Handbook of Data Analysis of Electronic Health Records (EHR) using SAS Software

$95.00$143.00

Behrouz Ehsani-Moghaddam, PhD – Adjunct Professor, Health Sciences, Queen’s University, ON Canada

Series: Health Care in Transition
BISAC: MED090000; MED051000; MED003100
DOI: 10.52305/BXKA2663

Electronic Health Records (EHR) are longitudinal data that are stored in a database that captures current and new patients at different points in time. Since EHR data come from multiple different vendors and open-source products, they can be messy, inconsistent, and often need to be harmonized and reformatted properly before they can provide real-world insights about patients using statistical techniques. This book goes beyond the general data manipulation, viewing the data analysis issues in a wider and more practical context. It covers all major steps of analysis of EHR data, even those instructions that cannot be taught in any classroom. The reader can have hands-on experience using the codes that are provided in the book and by utilizing the accompanying data that are available for free. This book is not restricted to one specific discipline but rather will be of interest to scientists working in any area where analyzing electronic public health data using SAS program is necessary. The material is aimed at the reader who are already familiar with applied statistics at an undergraduate level or higher.

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Table of Contents

Preface

About the Author

Part I: Basic Information about EHR Data and Data Manipulation

Chapter 1. EHR Observations

Chapter 2. Data Transfer from Database Management Systems to SAS

Chapter 3. Creating Temporary and Permanent Data Sets

Chapter 4. Retrieving Patient Information

Part II: Analysis of Longitudinal EHR Data

Chapter 5. Data Extraction from Text and Analysis: Adverse Events Following Immunization

Chapter 6. Prevalence Estimation for Acute Diseases (A Cross-Sectional Cohort Study)

Chapter 7. Prevalence Estimation for Chronic Diseases

Chapter 8. Disease Case Validation

Chapter 9. Multiple Logistic Regression

Chapter 10. Machine Learning for Medical Diagnoses

Index


Author’s ORCID iD

Behrouz Ehsani-Moghaddam 0000-0002-5038-1118