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15: Quality Assurance

Last updated

Sep 12, 2021
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- 14.7: Chapter Summary and Key Terms
- 15.1: The Analytical Perspective Revisited

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In Chapter 14 we discussed the process of developing a standard method, including optimizing the experimental procedure, verifying that the method produces acceptable precision and accuracy in the hands of a signal analyst, and validating the method for general use by the broader analytical community. Knowing that a method meets suitable standards is important if we are to have confidence in our results. Even so, using a standard method does not guarantee that the result of an analysis is acceptable. In this chapter we introduce the quality assurance procedures used in industry and government labs for the real-time monitoring of routine chemical analyses.

15.1: The Analytical Perspective Revisited
The page discusses the analytical approach in chemistry, highlighting the problem-solving process and the importance of feedback loops in improving analytical methods. It emphasizes the role of quality assurance programs in controlling systematic and random errors, ensuring results are unbiased and within defined confidence intervals.
15.2: Quality Control
Quality control in laboratories involves activities that ensure analyses are in statistical control, primarily through written directives that guide various operations. Good laboratory practices (GLPs) outline general operations such as data recording, reagent preparation, and equipment maintenance. Good measurement practices (GMPs) focus on equipment use and calibration specific to techniques. Standard operations procedures (SOPs) provide detailed instructions for analyzing specific analytes.
15.3: Quality Assessment
The text explains that quality control directives are crucial for analysis but not enough to ensure statistical control, which is managed by quality assessment???a key part of quality assurance. Quality assessment helps maintain, detect, and suggest solutions for loss of statistical control. It includes internal methods, like analyzing duplicate samples and spikes, and external methods, such as laboratory certification by an agency.
15.4: Evaluating Quality Assurance Data
The text discusses two approaches to developing a quality assurance program in analytical chemistry: the prescriptive approach and the performance-based approach. The prescriptive approach involves a strict protocol for quality assessment, often required by regulatory agencies, while the performance-based approach allows laboratories flexibility, using control charts to monitor statistical control. Control charts help detect errors, ensuring precision and accuracy in analysis.
15.5: Problems
This page contains instructions related to various analytical chemistry tasks and practices, including developing lab guidelines, conducting specific measurements, analyzing limits of detection, calculating statistical values such as standard deviations, creating control charts, and evaluating spike recoveries.
15.6: Additional Resources
This page lists various resources related to quality assurance and quality control in chemical research and analysis. The resources include journal articles discussing the integration of QA/QC into quantitative analysis, environmental analytical chemistry, undergraduate research, quantitative analysis, and bioanalytical experiments.
15.7: Chapter Summary and Key Terms
The page discusses the importance of quality assurance programs in analytical work to ensure high-quality results. It distinguishes between quality control, which involves bringing a system into statistical control through documentation and good practices, and quality assessment, which uses statistical tools to evaluate whether an analysis is under control and identify potential issues.

Thumbnail: Examples of property control charts that show a sequence of results.

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