2017 Event Page

Loading Map....

Date(s) - 10/18/2017 - 10/20/2017
12:00 am

Bethesda North Marriott

Categories No Categories


OHDSI’s mission is to improve health, by empowering a community to collaboratively generate the evidence that promotes better health decisions and better care. As a community we envision a world in which observational research produces a comprehensive understanding of health and disease. OHDSI promotes a collaborative approach to research and has rapidly grown into a vibrant international community. Everyone is welcome to actively participate in OHDSI, whether as a patient, a health professional, a researcher, or someone who simply believes in our cause

The third annual OHDSI symposium will promote this vision and provide OHDSI collaborators an opportunity to share our accomplishments with the broader healthcare community. The day will include a collaborator showcase involving a poster session to highlight OHDSI’s research achievements and interactive demonstrations of OHDSI’s open-source software tools that will revolutionize how medical evidence is generated.

The 2017 OHDSI symposium will take place on Wednesday, October 18th at the at the Bethesda North Marriott Hotel & Conference Center, located at 5701 Marinelli Rd, North Bethesda, MD 20852.

There is no fee to attend the symposium.

On October 19-20th, 2017 we will hold tutorial workshops. Please see the 2017 Tutorial Workshops tab to learn more about the workshops and topics.

Registration is separate for the symposium and the tutorials. 


Who Should Attend:

Stakeholders from the following organizations who would benefit from the presentations and discussions during and following this event, include but are not limited to:

  • AMIA, Technology and Software developers
  • Academia, Centers of Excellence
  • Groups involved in the discovery of new pathways for treatment of cancer and other diseases
  • Pharmaceutical and Device Industry
  • Health-care start-ups, Healthcare payers and providers
  • Clinicians, Patients, and Disease-focused Patient Advocates and Foundations
  • Data standardization organizations

Stakeholders include:

  • People most interested in addressing these issues, because they are the most directly affected by the problems.
  • Senior management interested in breaking the cycle


We are proud to announce some of the presenters for this year’s symposium:

Jon Duke, MD, MS
Senior Scientist and Director, Drug Safety Informatics Program
Regenstrief Institute

Dr. Duke is Chief Innovation Officer and Senior Research Scientist at the Regenstrief Center for Biomedical Informatics. He directs Regenstrief’s Drug Safety Informatics Lab and leads the Merck-Regenstrief Partnership for Healthcare Research and Innovation. Dr. Duke graduated from Harvard Medical School and completed his residency in internal medicine at Brigham and Women’s Hospital. He completed a National Library of Medicine fellowship in Medical Informatics and holds a master’s in Human-Computer Interaction. He is also fluent in Japanese and served as Fulbright Scholar to Japan.

Dr. Duke’s research focuses on applications of big data and human computer interaction to support medication safety. His projects range from predictive modeling of adverse drug events to advanced clinical decision support systems. He has spoken at the FDA on multiple occasions and has received an award for his research on visualization of drug safety information. Dr. Duke has also overseen the development of Regenstrief Institute’s next-generation EMR system and has spoken nationally and internationally on innovation in EMRs. Dr. Duke has been awarded over $15 million in grants and contracts from sources including the National Institutes of Health, National Science Foundation, and pharmaceutical and health IT industry partners. Dr. Duke’s research has resulted in numerous academic publications and been featured in a variety of popular media such as the New York Times, Consumer Reports, and National Public Radio.

George Hripcsak

George Hripcsak, MD, MS
Vivian Beaumont Allen Professor and Chair of Biomedical Informatics
Columbia University Medical Center

George Hripcsak, MD, MS, is Vivian Beaumont Allen Professor and Chair of Columbia University’s Department of Biomedical Informatics and Director of Medical Informatics Services for New York-Presbyterian Hospital/Columbia Campus. He is a board-certified internist with degrees in chemistry, medicine, and biostatistics. Dr. Hripcsak’s current research focus is on the clinical information stored in electronic health records and on the development of next-generation health record systems. Using nonlinear time series analysis, machine learning, knowledge engineering, and natural language processing, he is developing the methods necessary to support clinical research and patient safety initiatives. He led the effort to create the Arden Syntax, a language for representing health knowledge that has become a national standard, and he co-chaired the Meaningful Use Workgroup of HSS’s Office of the National Coordinator of Health Information Technology, which defined the criteria by which health care providers collect incentives for using electronic health records. Dr. Hripcsak chaired the National Library of Medicine’s Biomedical Library and Informatics Review Committee, and he is a fellow of the Institute of Medicine, the American College of Medical Informatics, and the New York Academy of Medicine. He has published over 250 papers.

Dr. Hripcsak serves as PI–with co-PI David Madigan–of OHDSI’s Coordinating Center, which is based at Columbia University. His recent pharmacovigilance research has included medication-wide association studies, which improve visualization and prediction by exploiting structural and functional relationships among medications, and next-generation phenotyping to better exploit electronic health record data for observational research.

Peter Rijnbeek

Yeesuk Kim, MD, PhD
Associate Professor, Department of Orthopaedic Surgery
College of Medicine, Hanyang University

Dr. Kim is an orthopaedic surgeon of Hanyang university hospital in Korea and his subspeciality is adult reconstruction. Also, he is a chief director of Hanyang University Medical Information Center and also involved in Department of Biomedical Engineering in Hanyang University. He has about 30 publications and is interested in clinical informatics and artificial intelligence in medial fields. As a visiting scholar, he has joined in prof. Suchard’s laboratory in UCLA from 2017 to 2018.

