be 50 or less. This corresponds to the ‘unacceptable’ or ‘need for improvement’ zones. RIQAS TRAINING MANUAL RIT 2.4 Revision E

How can Analytical Quality be Controlled ?
So how can a laboratory control its analytical quality ? RIT 2.2 Revision C

Internal Quality Control (IQC).
daily monitoring of quality control sera External Quality Assessment (EQA). comparing of performance to other laboratories. Laboratories with good Quality Assurance Programmes will generally adopt two separate but complementary systems:- Firstly, Internal Quality Control (IQC) where analytical performance is monitored by analysing Quality Control Sera with known values, on a daily basis. Secondly, External Quality Assessment (EQA) where analytical performance is assessed by comparing the laboratory’s performance with that of other laboratories. RIT 2.2 Revision C

Internal Quality Control..
Daily monitoring precision accuracy Quality control sera results within control limits indicates that analytical system is running satisfactorily Internal Quality Control is essential for the daily monitoring of both precision and accuracy. Typically, at the beginning of each day, a laboratory will calibrate its instrument and then run a whole series of quality control sera at different concentration levels. When the results obtained fall within acceptable limits, it indicates that the analytical system is running satisfactorily. Only then will the laboratory be in a position to report reliable patient results. RIT 2.2 Revision C

A sodium control has a target value of 140 mmol/L
What is Acceptable ? A sodium control has a target value of 140 mmol/L 139 mmol/L 140 mmol/L 141 mmol/L 120 mmol/L 160 mmol/L 180 mmol/L Acceptable ! Unacceptable ! To do on this, we must decide what results should be rejected ! For example, consider a sodium control with a target value of 140 mmol/L. If we obtain results with this control of 139, 140 or 141 mmol/L, we could assume that being close to the assigned target that they probably would be acceptable. However at the other end of the scale results of 120, 160 or 180 mmol/L, would probably not be acceptable. So this obviously raises the question:- At what stage does a result become unacceptable ? RIT 2.2 Revision C

What is Acceptable ? A range of acceptable values is established
Sodium Control:  143mmol/L. Generally a range of acceptable values is established for a control sera. For example, our sodium control with its target value of 140 mmol/L, may have an acceptable range of 137  143 mmol/L. RIT 2.2 Revision C

What are the Options ? Unassayed serum: Assayed serum:
the cheaper option ! but the laboratory must establish its own ranges cannot be used to assess accuracy ! no externally assigned target values Assayed serum: with predetermined targets and ranges established by the manufacturer. How this range is established will depend on the type of quality control used. There are two types of serum that are commercially available:- Unassayed serum which is supplied with little or no information. This is a cheaper option but the laboratory must establish its own acceptable ranges and cannot be used to assess accuracy as it has no externally assigned target value. The other option is to use an assayed serum which has predetermined target values and ranges established by the manufacturer. RIT 2.2 Revision C

Unassayed Serum.. Analysed extensively by the laboratory.
a minimum of 20 sets of data generated a mean +/- 2SD range established 95% of results acceptable some laboratories may adopt tighter ranges If the laboratory is using an unassayed or precision serum, then it should be tested extensively to generate at least twenty sets of data for each parameter. From these collated results the mean and standard deviations are calculated which are then used to establish the acceptable ranges. Generally, a range based on the mean +/- 2SDs is used, remembering 95% or 19 out of every 20 results should statistically fall within this range. Some laboratories however may create tighter ranges based on perhaps +/- 1.5 or 1.75 SD’s. RIT 2.2 Revision C

Assayed Serum.. Targets and ranges generated by the manufacturer:
abc utilises RIQAS database of 5,000 laboratories method / instrument / temperature specific values If using an assayed quality control serum, an assigned target with an acceptable range is generally provided by the manufacturer. The accuracy of these assigned values is obviously critical if the laboratory is to objectively assess his own analytical performance. This will obviously be dependent on how the manufacturer conducts value assignment with the number and quality of those laboratories used an essential factor. At Randox we utilise a database of over 5,000 laboratories through their participation in our RIQAS EQA programmes. This huge volume of data allows us to establish not only highly accurate method values but also instrument and temperature specific values. RIT 2.2 Revision C

RIT 2.2 Revision C

Levey Jennings Chart +2SD 143 +1SD 141.5 Mean 140 -1SD 138.5 -2SD 137
X X X X X X Mean X 140 X X X X X X X A Levey Jennings Chart, is plotted with lines representing the mean and the SDs above and below, against a suitable time interval. Most laboratories will run a series of quality control sera, covering the full clinical range and not rely on a single control with only normal values. A chart will be established for each analyte and each level of control run. The values obtained are plotted on the chart allowing a rapid visual assessment of performance to be made. Remember, 68% of the results should statistically fall within 1 SD of the mean, and 95% should be within 2 SDs. Thus, it would be acceptable to see one result in every twenty outside the 2 SD limit. X -1SD 138.5 X X -2SD 137 RIT 2.2 Revision C

X X X X X Mean X 140 X X X X X X X X X Excellent performance with a nice tight grouping of results (good precision) with a random spread of results either side of the 140mmol/L target (good accuracy). X -1SD X 138.5 -2SD 137 RIT 2.2 Revision C

