Quality Assurance
Quality Assurance - Related Videos
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Quality Assurance
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2024
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
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Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement
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Cited by 1 •
2013
This paper describes in-house procedures of constructing a preclinical multimodality phantom made of tissue-mimicking (TM) materials for quality assurance (QA) of tumor size measurement in animal imaging modalities such as ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI).
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Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition
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2024
Here, we present a protocol for obtaining high-quality hyperpolarized xenon-129 magnetic resonance images, covering hardware, software, data acquisition, sequence selection, data management, k-space utilization, and noise analysis.
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Service Quality
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2024
Service quality is essential for customer satisfaction and loyalty. To effectively meet customer expectations, focus on aspects like tangibles, reliability, responsiveness, assurance, and empathy. Tangibles are the physical aspects of a service that customers interact with. For instance, the design and cleanliness of a hotel lobby or the professionalism of the staff's attire contribute to a customer's overall impression. A well-maintained environment and transparent, visually appealing...
01:05
Quality Control
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2024
Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results. Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
FAQs
Quality assurance operates at a broader level than a single quality-control check. Standardized protocols, documented workflows, equipment calibration, staff training, and validation create a controlled system, while quality-control samples provide practical evidence that an assay is behaving consistently. This distinction helps laboratories address sources of variation before data are reported, rather than discovering problems only during result review.
Validation establishes whether an immunoassay, molecular test, or microbial culture performs as intended under specified conditions. Routine monitoring then checks whether that expected performance remains stable during ongoing work. Together, these activities connect initial confidence in a procedure with continued oversight, helping laboratories recognize departures from expected performance before they compromise reported results.
Equipment calibration and staff training control two different sources of variation. Calibration addresses whether instruments operate according to defined expectations, whereas training supports consistent execution of documented procedures. Combined with standardized workflows, these controls make it easier to distinguish assay-related variation from procedural inconsistency, improving the accuracy and consistency of results in immunology and infection research.
Defined standards give laboratories a reference for judging whether procedures and results are acceptable. In immunology and infection research, that reference supports consistent handling of immunoassays, molecular tests, and microbial cultures, making results easier to evaluate for accuracy and reliability. Documented expectations also strengthen reproducibility by allowing workflows and outcomes to be compared over time.
An implementation sequence can begin by setting standards and documenting the workflow, followed by staff training and equipment calibration. The laboratory can then validate the assay under specified conditions, use quality-control samples during routine work, and monitor performance before reporting results. This sequence creates checkpoints where variation or error can be identified and addressed.
Quality-control samples act as practical checks on assay performance. Their results can reveal variation or error while testing is still in progress, allowing the laboratory to evaluate performance before releasing data. In immunology and infection work, this safeguard applies across immunoassays, molecular tests, and microbial cultures, supporting more consistent and reliable results under defined laboratory conditions.
Within immunology and infection, quality assurance supports diagnostic testing, vaccine and therapeutic evaluation, biosafety practices, and research findings. Its value extends beyond the assay itself because reliable laboratory results can support sound decisions in clinical and public health settings. The framework therefore links technical performance with confidence in conclusions and actions based on those results.