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Peer Review

Transforming Healthcare Through Data: A Comprehensive Guide to Analytics for Executives and Professionals

Reviewed:

Oct 28, 2026 by Health Sciences
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Ratings

Overall Rating: 4.8 stars
Content Quality: 4.8 stars
Effectiveness: 4.8 stars
Ease of Use: 5.0 stars
Overview:

Open-access textbook covering healthcare analytics, artificial intelligence, governance, interoperability, cybersecurity, quality improvement, operations, finance, leadership, and organizational transformation.

Type of Material:

  • Open (Access) Textbook
Recommended Uses:

  • Homework reading, individual, team, self-paced learning, asynchronous learning
Technical Requirements:

  • Online Access
  • Access the online edition through a standard web browser. Downloadable PDF and EPUB versions are available for offline use.
  • Users may access the content on desktop computers, laptops, tablets, smartphones, and e-book readers that support EPUB formats.
  • No specialized software or institutional subscription is required.
Identify Major Learning Goals:

After active engagement, the learner will

  1. Understand the conceptual, technical, and organizational foundations of healthcare data analytics.
  2. Explore applied healthcare analytics, big data, artificial intelligence, and qualitative analytics.
  3. Examine the capabilities required to govern, implement, sustain, and advance healthcare analytics responsibly.
Target Student Population:

  • This book is intended for readers with varied educational, professional, and technical backgrounds, including:

    • undergraduate and graduate students in healthcare administration, public health, health informatics, nursing, business, and related disciplines;
    • healthcare executives, administrators, and operational leaders;
    • clinicians transitioning into administrative, informatics, quality, or analytics leadership roles;
    • analysts, data scientists, informaticists, and technology professionals seeking a stronger understanding of healthcare context;
    • finance, revenue-cycle, quality, compliance, privacy, and cybersecurity professionals;
    • educators developing healthcare analytics curricula; and
    • independent learners seeking an accessible introduction to analytics and data-informed leadership.
Prerequisite Knowledge or Skills:

  • Knowledge of one or more of the following:
    • Healthcare administration, public health, health informatics and healthcare data science, nursing, business, and related disciplines
    • Basic computer navigation skills

Content Quality

Rating:
Strengths:

  • Valid and holistic content information is included.
  • The chapters include some source citations.
  • No advanced programming or statistical background is required to begin learning.
  • The OER text introduces technical concepts in accessible language and connects them to practical healthcare examples.
  • Concepts are clearly presented and follow a consistent progression, using a scaffolding approach from simple to complex.
  • The learning material integrates concepts well and is overall accurate. 
Concerns:

  • Some image attributions are missing within the chapters.
  • Some references appear in the reference list but aren't cited in the chapter. For example, in Chapter 1: Cheikh, A. Ben, Gorincour, G., Nivet, H., May, J., Seux, M., Calame, P., Thomson, V., Delabrousse, E., & Crombé, A. (2022). How artificial intelligence improves radiological interpretation in suspected pulmonary embolism. European Radiology, 32(9), 5831–5842.  and in Chapter 2: Hozak, M. A., Nelson, J. W., & Felgen, J. (2021). Using predictive analytics to improve healthcare outcomes. John Wiley & Sons, Inc. 

Potential Effectiveness as a Teaching Tool

Rating:
Strengths:

  • Each chapter includes an overview, learning objectives, figures, images, call-out boxes, and a summary of key points.
  • The detailed figures that visually represent the concepts and systems are outstanding! 
  • The content moves from basic to more complex, allowing learners to build on what they've learned.
  • Tables are informative and organize concepts and examples. 
  • Good use of white space with a content-heavy source.
  • Terms are clearly defined.
  • Sections are good at demonstrating relationships between concepts. 
  • Good use of headings and tables to help simplify complex areas.
  • The book is freely accessible under a Creative Commons 0 public domain license, which provides equitable access for everyone.

 

 

 

Concerns:

  • Adding engaging activities that let learners test their understanding of the content would greatly improve the source. Knowledge-check questions, matching, crossword puzzles, or drag-and-drop activities would help the learner.
  • Those using the resource should consider adding knowledge checks so students can assess their own understanding of the content.

Ease of Use for Both Students and Faculty

Rating:
Strengths:

  • Heading levels 1 and 2 are set up for accessibility
  • No split cells in tables.
  • Complex figures include detailed descriptions following the figure. The narrative is detailed and effectively supports complex figures. 
  • Shaded colors over text use an appropriate contrast ratio.
  • Alt-text is used for images.
  • The textbook is easy to navigate, with standard forward and backward navigation and a table of contents that links to each corresponding chapter.
  • The table of contents on the left side of the screen helps to move through the topics. 

 

 

Other Issues and Comments:

This OER textbook is a tremendous resource, with great detail, helpful figures, and detailed narrative descriptions! 

Creative Commons:
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