Quality control is a critical element in laboratory monitoring that helps ensure product integrity and process accuracy. Without quality control procedures in the laboratory, there may be no means of determining whether a product or process meets regulatory standards.
Laboratories are often sensitive facilities that demand high regard for accuracy in all processes. For example, a medical lab may conduct tests on human samples to establish pathological anomalies to ultimately inform a doctor's prognosis for a patient. As such, it is of utmost importance that reagents used in the laboratory are of the right concentration and quantity.
The process itself necessitates documentation to prevent variations that may induce errors. Without proper quality control in the laboratory, the outputs may likely be erroneous.
In a worse case scenario, misleading information may be provided to a doctor who may then prescribe a fatal medication to a patient. The same applies to pharmaceutical labs, where experts manufacture medicines and vaccines.
The nature of products used and produced in the labs often necessitates stringent control measures. There must be a quality control program to validate the accuracy of the production process and ensure it meets regulatory standards.
The scope of quality control includes system and process efficiency. One can maximize a lab's productivity by having the means to control quality by minimizing waste.
Without quality control procedures in the laboratory, there is no means of determining whether a product or process meets regulatory standards.
The concept of quality control began in the early 20th century, where the first guidelines for statistical control were applied to production lines. Early on, quality control experts realized the fallacy of focusing only on the product and ignoring the process.
The first proponents of quality control advocated for the inclusion of the process in all quality control procedures to achieve better outcomes. ELPRO solutions help enable companies to carry on that quality control tradition in laboratories worldwide.
In the 1950s, Levey and Jennings introduced quality control in the medical laboratory. At a basic level, the procedure involved multiple measurements on a single patient’s sample.
Although the mean showed significant variations from patient to patient, the range offered a more reliable precise measurement. As time went on, quality control in the laboratory developed to become increasingly important. Modern methods provide more accurate results and offer sophisticated techniques for analysis and interpretation.
The Science of Quality Control in the Laboratory
In a broader sense, quality control is a means to ensure that the product quality remains the same or improves. It denotes the construction of control protocols to standardize production processes to achieve consistent quality outputs.
The laboratory's quality control seeks to streamline lab processes and set control measures to detect and rectify discrepancies. The end goal is to minimize errors, which consequently ensures improved results quality.
In that regard, quality control is a measure of precision. It determines how consistent a system is in producing accurate results under varying conditions.
Quality control processes in a laboratory are often conducted at the beginning of every shift as staff interchange. It is also essential to run quality checks after equipment undergoes service or calibration before putting it back into service. This helps determine accurate results before entrusting the equipment to patient use.
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Detailed analysis can help determine how close output is to an expected value. The precision value determines how consistently the instrument can reproduce the same value, for the same test sample, under the same test conditions.
Quality control and quality assurance are both part of quality management. However, they differ in purpose and application. Quality assurance puts in place mechanisms and systems to instill confidence in management and stakeholders that the output will fulfill all requirements. However, quality control has to do more with inspection, to determine compliance with quality requirements.
A few elements are mandatory for an excellent quality control system. The system must be easy to use and reproduce over many groups of control samples. It must also have minimal vial-to-vial variations. If not, these discrepancies will appear as systemic errors arising from the measurement system. Moreover, its stability should be dependable for extended periods and not susceptible to interferences in the short term.
There are two main methods that one can employ in laboratory quality control.
The first is product inspection, where the focus is on both the process and the product. That means checking the product for any defects and compliance with the set regulatory standards.
A lab process is a sequence of steps undertaken to produce a desired output from raw material. Process inspection includes checking whether the equipment and materials meet set standards for a particular procedure.
Apart from inspection, there is another quality control method known as statistical quality control. It is a more advanced technique that employs statistical inferences, including probability and sampling, to control product quality.
To conduct statistical quality control, one must first identify the universe from which one will use an appropriate sampling technique to carve out a sample population. Study and analysis of the sample population will provide the results to generalize for the entire study group. Control charts can be used to analyze results and determine the correct remedial steps.
Quality Control Calculations
Before one can embark on any quality control calculations, there is a need to have 20 sample measurements over a minimum of 10 working days. However, a longer time is better since a study period will often cover more method changes.
To get the mean, one must find the summation of all measured values and divide that value by the total number of measurements. A scientific calculator with a mean determining function can be used for a small range of samples.
For larger data sets, statistical programs like SPSS and SAS will work better. Since the mean relates to accuracy and indicates the central tendency, one can determine systematic drifts by observing a change in the mean value when the distribution of the control results shifts.
The standard deviation is also a critical calculation in quality control in the laboratory. Find the difference between each control result and the mean value, square it, and divide by n-1, where ‘n’ refers to the number of control samples. This value's square root gives the standard deviation, which provides the results' distribution about the expected mean value.
The standard deviation describes the distribution width and thereby denotes the precision. Under normal circumstances, one can expect a Gaussian distribution that is easily predictable. The disadvantage with the standard deviation measurement is that it changes with concentration.
You can use the Coefficient of Variation value that describes the standard deviation as a percentage of the mean to avoid this. The Coefficient of Variation provides a more accurate performance estimate over variable concentrations of control values.
Quality control in laboratories is a crucial element that cannot be overlooked. It is necessary to apply it to both the product and process to improve productivity and maintain product quality.
Every accredited lab should invest in a quality control plan and promote a culture of mandatory compliance to it. Additionally, regular audits to keep the plan in line with the latest standards are also necessary.