Chapter 1, Introduction to Healthcare Analytics, provides a definition of healthcare analytics, lists some foundational topics, provides a history of the subject, gives some examples of healthcare analytics in action, and includes download, installation, and basic usage instructions for the software in this book.
Chapter 2, Healthcare Foundations, consists of an overview of how healthcare is structured and delivered in the US, provides a background on legislation that's relevant to healthcare analytics, describes clinical patient data and clinical coding systems, and provides a breakdown of healthcare analytics.
Chapter 3, Machine Learning Foundations, describes some of the model frameworks used for medical decision making and describes the machine learning pipeline, from data import to model evaluation.
Chapter 4, Computing Foundations – Databases, provides an introduction to the SQL language and demonstrates the use of SQL in healthcare with a healthcare predictive analytics example.
Chapter 5, Computing Foundations – Introduction to Python, gives a basic overview of Python and the libraries that are important for performing analytics. We discuss variable types, data structures, functions, and modules in Python. We also give an introduction to the pandas and scikit-learn libraries.
Chapter 6, Measuring Healthcare Quality, describes the measures used in healthcare performance, gives an overview of value-based programs in the US, and demonstrates how to download and analyze provider-based data in Python.
Chapter 7, Making Predictive Models in Healthcare, describes the information contained in a publicly available clinical dataset, including downloading instructions. We then demonstrate how to make predictive models with this data, using Python, pandas, and scikit-learn.
Chapter 8, Healthcare Predictive Models – A Review, reviews some of the current progress being made in healthcare predictive analytics for select diseases and application areas by comparing machine learning results to those obtained by using traditional methods.
Chapter 9, The Future – Healthcare and Emerging Technologies, discusses some of the advances being made in healthcare analytics through using the internet, introduces the reader to deep learning techniques in healthcare, and states some of the challenges and limitations facing healthcare analytics.