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This course provides a deep dive into advanced methods for analyzing variation in healthcare data, with a focus on Shewhart charts and related statistical techniques. You’ll learn how to interpret both continuous and attribute data, and master advanced visualization tools such as Pareto and scatterplots, which are essential for understanding data variation. Through the course, learners will gain the skills needed to address common challenges in chart interpretation, apply adaptations of Shewhart-type charts, and use specialized techniques for analyzing complex data scenarios. Emphasis is placed on practical application, ensuring that you can translate statistical insights into quality improvement strategies for healthcare settings. What sets this course apart is its combination of theory and hands-on practice. The course covers key issues faced by professionals in real-world healthcare settings and provides tools for uncovering actionable insights from aggregate data to improve care. Healthcare professionals involved in data analysis and quality improvement will benefit from this course. A basic understanding of healthcare data and statistical methods is recommended but not required. This course is part two of a three-course Specialization designed to provide a comprehensive learning pathway in this subject area. While it delivers standalone value and practical skills, learners seeking a more integrated and in-depth progression may benefit from completing the full Specialization. Copyright © 2022 John Wiley & Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

Syllabus

Understanding Variation Using Shewhart Charts

This module guides learners through the selection and application of Shewhart charts for both continuous and attribute data, including I, Xbar S, P, C, U, G, and T charts. Participants will learn to distinguish between common and special cause variation and assess process capability using control charts. Real-world examples illustrate how these tools support data-driven improvement in various contexts.

Additional Tools for Understanding Variation in Data

This module introduces a variety of graphical tools—including frequency plots, Pareto charts, scatterplots, and radar charts—to deepen your understanding of variation in data. You will learn how to use these tools alongside Shewhart charts and apply stratification techniques to enhance data interpretation and process improvement.

Shewhart Chart Savvy: Dealing with Common Issues

This module guides learners through common challenges encountered when creating and interpreting Shewhart charts, including best practices for formatting, recalculating limits, and selecting appropriate chart types. Participants will also explore considerations for using SPC software, publishing charts, and distinguishing Shewhart's theory from statistical inference. By the end, learners will be equipped to troubleshoot and enhance the effectiveness of Shewhart charts in improvement projects.

More Shewhart-Type Charts

This module introduces advanced Shewhart-type charts, including Xbar Range, Median, Negative Binomial, and multivariate charts, as well as adaptations like CUSUM and EWMA for enhanced detection of variation in health data. Learners will gain practical skills in selecting and interpreting specialized control charts to address complex data scenarios in healthcare quality improvement.

Special Uses for Shewhart Charts

This module explores advanced adaptations of Shewhart charts for complex healthcare data scenarios, including handling seasonal effects, confounders, autocorrelation, and risk adjustment. Learners will discover how to modify standard control charts to address real-world challenges and improve data interpretation. The module also distinguishes Shewhart charts from comparison charts and discusses appropriate data transformations.

Drilling Down into Aggregate Data for Improvement II

This module guides learners through the process of analyzing and improving healthcare outcomes using aggregate data. By applying the Drill Down Pathway and Shewhart charts, participants will learn to disaggregate data, identify improvement opportunities, and implement effective changes. Real-world case studies, such as adverse drug events, illustrate each step for practical understanding.