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Related Concept Videos

Quality Assurance01:19

Quality Assurance

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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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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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Run Charts01:12

Run Charts

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Run charts serve as an essential instrument for visualizing the performance of various processes over time, enabling the identification of trends and patterns crucial for quality improvement. These charts map out a series of data points chronologically, offering insights into the stability and efficiency of a process. A run chart's creation involves plotting data points on a graph, with the time intervals on the horizontal axis and the specific measurements on the vertical axis. For...
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Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

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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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Interpreting R Charts01:22

Interpreting R Charts

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R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
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Interpreting Run Charts01:25

Interpreting Run Charts

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Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
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Related Experiment Video

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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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[Practice report: the process-based indicator dashboard. Visualising quality assurance results in standardised

Thomas Petzold1, Diana Hertzschuch2, Frank Elchlep2

  • 1Zentralbereich Qualitäts- und Medizinisches Risikomanagement, Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden, Dresden, Deutschland; Zentrum für Evidenzbasierte Gesundheitsversorgung, Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden, Dresden, Deutschland.

Zeitschrift Fur Evidenz, Fortbildung Und Qualitat Im Gesundheitswesen
|December 20, 2014
PubMed
Summary

Process management (PM) enhances clinical treatment quality and safety through systematic analysis. Utilizing quality indicators and dashboards aids in process optimization and error remediation for improved patient care.

Keywords:
IndikatorendashboardProzessmanagementProzessoptimierungQuality assuranceQualitätsindikatorQualitätssicherungindicator dashboardprocess managementprocess optimisationquality indicator

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Area of Science:

  • Healthcare Management
  • Quality Improvement
  • Clinical Process Analysis

Background:

  • Process management (PM) is crucial for optimizing clinical treatment quality and safety.
  • Effective PM necessitates strong employee and management commitment to change.
  • Systematic quality measurement requires well-defined quality indicators.

Purpose of the Study:

  • To highlight the benefits of process management in clinical settings.
  • To emphasize the role of quality indicators in assessing treatment quality.
  • To demonstrate how process-based dashboards facilitate analysis and improvement.

Main Methods:

  • Utilizing external quality assurance indicators (Sect. 137 SGB V) for comparable quality results.
  • Analyzing data from 30 defined inpatient treatment subjects across Germany.
  • Implementing process-based indicator dashboards for continuous monitoring.

Main Results:

  • Quality indicators provide essential information for employee understanding of treatment processes.
  • Process-based dashboards enable effective process analysis and identification of areas for improvement.
  • Continuous monitoring of indicators allows for rapid error detection and correction.

Conclusions:

  • Process management, supported by quality indicators and dashboards, is vital for enhancing healthcare quality and safety.
  • Benchmarking using quality indicators can identify significant potential for process optimization.
  • A motivated workforce and management are key to successful implementation of process management strategies.