Registration is open! Join us for the next live-stream Electronic Medical Records Boot Camp on June 29-30, 2022.
The Electronic Medical Records Boot Camp is a two-day intensive boot camp of seminars and hands-on analytical sessions to provide an overview of electronic health data opportunities, statistical challenges, and latest techniques.
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Summer 2022 dates: Live-stream, online training June 29-30, 2022; 10:00am - ~5:00pm EDT.
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
Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate.
There are four prerequisites and requirements to attend this training:
Each participant must have an introductory background in statistics.
Each participant must be familiar with R.
Each participant must be bring a laptop 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. Personal laptops will be used for multiple boot camp sessions.
Each participant will be required to apply for access to MIMIC-III data, requiring completion of specific HIPAA training to receive credentials.
Shuang Wang, PhD, Department of Biostatistics, Columbia University. Dr. Wang is Professor of Biostatistics in the department of Biostatistics at Mailman School of Public Health. Her research focuses on methodological development in observational studies using electronic health records data and multi-omics data, especially methods for multiple domain fusion or multi-omics integration.
Ying Wei, PhD, Department of Biostatistics, Columbia University. For the past decade Dr. Wei’s work has centered around innovative methods to maximize the potential of large-scale datasets such as electronic medical records. She has made several important contributions in developing models for pediatric growth charts and in developing statistical methods to handle measurement errors, missing data, and high-dimensional confounding rising from electronic medical records. Recently, she has been actively engaged in building analysis tools in bioinformatics and genetic research. For her contribution to nonparametric statistics and biostatistics, she received the Noether Young Scholar Award from the American Statistical Association in 2011, and was elected as an American Statistical Association Fellow in 2015. She is currently an Associate Editor for the Journal of American Statistical Association (JASA).
Training scholarships are available for the Electronic Medical Records Boot Camp.
COVID-19 Update: The EMR Boot Camp will not take place in person due to the COVID-19 pandemic. Instead, the Training will be a live-stream, remote training that takes place over live, online video on June 29-30, 2022 from 10am EDT - ~5pm EDT. Please note this training is not a self-paced, pre-recorded online training.
This bootcamp was helpful for understanding what kinds of clinical questions can be answered with large-scale EMR data. There were novel techniques introduced that I was not familiar with, and the code review was helpful for understanding how to implement them. - Non-profit staff member at Whitman-Walker Institute, 2021
The training materials (codings and books) are very practical. It inspires me to apply various analytical techniques in my EMR projects and produce better and more robust results. - Philip Y., Consultant, 2021
I was excited to learn new techniques and R packages for EMR analysis. - Michael B., Staff member at Michigan DHHS, 2021
The boot camp covered an impressive array of sophisticated inference and modeling techniques. I felt much more comfortable with complicated, multi-dimensional EHR data after this bootcamp. - Postdoc at Memorial Sloan Kettering Cancer Center, 2021
|Early-Bird Rate (through 4/15/22)||Regular Rate (4/16/22 - 6/15/22)||Columbia Discount*|
|Faculty/Academic Staff/Non-Profit Organizations/Government Agencies||$1,025||$1,225||10% off|
*Columbia Discount: This discount is valid for any active student, postdoc, staff, or faculty at Columbia University. To access the Columbia discount, email Columbia.EMR@gmail.com for instructions and specify the following: 1) your registration category from the table above, 2) if you are paying by credit card, or internal transfer within Columbia, and 3) if an internal transfer, indicate the registration category from the table above, and if grant funds are being used.
Invoice Payment and Group Registrations: If you would prefer to pay by invoice/check, or would like to pay for a group of registrants, please email Columbia.EMR@gmail.com with the following details: 1) full attendee name(s) and applicable registration category from the table above, and 2) payment method (credit card, invoice, wire).
Registration Fee: This fee includes course material, which will be made available to all participants both during and after the conclusion of the training.
Cancellations: 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. Due to workshop capacity and preparation, we regret that we are unable to refund registration fees for cancellations <14days 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 to include them on attendee communications, updated registration forms, and materials. Should the substitute fall within a different registration category your credit card will be credited/charged respectively. Please email substitute inquiries to Columbia.EMR@gmail.com. In the event Columbia must cancel the event, your registration fee will be fully refunded.
The Electronic Medical Records Boot Camp is hosted by Columbia University's SHARP Program at the Mailman School of Public Health.