COVID-19 UPDATE: THE 2020 Electronic medical records boot camp has unfortunately been canceled. We hope you join us when this training will resume in NYC in summer 2021.
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 opportunities of electronic health data, statistical challenges, and latest techniques.
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Summer 2020 dates: Due to COVID-19, this training has been rescheduled for summer 2021.
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 multiple techniques with their latest development 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 to attend this training:
- Each participant must have an introductory background in statistics.
- Each participant must be familiar with R.
- Each participant must bring a laptop with R downloaded and installed prior to the first day of the training.
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 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.
The Electronic Medical Records Boot Camp will take place on the Columbia University Irving Medical Campus (CUIMC) in New York City, specifically at Columbia Mailman School of Public Health, 722 W. 168th Street, Allan Rosenfield Building 8th Floor Auditorium. Please note that the entrance to the building is on the 10th floor (training is located two floors below entrance).
General transportation and lodging information can be found in the Getting Around section. A PDF map of the Workshop location on the CUIMC campus will be available closer to training dates.
|Early-Bird Rate (through 6/15/20)||Regular Rate (6/16/20 - 8/10/20)||Columbia Discount*|
|Faculty/Academic Staff/Non-Profit Organizations||$1,350||$1,550||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, breakfast, lunch, and refreshment breaks. Course material will be provided to all participants after the workshop. Lodging and transportation are not included.
Cancellations: Cancellation notices must be received via email at least 30 days prior to the workshop start date in order to receive a full refund, minus a $75 administrative fee to cover the processing fee associated with your initial registration. Cancellation notices received via email 14-29 days prior to the workshop will receive a 75% refund, minus a $75 administrative fee. Please email your cancellation notice to Columbia.EMR@gmail.com. Due to workshop capacity, we regret that we are unable to refund registration fees for cancellations after these dates, unless a new COVID-19 restriction is implemented that impedes attendance. 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 rare event Columbia must cancel the event, your registration fee will be fully refunded.