Overview

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This course explores how predictive analytics can transform healthcare by shifting from a reactive to a proactive approach in managing patient outcomes. Learners will dive into predictive tools and strategies, enhancing their ability to drive significant improvements in healthcare safety and quality. Through the course, students will learn how advanced caring theories, combined with predictive analytics, can lead to better healthcare processes, more insightful data-driven decisions, and improved patient care. The course offers practical techniques for leveraging data to optimize healthcare delivery. What makes this course unique is its practical approach that blends advanced theoretical frameworks with actionable real-world applications. You’ll gain the skills to apply predictive analytics to improve healthcare outcomes, reduce falls, and enhance patient safety. This course is ideal for healthcare professionals, data scientists, and organizational leaders seeking to use predictive analytics for improving patient safety and operational efficiency. A basic understanding of healthcare and data analytics is recommended. 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, called: Using Predictive Analytics to Improve Healthcare Outcomes. Copyright © 2021 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. The right of John W. Nelson, Jayne Felgen, and Mary Ann Hozak to be identified as the authors of the editorial material in this work has been asserted in accordance with law.

Syllabus

Using Predictive Analytics to Move from Reactive to Proactive Management of Outcomes

In this section, we explore using predictive analytics to create context-aware models that engage staff in outcomes improvement through empirical data storytelling and actionable insights.

Advancing a New Paradigm of Caring Theory

In this section, we examine caring theories and frameworks in healthcare, focusing on their application, scientific validation, and measurement to improve patient outcomes through compassionate care.

Cultivating a Better Data Process for More Relevant Operational Insight

In this section, we examine the importance of accurate data collection, analysis, and presentation to drive operational improvements and informed decision-making.

Leadership for Improved Healthcare Outcomes

In this section, we explore how healthcare leaders use data to drive operational improvements and cultural change. Key concepts include data-driven decision-making, organizational culture analysis, and predictive analytics for targeted action.

Using Predictive Analytics to Reduce Patient Falls

In this section, we explore using predictive analytics and R+A+A to reduce patient falls. Key concepts include relationship-based care, collaborative decision-making, and data-driven safety plans.

Using the Profile of Caring to Improve Safety Outcomes

In this section, we explore how machine learning and the Profile of Caring® identify clinician behaviors that improve safety outcomes, enabling proactive staff training and hiring for better patient care.