ABC of Quality Control A problem based approach RT ERASMUS NHLS / FACULTY OF HEALTH SCIENCES, UNIVERSITY OF STELLENBOSCH 20th July, 2007, Bela Bela

1.What is quality control?

It is a statistical process used to monitor and evaluate the analytical process which produces patient results. The statistical process requires regular testing of quality control products along with patient samples comparison of quality control results to specific statistical limit (ranges).QC results are used to validate patient results and requires testing normal and abnormal controls for each test at least daily to monitor the analytical process. Regular QC testing creates a QC database. Validation occurs by comparing daily QC results to a laboratory defined range of QC values.

Calculate the control mean values of the following: Normal control Test : creatine kinase Control values are: 94, 93, 97, 95, 95, 100, 99, 100, 99, 100 What does the mean value for these control values reflect ?

2.The mean and standard deviation are the most fundamental statistics used by the laboratory. The QC statistics for each test performed in the laboratory are calculated from the QC database collected by regular testing of control products. Consequently the mean level of the control reflects the behaviour of the test at that specific concentration.

3. Calculate mean and standard deviation of the following control values obtained for potassium over several days What do you understand by the results obtained ? What do you understand by the term “standard deviation” ? What is the standard deviation used for?

S.D S=√∑ (x n - х) 2 n-1 ∑ (x n - х) 2= the sum of squares of differences between individual QC values and the mean n =number of values in the data set х=28.7 mmol/L ÷ 7 = 4.1 _______________________________________________ S=√ (4.0 – 4.1)2 + (4.1 – 4.1)2 + (4.0 – 4.1)2 + (4.2 – 4.1)2 + (4.1 – 4.1)2 + (4.1 – 4.1)2 + (4.2 – 4.1)2 __________________________________________ 6

S=√ (– 0.1)2 + (0.0)2 + (-0.1)2 + (0.1)2 + (0)2 + (0)2 + (0.1)2 ___________________________ 6 __________ S=√ (0.04 ÷ 6)=0.082 or 0.1 This type of S.D is called between run standard deviation b/c data used to calculate the statistics came from different analytical runs. Standard deviation indicates the dispersion or spread of values. The bigger the value, the greater the imprecision.Standard deviation can be used for (A) evaluating method performance (i.e. b/w run and within run precision) (B) instrument evaluations (C) comparing performance with other laboratories using the same instrument (D) monitor on going day to day performance

Create a Levey-Jennings for the following control values obtained on each day for serum creatine kinase. 327, 325, 321, 323, 315, 308, 304, 298, 327, 334 The mean value of the control is 350 U/L with a standard deviation of 25 U/L.

S.D is commonly used for preparing a Levey-Jennings Chart. The chart is used to graph successive day to day quality control values. Step 1 :Calculate decision limits. These limits are + 1s, + 2s, + 3s from the mean Step 2 : The control limits of serum creatine kinase are + 1s =350 – 25 = = s = 350 – (25) (2) = (25) (2) = s = 350 – (25) (3) = (25) (3) = 425

When an analytical process is within control, approximately 68% of all QC values fall within + 1 standard deviation. Likewise 95.5% of all QC values fall within +2 standard deviations (2s) of the mean. About 4.5% of all data will be outside the +2s limits when the analytical process is in control. Approximately 99.7% of all QC values are found to be within +3 standard deviations of the mean. As only 0.3% or 3 out of 1000 points will fall outside the +3s limits any value outside of +3s is considered to be associated with a significant error condition and patient results should not be reported. Some laboratories incorrectly consider any quality control value outside its +2s limits to be out of control, as approximately 4.5% of all valid QC values will fall somewhere between +2 and +3 standard deviations limits. Laboratories using +2s control limits frequently reject good runs.

5. How do you use the Levy-Jennings Chart to evaluate run quality?

Once the QC data have been plotted on the chart search for (a)systematic error (b)random error Systematic error is evidenced by a change in the mean of the control value. The change may be gradual and seen as a trend, or may be abrupt and seen as a shift. Trend Usually subtle. Causes are weakening light source gradual accumulation of debris in reagent tubing or on electrode surface aging of reagents gradual breakdown of control materials gradual loss of temperature control gradual loss of filter integrity

Shifts Abrupt changes in control mean. Signifies a sudden positive or negative change in test system performance. May be caused by sudden failure of light source change in reagent lot / formulation sudden change in incubation temperature or room temperature/ humidity failure in reagent dispensing or sampling inaccurate recalibration Random Errors : Any +ve or –ve deviation away from calculated mean can be classified as acceptable or unacceptable. Unacceptable random error is when any data point is outside +3S.D.

WESTGARD RULES These are quality control rules developed by Dr James Westgard in Most rules are expressed as NL, where N represents the number of control observations. Thus 1 3s represents a control rule which is violated when one control observation exceeds the +3s control limits. 1 2s Warning rule (single observation outside +2s) Warns that random or systematic error may be present Examine this with other previous values If no source of error found, it is assumed that it is an acceptable random error. Violation of following rules results in rejection of entire run. 1 3s :Identifies unacceptable random error or beginning of a large systematic error. 2 2s :Identifies systematic error only.Two consecutive QC results greater than 2s on the same side of the mean

R 4s Identifies random error only and is applied only within the current run Implies a 4s difference between control values within a single run. e.g. in a run, 2 controls (low and high) are used. Level 1 is + 2.8s above mean and level 2 is –1.3. Total difference is 4.1s. Violation of following rules does not necessarily require rejection of analytical run. They usually identify smaller systematic error, which is often not clinically significant. Can be eliminated by instrument maintenance or calibration. 3 ls : 3 consecutive results greater than ls on the same side as the mean Two applications to 3 ls and 4 ls rule. These are within control material or across control materials.

6. (a) What do you understand by C.V (b) How does it differ from S.D (c) What function does it serve in laboratory statistics

6.Coefficient of Variation (C.V) Is the ratio of standard deviation to the mean and is expressed as a percentage. Allows for easier comparison of the overall precision. Because S.D increases with analyte concentration, C.V is regarded as a statistical equalizer. C.V can also be used when comparing instrument performance. In practice CV is used for method comparison over different levels of controls which may be used to identify method performance over varying analyte ranges.