Overview

AI, Data Science & Cloud Certificates from Google, IBM & Meta — 50% Off

One plan covers every Professional Certificate on Coursera. 50% off Coursera Plus Annual for 10 days only — price increases June 17.

Unlock All Certificates

This course introduces healthcare professionals to the foundational principles of healthcare data analysis aimed at improving clinical outcomes. You’ll learn how to collect, analyze, and interpret data to make informed decisions that directly impact quality improvement in healthcare settings. By understanding how to define improvement goals, select relevant measures, and use various data types, you’ll be equipped to contribute to data-driven initiatives. This course covers the basics of data collection, operational definitions, sampling, and how to use run charts to identify and understand variations in clinical settings. Unlike traditional courses, this one combines theoretical knowledge with real-world applications to ensure that the tools and techniques you learn are practical and actionable. The course is structured to provide hands-on examples and interactive quizzes, ensuring you gain the skills to initiate and evaluate improvement efforts effectively. Healthcare professionals looking to improve their data literacy will benefit from this course. While no advanced experience is required, basic knowledge of healthcare operations and data is helpful. This course is part one 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

Improvement Methodology

This module introduces the Model for Improvement and the PDSA cycle, guiding learners through setting clear aims, using data for measurement, and designing effective tests for change. Participants will gain practical skills in applying improvement methodologies to health care processes and analyzing results to drive sustainable improvements.

Using Data for Improvement

This module introduces the foundational concepts of using data to drive improvement in healthcare settings. Learners will explore different types of data, the creation of meaningful measures, and the importance of operational definitions, sampling, and data stratification. Practical strategies for analyzing and presenting data to inform quality improvement efforts are also covered.

Understanding Variation Using Run Charts

This module introduces the use of run charts to visually analyze process data, detect signals of change, and support improvement initiatives. Learners will explore practical and statistical methods for interpreting run charts, including stratification and the use of cumulative sum statistics. By the end, participants will be able to effectively display, interpret, and draw actionable insights from small data sets.

Learning from Variation in Data

This module introduces visual tools such as run charts and Shewhart charts to help you interpret variation in process data. You will learn how to set and revise chart limits, annotate charts for effective learning, and distinguish between different types of variation to guide improvement strategies.