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Related Concept Videos

Quality Control01:05

Quality Control

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...
Quality Assurance01:19

Quality Assurance

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...
Good Manufacturing Practices01:26

Good Manufacturing Practices

Good Manufacturing Practices (GMP) constitute a foundational set of guidelines that ensure the production of safe, consistent, and high-quality products, particularly in industries such as pharmaceuticals, biotechnology, and food processing. These protocols encompass all aspects of production, from the sourcing of raw materials to the final distribution of the finished product.A core pillar of GMP is stringent hygiene and sanitation across all production environments. This includes routine...
Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
Control Systems01:10

Control Systems

Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
The X̄ Chart00:58

The X̄ Chart

The  x̄ chart is a statistical tool for monitoring the means in a process.
The x̄ chart, often known as the individual control chart, is a crucial tool in statistical process control. It is designed to monitor process behavior and performance over time and is widely used in various industries to ensure that processes are operating at their optimum capacity and within specified limits.
A x̄ chart is constructed by plotting individual measurements of a quality characteristic in the order in which...

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Related Experiment Video

Updated: Jul 4, 2026

Microbial Control and Monitoring Strategies for Cleanroom Environments and Cellular Therapies
09:30

Microbial Control and Monitoring Strategies for Cleanroom Environments and Cellular Therapies

Published on: March 17, 2023

Quality leadership and quality control.

Tony Badrick1

  • 1Sullivan Nicolaides Pathology, Brisbane Laboratory, Indooroopilly, QLD, Australia. Tony_Badrick@snp.com.au

The Clinical Biochemist. Reviews
|June 24, 2008
PubMed
Summary

Effective laboratory quality control requires understanding how different rules detect errors and implementing robust troubleshooting. Defining acceptable error based on biological variation and strong leadership are crucial for optimal performance.

Area of Science:

  • Clinical Chemistry
  • Laboratory Medicine
  • Quality Management Systems

Background:

  • Quality control (QC) rules vary in their efficiency for detecting analytical errors based on error type, prevalence, and sample size.
  • QC rules are insufficient alone; effective troubleshooting systems are equally vital for process integrity.
  • Conventional serum-based QC programs can be augmented by methods like 'Average of Patient Normals'.

Purpose of the Study:

  • To analyze the efficiency of different quality control rules in detecting analytical errors.
  • To emphasize the importance of troubleshooting systems alongside QC rules.
  • To explore the integration of acceptable error criteria, such as biological variation, into QC systems.

Main Methods:

  • Evaluation of quality control rule efficiency using power function graphs.

Related Experiment Videos

Last Updated: Jul 4, 2026

Microbial Control and Monitoring Strategies for Cleanroom Environments and Cellular Therapies
09:30

Microbial Control and Monitoring Strategies for Cleanroom Environments and Cellular Therapies

Published on: March 17, 2023

  • Discussion of acceptable error criteria, highlighting biological variation.
  • Exploration of organizational leadership and internal characteristics in medical settings.

    • Main Results:

    • Different quality control rules exhibit varying efficiencies in detecting analytical errors.
    • The power function graph is a tool for assessing rule efficiency.
    • Biological variation offers a sensible basis for defining acceptable error limits.

    Conclusions:

    • Optimizing laboratory quality control necessitates a comprehensive approach, integrating effective QC rules, robust troubleshooting, and clearly defined error limits.
    • Leadership and organizational structure significantly influence the effectiveness of quality systems in medical laboratories.
    • Defining acceptable error based on biological variation provides a scientifically sound foundation for quality control.