Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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...
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...
Proofreading01:43

Proofreading

Synthesis of new DNA molecules starts when DNA polymerase links nucleotides together in a sequence that is complementary to the template DNA strand. DNA polymerase has a higher affinity for the correct base to ensure fidelity in DNA replication. The DNA polymerase furthermore proofreads during replication, using an exonuclease domain that cuts off incorrect nucleotides from the nascent DNA strand.Errors during Replication Are Corrected by the DNA Polymerase EnzymeGenomic DNA is synthesized in...
Proofreading01:43

Proofreading

Synthesis of new DNA molecules starts when DNA polymerase links nucleotides together in a sequence that is complementary to the template DNA strand. DNA polymerase has a higher affinity for the correct base to ensure fidelity in DNA replication. The DNA polymerase furthermore proofreads during replication, using an exonuclease domain that cuts off incorrect nucleotides from the nascent DNA strand.Errors during Replication Are Corrected by the DNA Polymerase EnzymeGenomic DNA is synthesized in...
Proofreading01:31

Proofreading

Synthesis of new DNA molecules is carried out by the enzyme DNA polymerase, which adds nucleotides on the daughter strand complementary to the template DNA strand. DNA polymerase has a higher affinity to add the correct base and ensures fidelity during DNA replication. Furthermore,  it exhibits proofreading activity during replication, using an exonuclease domain that cuts off incorrect nucleotides from the nascent DNA strand.
Errors During Replication are Corrected by the DNA Polymerase Enzyme
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...

You might also read

Related Articles

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

Sort by
Same author

Clearing the HIPAA Cobwebs.

Journal of AHIMA·2016
Same author

Slow to the information governance starting line.

Journal of AHIMA·2015
Same author

Warning: Health IT may be hazardous to your healthcare.

Journal of AHIMA·2014
Same author

Governance apples and oranges. Differences exist between information governance, data governance, and IT governance.

Journal of AHIMA·2013
Same author

Reviewing the new HIPAA rules.

Journal of AHIMA·2013
Same author

Treating healthcare with health "I"T.

Journal of AHIMA·2012

Related Experiment Video

Updated: Jun 8, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

Quality check.

Chris Dimick1

  • 1chris.dimick@ahima.org

Journal of AHIMA
|October 15, 2010
PubMed
Summary
This summary is machine-generated.

Quality measures are crucial for healthcare performance. Most measures fall into three main categories, impacting healthcare quality and payment.

Related Experiment Videos

Last Updated: Jun 8, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

Area of Science:

  • Healthcare Quality Improvement
  • Health Informatics
  • Health Policy

Background:

  • Meaningful Use (MU) and pay-for-performance (P4P) initiatives emphasize healthcare quality.
  • Numerous quality measures are currently employed in healthcare settings.
  • Understanding the categorization of these measures is essential for effective implementation.

Purpose of the Study:

  • To categorize the broad spectrum of healthcare quality measures.
  • To provide a framework for understanding the landscape of quality measurement.

Main Methods:

  • Literature review of existing quality measures.
  • Analysis of measure categorization in healthcare policy and informatics.

Main Results:

  • Identification of three overarching categories encompassing most healthcare quality measures.
  • Detailed breakdown of measures within each identified category.

Conclusions:

  • A simplified categorization aids in navigating the complexity of quality measures.
  • This framework supports better understanding and application of quality metrics in healthcare.