Enhancing Patient Experience with Predictive Analytics

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Enhancing Patient Experience with Predictive Analytics

Coursera · Intermediate ·📊 Data Analytics & Business Intelligence ·2mo ago

Key Takeaways

Coursera teaches how to leverage predictive analytics to improve patient experience in healthcare

Original Description

In this course, you will learn how to leverage predictive analytics to improve patient experience in healthcare settings. The course focuses on utilizing data to forecast patient experiences beyond traditional satisfaction scores, helping you make informed decisions that enhance patient care and outcomes. You will explore how to analyze hospital-based palliative care programs to reduce patient length of stay, identify risk profiles to minimize early readmissions, and evaluate key metrics in multi-institutional healthcare systems. This course empowers healthcare professionals to apply real-world analytics to improve patient outcomes. What sets this course apart is its practical approach—combining predictive models with actionable insights to drive improvement in healthcare. Through real-world examples, you will gain the knowledge needed to impact patient care on a meaningful level. This course is designed for healthcare professionals, data analysts, and managers in hospital settings. A basic understanding of healthcare operations is recommended. 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, called: Using Predictive Analytics to Improve Healthcare Outcomes. © 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.
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