X X X X X X X X X Mean 140 X X X X X X X Both accuracy and precision are within acceptable limits, however there would perhaps be a tendency towards a slight positive bias over the last few results. X -1SD 138.5 -2SD 137 RIT 2.2 Revision C

X X X +1SD X 141.5 X X X X X X X X X X X X X Mean 140 Good precision but a definite positive bias – check calibration value or cuvette temperature. -1SD 138.5 -2SD 137 RIT 2.2 Revision C

X 143 X X X +1SD X 141.5 X X Mean 140 X X There is a definite downward trend – check reagent and control stability or the lamp. X X -1SD 138.5 X X X X -2SD 137 X X RIT 2.2 Revision C

X X X +1SD 141.5 X X X X X Mean X 140 X X X X Poor initial precision but note the dramatic improvement in performance perhaps following investigation. -1SD 138.5 X X X X -2SD 137 RIT 2.2 Revision C

X X X X X X X X X Mean 140 X X X X X X A distinct pattern evident – perhaps indicative of a change in shifts in a routine laboratory. X X -1SD 138.5 -2SD 137 RIT 2.2 Revision C

Westgard Rules.. Decision criteria is dependent on the precision of the method or analyser the less precise the method the more difficult the decision. Westgard provides multiple QC rules:- defines acceptability minimises false rejections maintains high error detection The interpretation of a Levey Jenning Chart takes time and experience. The decision to reject results often depends on the expected precision and accuracy of the methods and analyser systems being used. The less precise the method or analyser the more difficult the decision. In these circumstances, laboratories may decide to adopt external guidelines to help them reduce the incidences of false rejections yet at the same time maintain a high degree of error detection. A good example is provided by Westgard rules which are becoming more widely used. Westgard employs a multiple QC procedure to judge the acceptability of an analytical run. This is in contrast to the single rule procedure associated with a normal Levey Jennings Chart such as an acceptable range of +/- 2SD’s. RIT 2.2 Revision C

In control – report data Out of control – reject analytical run
Westgard Flowchart.. Control data 1 point outside 2 SD No In control – report data Yes No 1 point outside 3 SD No 2 consecutive values outside the same 2 SD No Difference between 2 controls within a run exceeds 4 SD 4 consecutive control values on one side of the mean and further than 1 SD from the mean 10 consecutive values on one side of the mean No No The selection of these rules is determined by the individual laboratory and can be set for each individual assay. Their aim should be to detect medically important errors at least 90% of the time. The rules will therefore flag warning results and also highlight danger results which would indicate that a particular run was invalid. Above we see how a laboratory might implement Westgard rules. Yes Yes Yes Yes Yes Out of control – reject analytical run RIT 2.2 Revision C

External Quality Assessment..
.. the main objective of EQA is not to bring about day to day consistency but to establish inter-laboratory comparability The main objective of external quality assessment is not to bring about day to day consistency but to establish inter-laboratory comparability. RIT 2.2 Revision C

EQA Options.. International / National / Regional
International schemes provide:- a larger database of results a wider range of analytical methods a global representation of diagnostic manufacturers Compulsory or Voluntary EQA options vary from one country to another. Schemes may be International, National or Regional. International Schemes such as RIQAS offer participants the advantages of :- a much larger database of results a wider range of analytical methods a global representation of manufacturer’s diagnostic kits Participation may be compulsory or voluntary. There is usually a subscription fee. RIT 2.2 Revision C

A Typical EQA Scheme.. Participants receive unknown samples.
these are analysed ‘blind’ the results returned to scheme organiser they are statistically analysed to generate a comparative report report sent to participant A typical EQA scheme provides the participating laboratories with a series of unknown samples. These samples are analysed ‘blind’ by the laboratory, in conjunction with their routine patient samples. However, rather than reporting the results to the clinician, they are returned to the scheme organiser. They are then subjected to statistical analysis, to generate a report, which is returned to the laboratory from which they can assess their performance with that of the other participants. RIT 2.2 Revision C

RIQAS abc International Quality Assessment Scheme Management tool
launched in 1988 5000 participants Management tool to assess, review and improve performance Since it’s launch in 1988, over 5,000 laboratories worldwide have joined the Randox International Quality Assessment Scheme or RIQAS. RIQAS provides a service, where by a laboratory manager can monitor his performance, in comparison with that of other laboratories. It provides an excellent management tool, enabling a laboratory to assess, review and improve, the precision and accuracy of the results they report. RIT 2.2 Revision C

RIQAS.. Annual subscription Weekly samples
two six monthly cycles Weekly samples one vial reconstituted per week tested blind as if a patient sample Results reported back to abc statistically analysed Weekly Report generated Each laboratory subscribes for one year, which represents two six monthly cycles. At the beginning of each cycle, the laboratory receives a RIQAS pack containing 26 vials of freeze-dried serum One vial for each week of the six month cycle. At the start of each week, the laboratory reconstitutes the appropriate vial of serum with water, and analyses it blind, as if it were a patient sample. The laboratory does not know what values to expect, but reports the results he obtains, each week, back to Randox. At Randox, the many thousands of results received each week are entered into a powerful computer, which in turn statistically assesses the data, to generate a weekly report. RIT 2.2 Revision C

RIT 2.2 Revision C

LABORATORY QUALITY CONTROL

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