After previewing this book at the AUPHA Annual Meeting this year, I was looking forward to my copy to arrive so I could really get into it. At face value it had the right ingredients: The author Dr. Susan White (from The Ohio State University) knows her stuff, and AHIMA, -the grandaddy organization of health information management, is the publisher.
Let me tell you it didn’t disappoint. While the market currently has many books that are either high-level jargon essays or my-tool-or-method-you’ve-never-heard-of-can-do-everything, Dr. White’s book is just what it says it is: practical, introductory, ways to analyze health data.
- Paperback: 258 pages(1/3 of this is appendix reference stuff in back like “understanding databases”)
- Publisher: American Health Information Management Associ; 2 edition (December 1, 2013)
- Language: English
- ISBN-10: 1584264217
- ISBN-13: 978-1584264217
- Product Dimensions: 10.9 x 8.4 x 0.6 inches
A Practical Approach to Analyzing Healthcare Data is a 175 page (plus 50 more pages of appendices) full-sized (8.5×11) softcover. A this weight, I’m not sure if it has enough material to fill a semester length course by itself, but I would totally use it for a short course, or as supplement material.
- Introduction to Data Analysis
- Data in Healthcare
- Tools for Data Organization, Analysis, and Presentation
- Analyzing Categorical Variables
- Analyzing Continuous Variables
- Analyzing the Relationship Between Two Variables
- Sample Selections
- Exploratory Data Applications
- Benchmarking and Analyzing Externally Reported Data
If you are already familiar with some aspects of health care, health data, or statistical analysis, this book will be a quick read. In Chapters 1-6, You’ll learn what types of data there are in healthcare and (very importantly) where this data comes from and what it is used for. Dr. White then covers several common techniques for analyzing the data, and introduces a few typically available tools (like MS Excel and databases) that will help.
My favorite is the “Exploratory Data Applications” chapter. Here is where we shift gears from learning technical information about data and methods, to how we actually can use these methods to help increase the quality of health care being delivered. This is also where Dr. White’s rich expertise in healthcare shines. She brings the crucial contextual element to what would otherwise be just a bag of tools. She explains how we do (and more importantly why) charge analysis, how to analyze patterns of care, physician productivity, and others. This part of the book is hugely valuable to people interested in health care analytics.
People who are interested in learning how to do basic health data analytics. This book would be good for folks with a basic understanding of statistics. If you have never been exposed to mathematical formula notation or general statistical concepts from an intro course you might be doing a whole lot of Googling while reading this book. Although not required, the more comfortable you are with the health care environment and/or database concepts, the easier this book will be.
If you can’t tell already, I think this is a great book. However, it is not perfect. The Contents lists “About the Downloadable Resources” on page ix but instead of instructions to find the downloadable resources, page ix is the Foreword. I also wish there were more actual hands on exercises and cases within the text. The more ‘practical’ the text(as this one is named), the more I would expect lots of hands on exercises. Lastly, Dr. White’s very deep experience in revenue cycle shines through, I think at the expense giving the reader the opportunity to learn more about clinical data (you know: labs, problem lists, documentation, etc.) , as well as clinical quality measures. These topics are growing in importance to where they can’t be ignored.
This book is one of the best introductory texts out there specifically on practical, applied, health care analytics. It is short (ish) and sweet. I give it 4.5/5 stars.
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