Improving Population Health Using Big Data ─ 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 investigator’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 population’s health.

Improving Population Health Using Big Data 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.

Neal D. Goldstein is an infectious disease epidemiologist at Christiana Care Health System (Newark, DE) and holds a faculty appointment at Drexel University Dornsife School of Public Health (Philadelphia, PA). His research spans several disciplines including vaccine-preventable diseases, sexual minority health, pediatric infectious diseases, and women’s health surrounding pregnancy. He also possesses a background in biomedical informatics with detailed knowledge of hardware and software in the healthcare 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, and can be followed on Twitter (@goldsteinepi).