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Healthcare Analytics Made Simple

You're reading from   Healthcare Analytics Made Simple Techniques in healthcare computing using machine learning and Python

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Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781787286702
Length 268 pages
Edition 1st Edition
Languages
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Authors (2):
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Vikas (Vik) Kumar Vikas (Vik) Kumar
Author Profile Icon Vikas (Vik) Kumar
Vikas (Vik) Kumar
Shameer Khader Shameer Khader
Author Profile Icon Shameer Khader
Shameer Khader
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Healthcare Analytics 2. Healthcare Foundations FREE CHAPTER 3. Machine Learning Foundations 4. Computing Foundations – Databases 5. Computing Foundations – Introduction to Python 6. Measuring Healthcare Quality 7. Making Predictive Models in Healthcare 8. Healthcare Predictive Models – A Review 9. The Future – Healthcare and Emerging Technologies 10. Other Books You May Enjoy

Summary

In this chapter, we have taken a look at some prominent value-based programs that are shaping the US healthcare industry today. We have seen how these programs quantify provider performance through the use of measures. Additionally, we have downloaded the data for comparing dialysis facilities and hospitals and worked through some code examples in Python to see how to analyze this data.

One might argue that the analysis in this chapter could be accomplished by using a spreadsheet application such as Microsoft Excel rather than programming. In Chapter 7, Making Predictive Models in Healthcare, we will train predictive models on a healthcare dataset to predict discharge status in the ED. As you will see, this type of analysis almost certainly requires writing code.

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