Improving Population Health Using Electronic Health Records
Methods for Data Management and Epidemiological Analysis
Electronic health records (EHRs) have become commonplace in the medical profession. Health data are readily captured and permanently stored in a digital fashion, and consequently, are increasingly being utilized in health research. The quality of this research depends upon the investigatorâ€™s ability to obtain the correct data to answer the correct question. It is easy to churn out poor quality research from the EHR; it is much harder to produce meaningful results that influence the populationâ€™s health.
Improving Population Health Using Electronic Health Records takes the reader through the process of conducting meaningful research from data in the EHR. It de-mystifies the entire research process, from how to ask the right kind of research questions, to obtaining data with particular emphasis on data management and manipulation, to performing a valid statistical analyses, and interpreting and presenting the results in a clear, concise fashion that has the potential to improve population health.
This book can be used as a hands-on how-to guide of performing research from EHR data in either a piece-meal fashion, selecting only the topics of greatest interest, or a complete guide to the entire research process.
Readers will benefit from the intuitive presentation of complex methods with a multitude of examples. It is invaluable reading for researchers and clinicians who are not otherwise familiar with the complexities of working with large data sets.
Table of Contents
Chapter 1. Research in the era of electronic health records
Chapter 2. How to use this book for research
Part I: Understanding the data
Chapter 3. Planning the research
Chapter 4. Accessing health data
Chapter 5. Organizing, merging, and linking data
Chapter 6. Data management and the research dataset
Part II: Conducting the research
Chapter 7. Study design and sampling
Chapter 8. Measures of frequency and risk
Chapter 9. Threats to validity
Chapter 10. The analytic dataset
Chapter 11. Epidemiological analysis I
Chapter 12. Epidemiological analysis II
Part III: Interpretation to implementation
Chapter 13. Interpreting the results
Chapter 14. Publication and presentation
Chapter 15. Improving population health
Neal D. Goldstein, is an infectious disease epidemiologist at Christiana Care Health System, Newark, Delaware, and holds a faculty appointment in the Dornsife School of Public Health at Drexel University, Philadelphia, Pennsylvania. He has an extensive experience in epidemiological analyses from secondary data sources, particularly electronic health records. His research spans several disciplines including vaccine-preventable diseases, sexual minority health, pediatric infectious diseases, and womenâ€™s health surrounding pregnancy. He also possesses a background in biomedical informatics with a detailed knowledge of hardware and software in the health-care domain. Most recently, he has focused on translational epidemiology, or moving from knowledge generation to application and advocacy. He writes a science blog, which is available at www.goldsteinepi.com/blog.