Event Phone: 1-610-715-0115

Cancellation Policy: If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 3-Day Livestream Seminar Taught by Jesse Gronsbell, Ph.D.

The widespread adoption of electronic health records (EHR) has generated massive amounts of clinical data with potential to improve healthcare delivery and advance biomedical research. EHRs contain comprehensive patient-level information collected over time, including demographics, disease diagnoses, medical procedures, and vital signs. Large scale EHR databases are also being increasingly linked across healthcare systems and to biobanks containing detailed genetic data to characterize individual health at unprecedented scale and precision.

However, EHR data is complex and heterogeneous. Effective data analysis requires a deep understanding of the data as well as familiarity with modern statistical and machine learning methods. This course will provide a broad overview of the analysis of EHR data for participants with little or no prior experience with the topic. We will start with the opportunities and challenges associated with the analysis of EHR data. We will then build an understanding of data provenance and structure. Finally, we will cover basic and advanced methods for EHR data analysis and their use in various research applications.

We will cover a full suite of methods for processing EHR data, developing phenotyping models, generating real-world evidence, and developing fair and privacy preserving predictive models. You will also be introduced to publicly available datasets, software packages for statistical analyses, and tools for clinical natural language processing. The course will be hands-on and use the R and Rstudio computing environment. After completing the course, you will be prepared to analyze your own EHR dataset and deepen your knowledge of the topic.