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Healthcare Analytics Made Simple
Healthcare Analytics Made Simple

Healthcare Analytics Made Simple: Techniques in healthcare computing using machine learning and Python

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Healthcare Analytics Made Simple

Healthcare Foundations

This chapter is mainly aimed at developers who have limited experience of healthcare. By the end of it, you will be able to describe basic characteristics of healthcare delivery in the United States, you will be familiar with specific legislation in the US that is relevant to analytics, you will understand how data in healthcare is structured, organized, and coded, and you will be aware of frameworks for thinking about analytics in healthcare.

Healthcare delivery in the US

The healthcare industry impacts all of us, through its interactions with ourselves, our loved ones, our family, and our friends. The high costs associated with the healthcare industry are intertwined with the physical, emotional, and spiritual trauma that occurs when someone close to us becomes ill or feels pain.

In the United States, the healthcare system is in a fragile state, as healthcare expenditure exceeds 15% of the nation's total GDP; this proportion far exceeds that of other developed countries, and is expected to rise to at least 20% by the year 2040 (Braunstein, 2014; Bernaert, 2015). The rise in healthcare costs in the US, and internationally, can be attributed to several factors. One is a shift in demographics to a more elderly population. Average life expectancy (LE) rose to in excess of 80 years of age for the first time in 2011...

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Key benefits

  • Perform healthcare analytics with Python and SQL
  • Build predictive models on real healthcare data with pandas and scikit-learn
  • Use analytics to improve healthcare performance

Description

In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed. By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples.

Who is this book for?

Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.

What you will learn

  • Gain valuable insight into healthcare incentives, finances, and legislation
  • Discover the connection between machine learning and healthcare processes
  • Use SQL and Python to analyze data
  • Measure healthcare quality and provider performance
  • Identify features and attributes to build successful healthcare models
  • Build predictive models using real-world healthcare data
  • Become an expert in predictive modeling with structured clinical data
  • See what lies ahead for healthcare analytics

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 31, 2018
Length: 268 pages
Edition : 1st
Language : English
ISBN-13 : 9781787283220
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Product Details

Publication date : Jul 31, 2018
Length: 268 pages
Edition : 1st
Language : English
ISBN-13 : 9781787283220
Category :
Languages :
Concepts :

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Table of Contents

10 Chapters
Introduction to Healthcare Analytics Chevron down icon Chevron up icon
Healthcare Foundations Chevron down icon Chevron up icon
Machine Learning Foundations Chevron down icon Chevron up icon
Computing Foundations – Databases Chevron down icon Chevron up icon
Computing Foundations – Introduction to Python Chevron down icon Chevron up icon
Measuring Healthcare Quality Chevron down icon Chevron up icon
Making Predictive Models in Healthcare Chevron down icon Chevron up icon
Healthcare Predictive Models – A Review Chevron down icon Chevron up icon
The Future – Healthcare and Emerging Technologies Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4
(8 Ratings)
5 star 75%
4 star 0%
3 star 12.5%
2 star 12.5%
1 star 0%
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J. Weeks May 19, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great overview of several broad topics. The book was exceptionally well written in an easy to read and referencable manner. I would highly recommend the book to anyone new to the healthcare industry or interested in learning advanced analytics with Python.
Amazon Verified review Amazon
Dr. Burt Lesnick Aug 21, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The reader is taken on two parallel journeys through the intricacy of the US Healthcare environment and the practical tools for Analytics. Using simple data sets that can be downloaded from public sources, the text guides you through the application of the Python language (including base language and external libraries, such as pandas and scikit-learn), the SQL language, and machine learning algorithms.This book could be used by people with some confidence in their programming skills to learn independently. It could also be a textbook to guide those in a more structured tutorial program.Overall the text is well written, easy to follow and insightful about the benefits and pitfalls about applying modern analytics to the healthcare environment.Burt Lesnick, MDPast Medical Director, The Children's Care Network (A pediatric accountable care organization in Atlanta, GA)Regent at Large, American College of Chest Physicians
Amazon Verified review Amazon
Aalap Shah, MD Jan 17, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
As an anesthesiologist, I have found that our specialty has shifted from traditional experience and bench/lab research to data-drive approaches in optimizing our patients' outcomes. As more patients enter the US hospital systems, more and more data points are being combined to help establish trends and extrapolate future results.While I personally have limited experience with data mining at different institutions (e.g. SQL), this primer helps even the least computer-savvy person read between the lines of the data-heavy EHR. One can understand how data points can start to be manipulated for research or quality/process improvement purposes. The primer does a great job of address important and trendy topics in healthcare quality improvement by empowering the reader with the tools to create predictive models for outcomes, code and analyze diagnoses and sub-groups, and plot data in a way that C-Suite and physicians alike can appreciate and understand.Overall, a very thorough primer that flows well between the tenets of knowledge germane to medical specialties and helps to create a dialog between non-programming physicians and analysts seeking to improve the healthcare system.
Amazon Verified review Amazon
Lakshmi Jonnakoti Sep 01, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Dr. Vikram Kumar justified the title by making Data Science and computer fundamentals simple for healthcare professionals and healthcare simple for computer professionals. This is a must-have book for healthcare professionals to elevate current responsibilities and a good start for a career change aspirants from a non-healthcare background. We can easily resonate our experiences with examples narrated by Dr. Vikram Kumar. Highly recommend this book.
Amazon Verified review Amazon
DI Jul 07, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent book to learn and to apply ML in healthcare.It s very well writen, so everybody can understand. I used this book as guideline for my project.
Amazon Verified review Amazon
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