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Related Concept Videos

Quality Assurance01:19

Quality Assurance

3.2K
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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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.
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...
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Quality of Water01:19

Quality of Water

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In concrete preparation, the quality of water is paramount as it affects the strength and durability of the concrete. Potable water is usually preferred; however, it must not have excessive sodium or potassium to prevent compromising the concrete's integrity. Water quality is typically evaluated based on impurities such as dissolved solids, chlorides, and sulfates, and its pH value is ideally between 6 and 8. Even slightly acidic natural water may be acceptable unless it contains harmful...
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Quartile01:15

Quartile

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Quartiles are numbers that separate the data into quarters. Quartiles may or may not be part of the data. To find the quartiles, first, find the median or second quartile. The first quartile, Q1, is the middle value of the lower half of the data, and the third quartile, Q3, is the middle value, or median, of the upper half of the data. To get the idea, consider the same data set:
1; 1; 2; 2; 4; 6; 6.8; 7.2; 8; 8.3; 9; 10; 10; 11.5
The median or second quartile is seven. The lower half of the...
9.8K
Pulse amplitude and quality01:17

Pulse amplitude and quality

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Pulse amplitude is a crucial indicator of cardiac health because it provides valuable insights into the strength of left ventricular contractions and the overall uniformity of blood circulation within the vasculature. The strength of the pulse is directly related to the force with which the heart contracts and the volume of blood being pumped.
A weak or absent pulse may indicate reduced cardiac output or poor left ventricular contraction, which can be signs of cardiovascular dysfunction or...
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Standard Deviation01:10

Standard Deviation

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The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The standard deviation value is small when the data are concentrated close to the mean, exhibiting slight variation or spread. The standard deviation value is never negative, it is either positive or zero. The standard deviation is larger when the data values are more spread out from the mean, which means the data values are exhibiting more variation.
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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
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Quality: the next six months

R H Laessig1, S S Ehrmeyer

  • 1Department of Pathology, University of Wisconsin, Madison 53706-1572, USA. rhl@prof.slh.wisc.edu

Clinical Chemistry
|May 1, 1997
PubMed
Summary
This summary is machine-generated.

Clinical laboratories are ready to shift from regulations to a quality-based system. A collaborative "Quality Alliance" of lab professionals, manufacturers, and regulators is key to improving patient care and reducing costs.

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Area of Science:

  • Clinical Laboratory Science
  • Quality Management Systems
  • Healthcare Policy

Background:

  • Current clinical laboratory operations rely heavily on regulations, laws, and inspections.
  • There is a recognized need to transition towards a more effective quality-based system.
  • Existing regulatory frameworks aim to ensure laboratory goals but may not be the most efficient approach.

Purpose of the Study:

  • To explore the consensus among diverse stakeholders on the need for a quality-based system in clinical laboratories.
  • To identify the potential benefits of transitioning from a regulatory-focused system to a quality-driven approach.
  • To propose a collaborative model for implementing a true quality system in clinical laboratories.

Main Methods:

  • The study is based on views expressed during a forum involving various stakeholders.
  • Analysis of participant consensus on the current state and future direction of laboratory quality.
  • Conceptualization of a collaborative alliance for quality system implementation.

Main Results:

  • A strong consensus exists among participants regarding the readiness for a transition to a quality-based system.
  • A quality-based system offers significant benefits, including cost reduction, product improvement, and enhanced test result accuracy.
  • The formation of a
  • Quality Alliance
  • comprising laboratory personnel, manufacturers, and regulators is identified as essential for this transition.

Conclusions:

  • The transition to a quality-based system in clinical laboratories is timely and achievable.
  • A collaborative
  • Quality Alliance
  • is crucial for successfully implementing and sustaining a true quality system.
  • This shift promises improved patient care through better laboratory services and outcomes.