Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Quality Assurance

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...

Quality Control

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

AAPM task group report 288: Recommendations for guiding radiotherapy event narratives.

Medical physics·2024

Same author

The ABS brachytherapy schools.

Brachytherapy·2020

Same author

GEC-ESTRO/ACROP recommendations for quality assurance of ultrasound imaging in brachytherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2020

Same author

Radiation Protection Responsibility in Brachytherapy.

Health physics·2018

Same author

Redefining and reinvigorating the role of physics in clinical medicine: A Report from the AAPM Medical Physics 3.0 Ad Hoc Committee.

Medical physics·2018

Same author

Limitations in learning: How treatment verifications fail and what to do about it?

Brachytherapy·2017

Search research articles

Related Experiment Video

Updated: Jul 6, 2026

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

Taxonometric guidance for developing quality assurance.

Bruce Thomadsen¹, She-Woei Lin

¹Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA. thomadsen@humonc.wisc.edu

International Journal of Radiation Oncology, Biology, Physics

|May 24, 2008

Summary

This summary is machine-generated.

Taxonomies classify human failures in error reduction analysis. This classification guides interventions by revealing causes of errors and informing future prevention strategies.

More Related Videos

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

Related Experiment Videos

Last Updated: Jul 6, 2026

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

Area of Science:

Human factors research
Cognitive psychology
Systems safety

Background:

Error reduction analysis frequently employs taxonomies to categorize human failures.
Understanding the characteristics of human errors is crucial for effective intervention.

Purpose of the Study:

To highlight the utility of taxonomies in error reduction analysis.
To demonstrate how classifying human failures provides insights into error causation.

Main Methods:

Review of the application of taxonomies in error reduction analysis.
Illustrative examples of how failure classification informs corrective actions.

Main Results:

Taxonomies offer a structured approach to understanding human failures.
Classification reveals underlying factors contributing to errors, differentiating between types of failures.

Conclusions:

Taxonomies are essential tools for guiding remediation and preventing future failures.
Tailoring corrective actions based on classified failure types enhances intervention effectiveness.