Quality Management Tools
Quality Management Tools - Related Videos
01:29
Total Quality Management
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2026
Total Quality Management (TQM) is a management philosophy that integrates quality into every aspect of an organization’s operations to achieve high customer satisfaction and long-term success. It emphasizes that everyone, from top management to frontline employees, is responsible for continuously improving processes, products, services, and outcomes.A key principle of TQM is customer focus, where all activities aim to meet or exceed customer needs rather than simply complying with technical...
06:40
The Dyspepsia Educational Tool As a Novel Aid in Dyspepsia Management
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Cited by 2 •
2019
This protocol describes the development process of a digital dyspepsia educational tool. Assessment of unmet needs and literature, content development, and building of the tool are presented. The methodology can be used as a guide for future development of digital educational tools.
08:01
A Web Tool for Generating High Quality Machine-readable Biological Pathways
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Cited by 8 •
2017
PathWhiz is a comprehensive, online pathway drawing tool for generating biochemical and biological pathways. It uses publicly accessible databases and easily expandable palettes consisting of pre-drawn pathway components. This protocol describes how to easily build new pathways, replicate and edit existing pathways, and propagate previously drawn pathways to different organisms.
09:55
Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition
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2024
Here, we present a protocol for obtaining high-quality hyperpolarized xenon-129 magnetic resonance images, covering hardware, software, data acquisition, sequence selection, data management, k-space utilization, and noise analysis.
10:39
Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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2025
This paper outlines the protocol for qualitatively and quantitatively validating a university service-learning instrument, following the parsimony criterion to create the most robust and optimal version possible. The Delphi qualitative validation method and Robust Unweighted Least Squares Exploratory Factor Analysis, as a quantitative item optimization method, are utilized for this purpose.
FAQs
Flowcharts show the sequence of steps, decisions, and handoffs in a clinical workflow, making process gaps easier to see. Check sheets provide a structured way to record performance data or frontline observations as events occur. Used together, they connect what should happen with what repeatedly happens, helping teams locate recurring errors and select focused improvement actions.
Pareto charts organize observed problems so teams can identify which categories contribute most prominently to an issue. This prevents improvement efforts from being spread equally across every defect or source of variation. In medicine, the approach helps quality teams use available performance information to prioritize corrective actions that address the most significant recurring concerns first.
Cause-and-effect diagrams help teams examine possible contributors to an error or unwanted outcome, linking the observed problem to potential sources within the process. Control charts serve a different purpose by showing whether variation is common to the process or unusual. Together, they support more disciplined analysis before teams change a clinical workflow.
Selection should follow the information the team needs. A flowchart fits questions about workflow sequence, a check sheet supports organized data collection, and a Pareto chart helps rank recurring problems. Cause-and-effect diagrams are useful for exploring possible sources, while control charts help assess variation. Matching the tool to the question makes the resulting analysis more actionable.
A team can begin by mapping the workflow, recording relevant observations or performance data, and organizing recurring problems into analyzable categories. It can then investigate possible sources of error, distinguish common from unusual variation, and prioritize corrective actions. Reexamining process information after changes supports continuous improvement and shows whether the workflow has become more consistent.
These tools are especially useful when healthcare teams need to convert frontline observations and performance data into decisions about process improvement. They can be applied across clinical workflows and healthcare organizations to identify recurring sources of error, reduce process variation, and strengthen consistency, safety, and effectiveness. Their value is greatest when findings guide specific corrective actions.