Analytical procedure quality control chart

The underlying calibration procedure of a newly developed analytical method has to be examined by basic validation studies to determine the reliability of the method and its efficiency in comparison with traditional methods. In order to ensure long-term stability, it is necessary to perform revalidations, which can be combined with the use of quality control charts, over meaningful time periods. 

Note This experiment assumes that a permanent log and a quality control chart are constantly maintained for each analytical balance in use in the laboratory. Each day you use a given analytical balance and log in with your name and date. The following calibration check should be performed weekly on all balances. If, according to the log, the calibration of the balance you want to use has not been checked in over a week, perform this procedure. Review Section 3.3 for basic information concerning the analytical balance. 

A quality control chart is a visual aid for determining whether a given analytical result is outside the action limits determined for the results for that procedure. If it is outside the action limits, the cause may be a problem with the procedure, among other things. 

To monitor test procedures or to ensure the quality of products and processes by using analytical methods, quahty control charts have proven their success. There, a quahty characteristic is recorded at given spacing in a chart enabling ready recognition of typical situations (Figure 9.1). 

Analytical laboratories, especially quality assurance laboratories, will often maintain graphical records of statistical control so that scientists and technicians can note the history of the device, procedure, process, or method at a glance. The graphical record is called a control chart and is maintained on a regular basis, such as daily. It is a graph of the numerical value on the y-axis vs. the date on the x-axis. The chart is characterized by five horizontal lines designating the five numerical values that are important for statistical control. One is the value that is 3 standard deviations from the most desirable value on the positive side. Another is the value that is 3 standard deviations from the most desirable value on the negative side. These represent those values that are expected to occur only less than 0.3% of the time. These two numerical values are called the action limits because one point outside these limits is cause for action to be taken. 

Analytical method validation forms the first level of QA in the laboratory. Analytical quality assurance (AQA) is the complete set of measures a laboratory must undertake to ensure that it is able to achieve high-quality data continuously. Besides the use of validation and/or standardized methods, these measures are effective IQC procedures (use of reference materials, control charts, etc.), with participation in proficiency testing schemes and accreditation to an international standard, normally ISO/IEC 17025 [4]. Method validation and the different aspects of QA form the subject of Section 8.2.3. 

The laboratory quality control program has several components documentation of standard operating procedures for all analytical methods, periodic determination of method detection levels for the analytes, preparation of standard calibration curves and daily check of calibration standards, analysis of reagent blank, instrument performance check, determination of precision and accuracy of analysis, and preparation of control charts. Determination of precision and accuracy of analysis and method detection limits are described under separate subheadings in the following sections. The other components of the quality control plan are briefly discussed below. 

Samples can be divided into two aliquots and analyzed, and the duplicates used for control purposes. This is a simple quality control procedure that does not require stable control materials and therefore can be used when stable materials are not available or as a supplemental procedure when stable control materials are available. The differences between duplicates are plotted on a range type of control chart that has limits calculated from the standard deviation of the differences. When the duplicates are obtained from the same method, this range chart monitors only random error and thus is not adequate for ensuring the accuracy of the analytical method. When the duplicates are obtained from two different laboratory methods, then the range chart actually monitors both random and systematic errors but cannot separate the two types of errors. The interpretation becomes more difficult, particularly when there are stable systematic differences or biases between the two analytical methods. Multiplicative factors may be necessary to deal with proportional differences, and additive factors may be necessary to allow for constant differences. Interpretation of observed differences becomes more qualitative nevertheless, this procedure still provides a useful way of monitoring the consistency of the data being generated by the laboratory. 

Quality control (QC) refers to the operational techniques and activities that are used to fulfill requirements for quality. Internal quality control comprises the routine practical procedures that enable the analytical chemist to make a decision on whether to accept a result or a group of results as fit for purpose, or reject them and repeat the analysis. Tools for quality control include the use of reference standards and certified reference materials, the use of positive (spiked or incurred) and negative control samples and control charts, replicate analyses, and proficiency tests. Quality control in the laboratory is discussed in more detail in Section 10.5 of this chapter. 

There are other routinely practiced procedures in terms of intralaboratory and interlaboratory quality control, such as the control chart, round-robin interlaboratory testing, and various proficiency tests offered by different agencies, such as the PATs (Proficiency Analytical Testing) by AHA in the US and WASPs (Workplace Analysis Scheme for Proficiency) by the Health and Safety Laboratory in Great Britain. In normal circumstances, a combination of these quality control measures should be used in performing workplace air analysis. 

Quality control includes such procedures as checking for proper identification of samples, checking reagent lot numbers and utilities, etc. Control charts should be maintained for both equipment as well as analytical procedure by measurement of QC samples [16]. These are typical samples of sufficient stability and quantity to be used for analytical purposes over a continued period of time. For routine measurement, the number of QC samples should be at least one of twenty samples for analysis, and for more complicated analytical procedures the number of QC samples occasionally increases to 1 1. For infrequent analytical procedures, e.g., in research, a validation of the method should be performed at all runs, and this should also include the use of certified reference materials (CRM) when suitable ones are available. 

The quality of the analytical work cannot be maintained without adequate quality control (QC) procedures. The meaning of the term quality control often varies according to context. In general QC is the overall system of activities used to fulfill requirements for documentation of quality. The system should be satisfactory, adequate, dependable, and economic. Examples of quality control are control charts, blank determination, blind samples, and repetitive determinations. The number of test results to be obtained from the analysis of each sample is related to the purpose of the analytical work. As guidance for QC purposes, it is necessary to analyze at least one sample in duplicate in every 10 determinations of the analyte. 

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