Quality assurance analytical errors

The "feedback loop in the analytical approach is maintained by a quality assurance program (Figure 15.1), whose objective is to control systematic and random sources of error.The underlying assumption of a quality assurance program is that results obtained when an analytical system is in statistical control are free of bias and are characterized by well-defined confidence intervals. When used properly, a quality assurance program identifies the practices necessary to bring a system into statistical control, allows us to determine if the system remains in statistical control, and suggests a course of corrective action when the system has fallen out of statistical control. 

In the previous section we described several internal methods of quality assessment that provide quantitative estimates of the systematic and random errors present in an analytical system. Now we turn our attention to how this numerical information is incorporated into the written directives of a complete quality assurance program. Two approaches to developing quality assurance programs have been described a prescriptive approach, in which an exact method of quality assessment is prescribed and a performance-based approach, in which any form of quality assessment is acceptable, provided that an acceptable level of statistical control can be demonstrated. 

Since many ion exchange columns exhibit mixed-mode interactions with analytes, factor analysis has been found to be useful in optimization.84 A 3-year, comprehensive review of inter-laboratory errors in determinations of the anions chloride, nitrate, and sulfate and the cations sodium, potassium, magnesium, and calcium suggested that multipoint calibration is essential and nonlinear calibration desirable.102 The need for nonlinear calibration was confirmed by an extended quality assurance study of chloride, sulfate, and nitrate in rainwater.103... 

In analytical practice, they are best recognized by the determination of xtest as a function of the true value xtrue, and thus, by analysis of certified reference materials (CRMs). If such standards are not available the use of an independent analytical method or a balancing study may provide information on systematic errors (Doerffel et al. [1994] Kaiser [1971]). In simple cases, it may be possible, to estimate the parameters a, / , and y, in Eq. (4.5) by eliminating the unknown true value through appropriate variation of the weight of the test portions or standard additions to the test sample. But in the framework of quality assurance, the use of reference materials is indispensable for validation of analytical methods. 

As in many such problems, some form of pretreatment of the data is warranted. In all applications discussed here, the analytical data either have been untreated or have been normalized to relative concentration of each peak in the sample. Quality Assurance. Principal components analysis can be used to detect large sample differences that may be due to instrument error, noise, etc. This is illustrated by using samples 17-20 in Appendix I (Figure 6). These samples are replicate assays of a 1 1 1 1 mixture of the standard Aroclors. Fitting these data for the four samples to a 2-component model and plotting the two first principal components (Theta 1 and Theta 2 [scores] in... 

Define Quality Control, Quality Assurance, sample, analyte, validation study, accuracy, precision, bias, calibration, calibration curve, systematic error, determinate error, random error, indeterminate error, and outlier. 

Sets of instructions that detail the procedures designed to reduce errors occurring during analytical procedures and ensure accurate quantitations are found in the quality assurance (QA) and quality control (QC) manuals. Quality assurance procedures are used by the laboratory to detect and correct problems in analytical processes. As newer methods and instrumentation are added to the laboratory, older procedures must be modified or changed completely. Quality control procedures are used to maintain a measurement system (i.e., a gas chromatograph) in a statistically satisfactory state to ensure the production of accurate and reliable data. 

Quality assurance (QA) is an essential part of analytical protocols. Each laboratory is required to detect and correct problems in analytical processes and to reduce errors to agreed-upon limits. To produce data that have acceptable quality, all laboratory members must follow established guidelines and protocols. Some of the essential elements that must be included in a QA program are as follows ... 

Two elements of quality assurance are quality control and quality assessment. Quality control is a set of measures implemented within an analytical procedure to assure that the process is in control. A combination of these measures constitutes the laboratory QC program. A properly designed and executed QC program will result in a measurement system operating in a state of statistical control, which means that errors have been reduced to acceptable levels. An effective QC program includes the following elements ... 

