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 Control01:05

Quality Control

1.1K
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...
1.1K
Modeling and Similitude01:12

Modeling and Similitude

512
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
512
Quality Assurance01:19

Quality Assurance

875
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...
875
Control Systems01:10

Control Systems

1.7K
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...
1.7K
Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

516
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...
516

You might also read

Related Articles

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

Sort by
Same author

Addressing property and unit discordance in laboratory interoperability: the role of NPU as a governance layer.

Clinical chemistry and laboratory medicine·2026
Same author

What are the correlates of laboratory productivity in clinical laboratories in the Asia Pacific region?

Clinical biochemistry·2026
Same author

An improved approach to modelling patient reclassification: HbA<sub>1c</sub> as an example.

Clinical chemistry and laboratory medicine·2026
Same author

Scenario-based multi-parametric QC for quality control of complex algorithms used in clinical care.

Clinical chemistry and laboratory medicine·2026
Same author

Bullwinkle's Revenge: From Moose Roast to Nocturnal Urticaria.

Clinical chemistry·2026
Same author

Clinical validation and implementation of mSTOP, a machine learning-based, longitudinal prediction model for the early identification of non-small cell lung cancer patients who not benefit from immune checkpoint inhibitor treatment.

Clinical chemistry and laboratory medicine·2026
Same journal

Interlaboratory Comparison of a Glucagon and Oxyntomodulin Immuno-LC-MS/MS Assay: Implications for Diabetes Research.

Clinical chemistry·2026
Same journal

Comparison of Information-Dependent Acquisition and Sequential Window Acquisition of All Theoretical Mass Spectra for Untargeted Drug Testing on a Linear Ion Trap-Pulsing Quadrupole-Time of Flight Mass Spectrometer.

Clinical chemistry·2026
Same journal

Patterns of One-Year Change in HbA1c and Continuous Glucose Monitoring (CGM) Metrics in Older Adults with Type 2 Diabetes.

Clinical chemistry·2026
Same journal

TSH Pediatric Reference Intervals: Lack of CALIPER Applicability to US-Based Populations.

Clinical chemistry·2026
Same journal

Rapid Detection of Hemoglobinopathy Variants Using One-Step Library Preparation and Nanopore Sequencing.

Clinical chemistry·2026
Same journal

Editor's Note: Circulating Proteolytic Products of Carboxypeptidase N for Early Detection of Breast Cancer.

Clinical chemistry·2026
See all related articles

Related Experiment Video

Updated: Dec 15, 2025

Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training
05:04

Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training

Published on: August 9, 2024

1.3K

Understanding Patient-Based Real-Time Quality Control Using Simulation Modeling.

Andreas Bietenbeck1, Mark A Cervinski2,3, Alex Katayev4

  • 1Institut für Klinische Chemie und Pathobiochemie Klinikum, München, Germany.

Clinical Chemistry
|July 9, 2020
PubMed
Summary
This summary is machine-generated.

Patient-based real-time quality control (PBRTQC) offers advantages over traditional methods. Computer simulations identified optimal PBRTQC parameters for early bias detection, improving laboratory quality control.

Keywords:
average of normalsexponentially weighted moving averagemoving averageoptimizationquality controlsimulation

More Related Videos

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research
07:15

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Published on: December 18, 2020

4.8K
Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects
11:12

Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects

Published on: September 18, 2012

17.7K

Related Experiment Videos

Last Updated: Dec 15, 2025

Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training
05:04

Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training

Published on: August 9, 2024

1.3K
Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research
07:15

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Published on: December 18, 2020

4.8K
Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects
11:12

Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects

Published on: September 18, 2012

17.7K

Area of Science:

  • Clinical Chemistry
  • Laboratory Medicine
  • Quality Control

Background:

  • Patient-based real-time quality control (PBRTQC) offers an alternative to traditional quality control methods.
  • PBRTQC requires optimization of parameters like algorithm, truncation, block size, and control limits for individual laboratories.

Purpose of the Study:

  • To assess the effectiveness of different PBRTQC methods in early bias detection using computer simulations.
  • To provide recommendations for optimizing PBRTQC parameters based on simulation results.

Main Methods:

  • Computer simulations were performed using 460,000 historical patient measurements for 10 analytes.
  • Biases were introduced to simulate erroneous measurements, and various PBRTQC algorithms were evaluated for their detection capabilities.
  • A web application was developed to facilitate the estimation of PBRTQC performance.

Main Results:

  • "Percentiles of daily extremes" proved effective for control limit calculation, though sensitive to changes in measurement distribution.
  • Box-Cox transformation enhanced error detection, and Winsorization outperformed simple outlier removal.
  • Parameter choices significantly impacted performance; for example, block size affected medians more than Harrell-Davis 50 percentile estimators (HD50s).

Conclusions:

  • Computer simulations are valuable for optimizing PBRTQC parameters.
  • Certain parameters demonstrate superior performance and can be considered as default settings for PBRTQC implementation.