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 2021 dates: Live-stream, online training August 12-13, 2021; 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, 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 three 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 have a laptop with R and RStudio downloaded and installed prior to the first day of the training.
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 August 12-13, 2021 from 10am EDT - ~5pm EDT. Please note this training is not a self-paced, pre-recorded online training.
|Early-Bird Rate (through 6/15/21)||Regular Rate (6/16/21 - 8/5/21)||Columbia Discount*|
|Faculty/Academic Staff/Non-Profit Organizations||$975||$1,175||10% off|
*Columbia Discount: This discount is valid for any active student, postdoc, staff, or faculty at Columbia University. To accss the Columbia discount, email Columbia.EMR@gmail.com for instructions and specify if you are paying by credit card, or internal transfer within Columbia.
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 details.
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.