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Quality Control01:05

Quality Control

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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.
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Quality Assurance01:19

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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...
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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.
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Introduction to Statistical Process Control01:15

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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...
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The  x̄ chart is a statistical tool for monitoring the means in a process.
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The internal quality control in the traceability era.

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Accurate laboratory results require traceability to higher references and acceptable measurement uncertainty (MU). Redesigned internal quality control (IQC) programs help medical laboratories verify in vitro diagnostics (IVD) traceability and monitor system reliability for clinical validity.

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Area of Science:

  • Clinical Laboratory Science
  • Analytical Chemistry
  • In Vitro Diagnostics

Background:

  • Laboratory result accuracy and equivalence depend on traceability to higher-order references.
  • Measurement uncertainty (MU) must be acceptable for the intended clinical use.
  • In vitro diagnostics (IVD) manufacturers must establish calibration hierarchies for traceable system calibrators.

Purpose of the Study:

  • To outline the necessity for medical laboratories to verify IVD calibrator traceability and estimate MU.
  • To propose a redesigned internal quality control (IQC) program for enhanced IVD traceability surveillance.
  • To ensure the clinical validity of laboratory test results through rigorous quality control.

Main Methods:

  • Verification of manufacturer-implemented traceability for system calibrators.
  • Estimation of measurement uncertainty (MU) on clinical samples.
  • Redesigning internal quality control (IQC) programs into two components: IQC component I for traceability surveillance and IQC component II for system reliability monitoring.

Main Results:

  • The proposed IQC redesign enables medical laboratories to surveil IVD traceability.
  • IQC component I verifies that control materials fall within clinically suitable validation ranges.
  • IQC component II allows for the estimation of MU due to random effects and monitoring of system performance.

Conclusions:

  • A redesigned IQC program is crucial for ensuring IVD traceability and monitoring measurement uncertainty.
  • Laboratories must actively verify manufacturer traceability and estimate MU to maintain clinical validity.
  • Continuous monitoring of IVD measuring systems through IQC component II ensures prompt corrective actions and reliable results.