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Related Concept Videos

Quality Control01:05

Quality Control

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...
Quality Assurance01:19

Quality Assurance

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...
Lumber Defects01:23

Lumber Defects

Lumber defects, which can affect both the appearance and structural integrity of wood, include a variety of growth and manufacturing flaws. Growth defects such as knots and knotholes occur where branches were once attached to the tree trunk, with knotholes forming when these knots fall out. Other natural defects include decay and insect damage, which compromise the wood's strength and durability.
Shakes are minor fractures that run along or across the wood's annual rings, while wane is...
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

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...
Wood Surfacing01:14

Wood Surfacing

Wood surfacing is a critical finishing process designed to smoothen the wood surface, enhance its dimensional accuracy, and make handling safer. This process compensates for potential shrinkage during the seasoning phase by marginally increasing the wood dimensions before surfacing. It also helps correct some distortions that may occur as the wood dries.
The equipment used in the surfacing process is a plane equipped with rotating blades. This tool efficiently smoothens the wood surface and can...

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Related Experiment Videos

Board quality scorecards: measuring improvement.

Christine A Goeschel1, Sean M Berenholtz, Richard A Culbertson

  • 1Tulane University, New Orleans, LA, USA. Cgoesch1@jhmi.edu

American Journal of Medical Quality : the Official Journal of the American College of Medical Quality
|April 19, 2011
PubMed
Summary
This summary is machine-generated.

Hospital boards need better tools to measure quality and patient safety. Current methods often identify risks rather than track improvement, highlighting the need for valid outcome measures for effective oversight.

Related Experiment Videos

Area of Science:

  • Healthcare Management
  • Patient Safety Science
  • Quality Improvement Metrics

Background:

  • Board accountability for healthcare quality and patient safety is established, but measurement science is underdeveloped.
  • Distinctions between performance measurement, hazard identification, and progress monitoring are frequently unclear.
  • Hospital scorecards used by boards lack evidence of validity due to absent national standards.

Purpose of the Study:

  • To identify the quality monitoring measures utilized by hospital boards.
  • To assess the validity and utility of these measures for board oversight.
  • To inform policy regarding board roles in quality improvement.

Main Methods:

  • Cross-sectional study involving hospital boards.
  • Analysis of measures used by boards to monitor quality and patient safety.
  • Evaluation of measure validity and focus (hazard identification vs. rate measurement).

Main Results:

  • Significant variation in quality monitoring measures across hospital boards.
  • Many measures demonstrated uncertain validity, primarily identifying hazards instead of quantifying rates.
  • Limited evidence supports the usefulness of current measures for assessing quality improvement.

Conclusions:

  • Hospital boards require more valid outcome measures to effectively monitor quality and patient safety progress.
  • Current measurement limitations impact national and hospital-level assessments of quality improvement.
  • Policy development is needed to enhance board oversight capabilities through improved metrics.