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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

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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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Development of Analytical Methods01:21

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An analytical methodology can be divided into four sequential steps: technique, method, procedure, and protocol. A technique is a scientific principle that rationalizes a specific phenomenon through chemical measurements. Adapting a technique for analyzing a sample of interest is termed a method. The procedure outlines the directions for performing the analysis via an analytical method. The protocol is the detailed guidelines on the procedure, which should be strictly followed to obtain the...
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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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Data Validation01:15

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Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
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Data Validation01:03

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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
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Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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The NICE process for developing quality standards and indicators.

Brian Bennett1, Emilene Coventry1, Nicola Greenway1

  • 1National Institute for Health and Care Excellence, Manchester, United Kingdom.

Zeitschrift Fur Evidenz, Fortbildung Und Qualitat Im Gesundheitswesen
|December 20, 2014
PubMed
Summary
This summary is machine-generated.

The National Institute for Health and Care Excellence (NICE) outlines its methods for creating evidence-based quality standards and indicators. These processes ensure high-quality healthcare through systematic guideline development.

Keywords:
NICEQualitätsstandardsQualitätsverbesserungclinical indicatorsklinische Indikatorenquality improvementquality standards

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Area of Science:

  • Health Services Research
  • Clinical Governance
  • Evidence-Based Practice

Background:

  • The National Institute for Health and Care Excellence (NICE) plays a crucial role in setting healthcare standards in the UK.
  • Translating evidence-based guidelines into measurable quality standards and indicators is essential for healthcare improvement.
  • A systematic approach is required to ensure the validity and applicability of quality metrics.

Purpose of the Study:

  • To describe the core principles and processes employed by NICE for developing quality standards.
  • To explain the methodology used to derive quality indicators from evidence-based guidelines.
  • To provide transparency in the NICE quality improvement framework.

Main Methods:

  • Systematic review of evidence-based guidelines.
  • Stakeholder consultation and consensus building.
  • Development of measurable quality standards and indicators.
  • Validation of indicators against established criteria.

Main Results:

  • NICE utilizes a defined set of principles and a structured process for quality standard development.
  • Quality indicators are derived directly from recommendations within evidence-based guidelines.
  • The process ensures that quality standards and indicators are evidence-based, relevant, and actionable.

Conclusions:

  • The NICE methodology provides a robust framework for developing healthcare quality standards and indicators.
  • This systematic approach supports the implementation of evidence-based practice and improves patient care.
  • The described principles and processes are fundamental to NICE's role in enhancing health and social care quality.