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

Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

3.5K
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
3.5K
Integrated Healthcare System01:20

Integrated Healthcare System

2.5K
An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
2.5K
Quality Assurance01:19

Quality Assurance

3.7K
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...
3.7K
Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

716
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...
716
Nursing Clinical Information System01:27

Nursing Clinical Information System

1.3K
Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
1.3K
Quality Control01:05

Quality Control

4.1K
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...
4.1K

You might also read

Related Articles

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

Sort by
Same author

High-resolution two-dimensional electrophoretic survey of serum protein genetic types in Schmiedeleut Hutterites.

American journal of human biology : the official journal of the Human Biology Council·2017
Same author

The last word on the LEAN laboratory?

MLO: medical laboratory observer·2014
Same author

QC design: it's easier than you think.

MLO: medical laboratory observer·2014
Same author

A strategic informatics approach to autoverification.

Clinics in laboratory medicine·2013
Same author

IICC aims to connect labs and clinicians.

Health management technology·2011
Same author

IICC aims to connect labs and clinicians.

MLO: medical laboratory observer·2011

Related Experiment Video

Updated: Mar 8, 2026

Conducting Respiratory Oscillometry in an Outpatient Setting
14:49

Conducting Respiratory Oscillometry in an Outpatient Setting

Published on: April 8, 2022

8.7K

Using Sigma Quality Control to Verify and Monitor Performance in a Multi-Instrument, Multisite Integrated Health Care

Harold H Harrison1, Jay B Jones2

  • 1Laboratory Medicine, Geisinger Health System, 100 North Academy Avenue, Danville, PA 17822, USA.

Clinics in Laboratory Medicine
|February 4, 2017
PubMed
Summary

This study introduces a Sigma-based quality control network for clinical laboratory testing across multiple hospitals. It ensures reliable performance through data-driven rule selection for laboratory diagnostics.

Keywords:
Clinical chemistryCoagulationHematologyMultisite instrument systemNetworked QC managementSigma metrics

More Related Videos

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies
10:38

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies

Published on: January 16, 2019

21.0K
Non-Invasive Monitoring of Microvascular Oxygenation and Reactive Hyperemia using Hybrid, Near-Infrared Diffuse Optical Spectroscopy for Critical Care
14:28

Non-Invasive Monitoring of Microvascular Oxygenation and Reactive Hyperemia using Hybrid, Near-Infrared Diffuse Optical Spectroscopy for Critical Care

Published on: May 10, 2024

2.4K

Related Experiment Videos

Last Updated: Mar 8, 2026

Conducting Respiratory Oscillometry in an Outpatient Setting
14:49

Conducting Respiratory Oscillometry in an Outpatient Setting

Published on: April 8, 2022

8.7K
Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies
10:38

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies

Published on: January 16, 2019

21.0K
Non-Invasive Monitoring of Microvascular Oxygenation and Reactive Hyperemia using Hybrid, Near-Infrared Diffuse Optical Spectroscopy for Critical Care
14:28

Non-Invasive Monitoring of Microvascular Oxygenation and Reactive Hyperemia using Hybrid, Near-Infrared Diffuse Optical Spectroscopy for Critical Care

Published on: May 10, 2024

2.4K

Area of Science:

  • Clinical Laboratory Science
  • Quality Management Systems
  • Analytical Chemistry

Background:

  • Implementing robust quality control is crucial for accurate clinical diagnostics.
  • Variability in laboratory instrumentation necessitates standardized quality management.
  • Existing quality control methods may not fully leverage performance data.

Purpose of the Study:

  • To develop and implement a system-wide integrated network for quality control.
  • To utilize Sigma metrics for a data-driven selection of Westgard rules.
  • To ensure reliable performance in fundamental chemistry, coagulation, and hematology analysis.

Main Methods:

  • Established an integrated network connecting multiple hospitals and regional laboratories.
  • Deployed Sigma-based quality control across diverse instrumentation (multiple models per manufacturer).
  • Monitored Sigma values for over five years to validate performance and justify rule selection.

Main Results:

  • Successfully implemented a Sigma-driven approach for Westgard rule selection.
  • Demonstrated sustained performance monitoring and validation through Sigma values.
  • The network encompasses a wide range of analytical platforms and laboratory settings.

Conclusions:

  • A Sigma-based quality control network provides a robust framework for laboratory performance management.
  • Data-driven rule selection enhances the reliability of clinical diagnostic testing.
  • Long-term Sigma value monitoring validates the effectiveness of quality control strategies.