Big Data in Healthcare: Statistical Analysis of the Electronic Health Record

Farrokh Alemi

• Publisher: ACHE Learn
• Year: 2020
• Topic: Business
• eBook ISBN:
  9781640550667
• Subtopic: Pharmaceutical, Biotechnology & Healthcare Industry
• Index: Business

Big Data in Healthcare: Statistical Analysis of the Electronic Health Record provides the statistical tools that healthcare leaders need to organize and interpret their data. Designed for accessibility to those with a limited mathematics background, the book demonstrates how to leverage EHR data for applications as diverse as healthcare marketing, pay for performance, cost accounting, and strategic management. Topics include: using real-world data to compare hospitals' performance; measuring the prognosis of patients through massive data; distinguishing between fake claims and true improvements; comparing the effectiveness of different interventions using causal analysis; benchmarking different clinicians on the same set of patients, and more. This book can be used in introductory courses on hypothesis testing, intermediate courses on regression, and advanced courses on causal analysis. It can also be used to learn SQL language. Its extensive online instructor resources include course syllabi, PowerPoint and video lectures, Excel exercises, individual and team assignments, answers to assignments, and student-organized tutorials. Big Data in Healthcare applies the building blocks of statistical thinking to the basic challenges that healthcare leaders face every day. Prepare for those challenges with the clear understanding of your data that statistical analysis can bring—and make the best possible decisions for maximum performance in the competitive field of healthcare.

Table of contents

• Cover Page
• Title Page
• Copyright Page
• Dedication
• Brief Contents
• Detailed Contents
• Acknowledgments
• Chapter 1. Introduction
• Chapter 2. Preparing Data Using Structured Query Language (SQL)
• Chapter 3. Introduction to Probability and Relationships
• Chapter 4. Distributions and Univariate Analysis
• Chapter 5. Risk Assessment: Prognosis of Patients with Multiple Morbidities
• Chapter 6. Comparison of Means
• Chapter 7. Comparison of Rates
• Chapter 8. Time to Adverse Events
• Chapter 9. Analysis of One Observation per Time Period: Tukey's Chart
• Chapter 10. Causal Control Charts
• Chapter 11. Regression
• Chapter 12. Logistic Regression
• Chapter 13. Propensity Scoring
• Chapter 14. Multilevel Modeling: Intercept Regression
• Chapter 15. Matched Case Control Studies
• Chapter 16. Stratified Covariate Balancing
• Chapter 17. Application to Benchmarking Clinicians: Switching Distributions
• Chapter 18. Stratified Regression: Rethinking Regression Coefficients
• Chapter 19. Association Network
• Chapter 20. Causal Networks
• Index
• About the Author
• About the Contributors