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

4.0K
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...
4.0K
Quality Control01:05

Quality Control

4.3K
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...
4.3K
Errors occurring during blood pressure monitoring01:25

Errors occurring during blood pressure monitoring

1.6K
Blood pressure monitoring is a crucial clinical procedure in diagnosing and managing various cardiovascular conditions. Despite its significance, the accuracy of blood pressure measurements can be compromised by multiple factors, potentially leading to either falsely high or low readings. These inaccuracies are critical as they can significantly impact patient care. So, it is vital to understand these challenges deeply and adopt strategic approaches to minimize errors.
Several factors...
1.6K
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

2.1K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.1K
Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

37.7K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
37.7K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

94.0K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
94.0K

You might also read

Related Articles

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

Sort by
Same author

A Guide to Observable Differences in Stated Preference Evidence.

The patient·2021
Same author

Does the U.S. Navy's reliance on objective standards prevent discrimination in promotions and retentions?

PloS one·2021
Same author

Observations on Performance Improvement in Surgical Patient Care.

AORN journal·2019
Same author

Modeling Preference and Willingness to Pay for Drought Tolerance (DT) in Maize in Rural Zimbabwe.

World development·2017
Same author

Response to "Inference Using Sample Means of Parametric Nonlinear Data Transformations".

Health services research·2016
Same author

Exploring direct and indirect influences of physical work environment on job satisfaction for early-career registered nurses employed in hospitals.

Research in nursing & health·2014
Same journal

WHO Issues Guidelines for Treating Ebola and Marburg Viruses.

JAMA·2026
Same journal

FDA Approves Additional Naloxone Nasal Spray for Opioid Overdose.

JAMA·2026
Same journal

HIV May Hide in More Cells Than Previously Thought-Here's What That Could Mean for a Cure.

JAMA·2026
Same journal

US Dietary Supplement Use Increasing, Especially in Older Adults.

JAMA·2026
Same journal

Heat Stress From Climate Change Surges Globally.

JAMA·2026
Same journal

Strength Training Linked With Lower Cardiovascular Disease Risk in Women.

JAMA·2026
See all related articles

Related Experiment Video

Updated: May 6, 2026

Conducting Respiratory Oscillometry in an Outpatient Setting
14:49

Conducting Respiratory Oscillometry in an Outpatient Setting

Published on: April 8, 2022

9.7K

Increasing demands for quality measurement.

Robert J Panzer1, Richard S Gitomer, William H Greene

  • 1Department of Medicine, General Medicine Division, University of Rochester Medical Center, Rochester, New York2Department of Public Health Sciences, Division of Healthcare Management, University of Rochester Medical Center, Rochester, New York.

JAMA
|November 14, 2013
PubMed
Summary
This summary is machine-generated.

Improving healthcare quality measurement is crucial for value-based reform. Key challenges include fragmented systems and reliance on flawed data, necessitating a focus on comprehensive, transformative measures.

More Related Videos

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification
09:04

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Published on: August 17, 2015

16.6K
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

686

Related Experiment Videos

Last Updated: May 6, 2026

Conducting Respiratory Oscillometry in an Outpatient Setting
14:49

Conducting Respiratory Oscillometry in an Outpatient Setting

Published on: April 8, 2022

9.7K
Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification
09:04

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Published on: August 17, 2015

16.6K
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

686

Area of Science:

  • Health Services Research
  • Healthcare Quality Improvement
  • Patient Safety

Background:

  • Healthcare quality and patient safety measurement are evolving due to US health system reforms focused on value.
  • The National Quality Forum guides the development and selection of quality measures for evaluating care.

Purpose of the Study:

  • To identify challenges in current healthcare quality measurement systems.
  • To propose recommendations for improving the US quality measurement system.

Main Methods:

  • Analysis of existing quality measurement systems and their limitations.
  • Review of national quality strategy and public-private partnerships.

Main Results:

  • Challenges include diverse measurement purposes, reliance on flawed claims data, system fragmentation, and resource strain from numerous measures.
  • Proliferation of measures creates logistical problems for clinicians, hospitals, and insurers.

Conclusions:

  • Recommendations include raising the standard for quality measures to drive transformational change.
  • Promoting harmonized, comprehensive measurement systems, reducing claims-based measures, and transitioning to electronic health record measures are essential.