Thanks to Melanie Kim from Texas for explaining to me the concept of Quality Control in Laboratory Operations.
Laboratory quality control is designed to detect, reduce, and correct deficiencies in a laboratory’s internal analytical process prior to the release of patient results, in order to improve the quality of the results reported by the laboratory. Quality control is a measure of precision, or how well the measurement system reproduces the same result over time and under varying operating conditions.
Laboratory quality control material is usually run at the beginning of each shift, after an instrument is serviced, when reagent lots are changed, after calibration, and whenever patient results seem inappropriate.Quality control material should approximate the same matrix as patient specimens, taking into account properties such as viscosity, turbidity, composition, and color. It should be simple to use, with minimal vial to vial variability, because variability could be misinterpreted as systematic error in the method or instrument. It should be stable for long periods of time, and available in large enough quantities for a single batch to last at least one year. Liquid controls are more convenient than lyophilized controls because they do not have to be reconstituted minimizing pipetting error.
Interpretation of quality control data involves both graphical and statistical methods. Quality control data is most easily visualized using a Levey-Jennings Chart. The dates of analyses are plotted along the X-axis and control values are plotted on the Y-axis. The mean and one, two, and three standard deviation limits are also marked on the Y-axis. Inspecting the pattern of plotted points provides a simple way to detect increased random error and shifts or trends in calibration
Levey-Jennings chart is a graph that QC data is plotted on to give a visual indication whether a laboratory test is working well.The distance from the mean is measured in standard deviations (SD). It is named after S. Levey and E. R. Jennings who in 1950 suggested the use of Control Chart in the clinical laboratory. On the x-axis the date and time, or more usually the number of the control run, are plotted. A mark is made indicating how far away the actual result was from the mean (which is the expected value for the control). Lines run across the graph at the mean, as well as one, two and three standard deviations to either side of the mean. This makes it easy to see how far off the result was.
Rules, such as theWestgard Rule can be applied to see whether the results from the samples when the control was done can be released, or if they need to be rerun. The formulation of Westgard rules were based on statistical methods. Westgard rules are commonly used to analyse data in Shewhart control charts. Westgard rules are used to define specific performance limits for a particular assay and can be used to detect both random and systematic errors. Westgard rules are programmed in to automated analyzers to determine when an analytical run should be rejected.
These rules need to be applied carefully so that true errors are detected while false rejections are minimized. The rules applied to high volume chemistry and hematology instruments should produce low false rejection rates.
The Levey-Jennings chart differs from the Shewhart individuals control chart in the way that sigma, the standard deviation, is estimated. The Levey-Jennings chart uses the long-term (i.e., population) estimate of sigma whereas the Shewhart chart uses the short-term (i.e., within the rational subgroup) estimate.
What stuffs I need to know from Lab Operations and QC for ASCP? Read the description below.
Controls= Assayed and Unassayed
Youden Plot for?
Levey-Jennings= know Westgard Multi Rules
Know some common Maths like Molarity, Dilution,
Know about Lab Safety like Fire safety, Radiation sign, Bio Hazard sign, Fire extinguisher classes, Biological safety Cabinets, Accrediated Agencies.
KNow just the principles of Instrumentation, All you need to know the basic idea about instrument, just 2-3 lines—> Spectrotophotometry(stary light and filetr?)= for example this method measures light in a Narrow Wavelength Range.
|1.||Accuracy||*Percentage of correct diagnoses
*Total Correct Scans/Total # of Studies
*Accuracy= TP=TN/ALL Scans
(note ALL Scans are TP+FP+FN+TN)
|2.||False Negative||(for example: cutting off the wrong leg)
Scan disagree with gold standard
-Gold standard abnormal
|3.||False Positives||(for example: taking medicine you don’t need)
Scans disagree with gold standard
-Gold standard normal
|4.||Negative Predictive Value||*Percentage of scans that accurately predict normality
(note ALL negatives are TN +FN)
|5.||Positive Predictive Values||*Percentage of scans that accurately predict abnormality
(note ALL positives are TP + FP)
|6.||QA Statistics||* Compare your exam to the gold standard or reference test
* Calculated values verify
-Quality of your exams
-Limitations of your lab
*Identify patients with disease
Sensitivity = A/A+C
*Identify patients without disease
Specificity = D/B+D
|9.||Test Validation and Statistics||* Sensitivity
*Positive Predictive Value
*Negative Predictive Value
|10.||True Negative||(Normal or No Pathology)
Your scans and the gold standard agree
|11.||True Positives||(Finding the presence of disease)
Your scans and the gold standard agree