Once the retesting protocol is executed successfully (i.e., no analytical deviations), the results will either support the OOS result and confirm a material failure or render the OOS result invalid and provide ample justification to pass the test specifications. If the OOS result is confirmed, the batch is rejected and the quality assurance department should take appropriate steps for batch disposal. Since confirmation of the OOS result strongly suggests an operator-related or process-related error, the onus is now placed on the formal or phase II investigation participants to identify a cause. If an operator-related error is found and batch rework is possible and prescribed in an approved batch record and approved regulatory submission, this may be the desired course of action. If no rework or reprocessing is possible, the batch is rejected and disposed of in an acceptable manner. 

As mentioned earlier, the complete analytical process involves sampling, sample preservation, sample preparation, and finally, analysis. The purpose of quality assurance (QA) and quality control (QC) is to monitor, measure, and keep the systematic and random errors under control. QA/QC measures are necessary during sampling, sample preparation, and analysis. It has been stated that sample preparation is usually the major source of variability in a measurement process. Consequently, the QA/QC during this step is of utmost importance. The discussion here centers on QC during sample preparation. 

For any analytical program selected, an appropriate quality assurance program must be implemented to minimize errors during the sampling and analysis process. The Federal Register contains the appropriate procedures for US EPA priority pollutants. 

Figure 19-11 Operating specifications chart for an analytical quality requirement of 10% (T o) and 90% analytical quality assurance for systematic error. Allowable inaccuracy is plotted on the y-axis versus allowable imprecision on the x-axis.

Quality assurance of blood analysis for gases and pH is dependent on control of preanaiytical error (i.e., on proper collection and handling of the specimen) and on control of the analytical instrument and testing process. Because laboratory personnel do not always control collection of arterial... 

Unfortunately, there is no simple and widely applicable method for determining the reliability of data with absolute certainty. Often, estimating the quality of experimented results reejuires as much effort as collecting the data. Reliability can be assessed in several wa vs. Experiments designed to reveal the presence of errors can be peiformed. Standards of known composition can be analyzed and the results compared with the known composition. A few minutes in the library to consult the chemical literature can be profitable. Calibrating equipment usually enhances the quality of data. Finally, statistical tests can be applied to the data. Because none of these options is perfect, we must ultimately make judgments as to the probable accuracy of our results. These judgments tend to become harsher and less optimistic with experience. The quality assurance of analytical methods and the ways to validate and report results are further discussed in Section 8D-3. 

External quality assurance (EQA) is fundamental to the standardization of clinical laboratory methods because it provides a means to compare results generated in one laboratory with those of peer laboratories subscribing to the same EQA program. EQA programs are especially beneficial since internal QA and QC procedures are limited in their ability to detect bias in analytical methods. Internal QA/QC can only detect errors that result in a deviation from the original method validation inherent errors in the method may go unnoticed. Therefore, it is helpful to compare the results produced by a new method with those from other laboratories (Burtis and Ashwood, 2001). Monitoring the performance of laboratory procedures in a consistent manner keeps the laboratory accountable, and can reveal systematic errors that would otherwise be undetected. A prominent component of EQA is proficiency testing. 

Because of the risk of analytical errors, it is crucial that every laboratory runs and reports a quality assurance program (cf. Friberg, 1988). This should include both internal and external quality control. The internal quality control procedure should include, in each analytical series, a sufficient number of samples with the same matrix as the study samples, and with a relevant mercury concentration. The results obtained are compared with pre-defined levels of acceptability. The external quality control may be assessed by inter-laboratory exchange of samples with (to the iaboratory) unknown concentrations, and by analysis of reference samples with well-defined levels. 

Recently, few topics in analytical chemistry have occupied the scientific community more than the ability of chemical laboratories to reliably determine at the low parts-per-billion level the presence of Fusarium trichothecenes in environmental and toxicological samples. This paper provides a systematic approach for developing and implementing a quality assurance and quality control program for a complex analytical method in which human error and system failure can occur. The application of this approach to the problem of determining the presence of nine naturally... 

Analytical methodology was developed for accurate quantitative analysis of trichothecenes at low part-per-billion levels in blood. Although this methodology was arduous and lacked the ruggedness normally demanded of an analytical procedure which must nave a low failure rates it proved to be both qualitatively reliable and quantitatively accurate when it was combined with a well planned quality assurance program. An indispensable part of developing the quality assurance plan was a formal risk assessment which specifically took into account the possibility of human error. 

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