Electronic Medical Records Boot Camp

Over the last decade, Electronic Health Records (EHRs) and Electronic Medical Records (EMRs) systems have been increasingly implemented at US hospitals. Huge amounts of longitudinal and detailed patient information, including lab tests, medications, disease status, and treatment outcome, have been accumulated and are available electronically. Extensive effort has been dedicated to developing advanced clinical data processing and data management in order to integrate patient data into a computable collection of rich longitudinal patient profiles. EMR/EHRs provide unprecedented opportunities for cohort-wide investigations and knowledge discovery. They are important data resources for building predictive models for disease diagnosis and prognosis, thus enabling personalized medicine.

Despite the great potential, analyzing such large, scattered and heterogeneous observational patient data is still technically challenging. This two-day intensive workshop will go over opportunities and potentials of EMR/EHR for health and medical studies, statistical challenges and pitfalls for analyzing EMR/EHR, and the latest developments of multiple techniques to address those challenges, followed by hands-on computer lab sessions and case studies to put concepts into practice.

By the end of the electronic medical records training, participants will be familiar with the following topics:

• Power and potentials of EMR/EHR data
• Open-access datasets across the world
• Preparation, transformation and integration of EMR/EHR
• Confounding, bias and missing data in EMR/EHR and statistical methods addressing these challenges
• Statistical methods for comparative effectiveness
• Statistical methods for predictive analysis

Summer 2027: The EMR Boot Camp is a livestream, remote training that takes place over live, online video. Please note this training is not a self-paced, pre-recorded online training.

Investigators from any institution and from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are four requirements to attend this training:

1. Each participant must have an introductory background in statistics.
2. Each participant must be familiar with R.
3. Each participant must have a laptop/computer with latest versions of R and R-Studio downloaded and installed prior to the first day of the workshop. R and R-Studio are available for free download and installation on Mac, PC, and Linux devices.
4. Each participant will be required to apply for access to MIMIC-III data, requiring completion of specific HIPAA training to receive credentials.

Tian Gu, PhD, Department of Biostatistics, Columbia University. Dr. Gu is an Assistant Professor of Biostatistics whose research focuses on developing statistical methods for integrating and analyzing multi-site EHR-linked biobank data. Her methodological work spans transfer learning, federated learning, and synthetic-data-powered inference to improve risk prediction and statistical inference across healthcare systems and studies. She also develops methods that use large language model embeddings to enhance EHR-based disease prediction and integrates genetic and wearable device data to advance precision health.

Xu Shi, PhD, Department of Biostatistics, University of Michigan. Dr. Shi is an Associate Professor of Biostatistics whose research focuses on developing statistical methods for EHR and claims data. Her work advances causal inference using negative controls and the harmonization and analysis of multi-institutional EHR data to generate reliable real-world evidence. She co-leads the Causal Inference Core of the FDA’s Sentinel Initiative, developing methods to evaluate medical product effectiveness and safety. She developed a semester-long course on EHR data analysis at the University of Michigan and has taught related short courses at the Joint Statistical Meetings, the Deming Conference, and the New England Statistics Symposium.

Former Instructors

Shuang Wang, PhD, Department of Biostatistics, Columbia University. 

Ying Wei, PhD, Department of Biostatistics, Columbia University.

Training scholarships are not currently available for the Electronic Medical Records Boot Camp. 

"The instructors and TAs did a wonderful job in explaining the material!" - Staff Scientist at Cleveland Clinic Genomic Medicine Institute, 2025

"The EMR Boot Camp provided me with some excellent ways I can clean and analyze EMR data in my own role. The instructing team was very helpful." - Student at Boston University, 2025

"Excellent presentation of the coursework and well-put-together labs and lectures in the 2-day intensive." - Staff Member at Columbia University Medical Center, 2025

"This is very useful bootcamp for complicated analyses of EHR. I liked how the bootcamp went through the data cleaning , R codes for doing different types of analyses, and how they went through the codes step by step. The instructors went above and beyond and answered all the questions given the diverse background." - Faculty Member at University of California, 2024

"A very comprehensive overview of statistical and machine learning approaches used to analyze EHR data, applicable to trainees from various backgrounds." - Fellow at Children's Hospital of Philadelphia, 2023

"This is a very informative and rigorous boot camp which helps understand how to use EHR data for answering clinical questions." - Senior research associate at Illinois Institute of Technology, 2023

"It was a great workshop and I highly recommend to those working with health data." - Graduate research assistant at University of Nebraska Medical Center, 2023

Registration Fee is based on your category and includes course material, which will be made available to all participants both during and after the conclusion of the training. 

2025 Registration Category Rates:

• Student/Postdoc/Trainee:
  • Early-bird rate: $995
  • Regular rate: $1,195
• Faculty/Academic Staff/Non-Profit Organizations/Government Agencies:
  • Early-bird rate: $1,195
  • Regular rate: $1,395
• Corporate/For-Profit Organizations:
  • Early-bird rate: $1,395
  • Regular rate: $1,595

$200 early-bird discount is automatically applied if you register before the early-bird deadline. 

• $200 Early-bird Discount: This is automatically applied if you register before the June 15 early-bird deadline.  

• 10% Columbia Discount: This is valid for any active student, postdoc, staff, or faculty at Columbia University. If paying by credit card, use your Columbia email address during the registration process to automatically have the discount applied. If paying by internal transfer within Columbia, see below.  

• 10% Mailman Alumni Discount: This is valid for any individual who graduated from the Columbia University Mailman School of Public Health. To access the Mailman Alumni discount and receive a registration code, please email sharp_program@cumc.columbia.edu your graduation year and degree.  

• Group discounts are available for organizations sending 5+ participants. Please contact us directly at sharp_program@cumc.columbia.edu for more information.  

If paying by internal transfer within Columbia, submit this Columbia Internal Transfer Request form (link to form coming soon) to receive further instructions. Please note: filling out this form is not the same as registering for a training and does not guarantee a training seat.

If you would prefer to pay by invoice/check, please submit this Invoice Request form (link to form coming soon) to receive further instructions. Please note: filling out this form is not the same as registering for a training and does not guarantee a training seat.

Cancellation notices must be received via email at least 30 days prior to the training start date in order to receive a full refund, minus a $75 administrative fee. Cancellation notices received via email 14-29 days prior to the training will receive a 75% refund, minus a $75 administrative fee. Please email your cancellation notice to Columbia.EMR@gmail.com(link sends e-mail). Due to workshop capacity and preparation, we regret that we are unable to refund registration fees for cancellations less than 14 days prior to the training.

If you are unable to attend the training, we encourage you to send a substitute within the same registration category. Please inform us of the substitute via email at least one week prior to the training so we can include them on attendee communications, gather registration details, and provide materials.Should the substitute fall within a different registration category (e.g., you are a faculty member and they are a postdoc), the credit card on file will be credited/charged respectively. Please email substitute inquiries to Columbia.EMR@gmail.com(link sends e-mail). In the event Columbia must cancel the event, your registration fee will be fully refunded.