He has been awarded the academic prizes from Korean hip society(2009, 2011) and from Korean orthopaedic association(2012), and is a winner of SOS challenge in 2017.


Patrick RyanPatrick Ryan, PhD

Sr. Director and Head, Epidemiology Analytics
Janssen Research and Development

Patrick Ryan, PhD is Senior Director of Epidemiology and the Head of Epidemiology Analytics at Janssen Research and Development, where he is leading efforts to develop and apply analysis methods to better understand the real-world effects of medical products. He is currently a collaborator in Observational Health Data Sciences and Informatics (OHDSI), a multi-stakeholder, interdisciplinary collaborative to create open-source solutions that bring out the value of observational health data through large-scale analytics. He served as a principal investigator of the Observational Medical Outcomes Partnership (OMOP), a public-private partnership chaired by the Food and Drug Administration, where he led methodological research to assess the appropriate use of observational health care data to identify and evaluate drug safety issues.

Patrick received his undergraduate degrees in Computer Science and Operations Research at Cornell University, his Master of Engineering in Operations Research and Industrial Engineering at Cornell, and his PhD in Pharmaceutical Outcomes and Policy from University of North Carolina at Chapel Hill. Patrick has worked in various positions within the pharmaceutical industry at Pfizer and GlaxoSmithKline, and also in academia at the University of Arizona Arthritis Center.

Marc SuchardMarc Suchard, MD, PhD
Professor, Department of Biomathematics, David Geffen School of Medicine
University of California, Los Angeles

Dr. Suchard is in the forefront of high-performance statistical computing. He is a leading Bayesian statistician who focuses on inference of stochastic processes in biomedical research and in the clinical application of statistics. His training in both Medicine and Applied Probability help bridge the gap of understanding between statistical theory and clinical practicality. He has been awarded several prestigious statistical awards such as the Savage Award (2003), the Mitchell Prize (2006 and 2011), as well as an Alfred P. Sloan Research Fellowship (2007) in computational and molecular evolutionary biology and a Guggenheim Fellowship (2008) to further computational statistics. He recently received the Raymond J. Carroll Young Investigator Award (2011) for a leading statistician within 10 years post-Ph.D., and in 2013 he was honored with the Committee of Presidents of Statistical Societies (COPSS) Presidents’ Award for outstanding contributions to the statistics profession by a person aged 40 or under. He is an elected Fellow of the American Statistical Association.


The agenda is available to download here:
2017 OHDSI Symposium


This year we will be offering tutorial workshops that will take place on October 19-20th, 2017 at the Bethesda North Marriott Hotel and Conference Center. Tutorial attendance is limited and you will be notified by September 7th, 2017 if you have been accepted into the workshop. You may register for one or two workshops, one on each day.

For workshops 2-4, you must have the prerequisites listed in order to register for the workshop. Below are the course prerequisites that will help you determine if you are a good fit for the course:




Topic:                        OMOP Common Data Model and Standardized Vocabularies

Faculty:                     George Hripcsak, Christian Reich, Erica Voss, Karthik Natarajan, Mark Velez, Mui Van Zandt, Rimma Belenkaya

Faculty:                      Don O’Hara, Michael Goodman, Gowtham Rao, Dmytry Dymshyts, Don Torok, Clair Blacketer

Target Audience:      Data holders who want to apply OHDSI’s data standards to their own observational datasets and researchers who want to be aware of OHDSI’s data standards so they can leverage data in OMOP CDM format for their own research purposes.

 Prerequisites:          None 

Date:                        October 19th, 2017


Topic:                         Population-Level Estimation

Faculty:                      Patrick Ryan, Marc Suchard, Martijn Schuemie, Christophe Lambert

Target Audience:        Researchers who want to design estimation studies for safety surveillance and comparative effectiveness using the OHDSI tools and programmers who want to implement and execute estimation studies using the OHDSI methods library

 Prerequisites:            Knowledge of OMOP CDM and Vocabularies and either epidemiologic knowledge, understanding of how to define cohorts or R programming skills   Date:                           October 19th, 2017



Topic:                         OHDSI Development Architecture

Faculty:                      Frank DeFalco, Sigfried Gold, Gregory Klebanov, Lee Evans

Target Audience:       Software developers who want to contribute to open-source analytics development to enhance OHDSI’s mission

 Prerequisites:            Knowledge of OMOP CDM and Vocabularies; Web-programming skills Date:                          October 20th, 2017



Topic:                         Patient-Level Prediction

Faculty:                      Peter Rijnbeek, Jenna Reps, Joel Swerdel

Target Audience:       Researchers who want to design prediction studies for precision medicine and disease interception using the OHDSI tools and programmers who want to implement and execute prediction studies using the OHDSI methods library.

 Prerequisites:           Knowledge of OMOP CDM and Vocabularies and either epidemiologic knowledge, understanding of how to define cohorts or R programming skills Date:                          October 20th, 2017



OHDSI’s mission is to improve health, by empowering a community to collaboratively generate the evidence that promotes better health decisions and better care. We envision a world in which observational research produces a comprehensive understanding of health and disease. To achieve this goal, the OHDSI team has formed a multi-stakeholder, interdisciplinary collaborative which aims to bring out the value of health data through large-scale analytics and open-source software tools. OHDSI has established a global community of observational health researchers and a research network covering over 600 million patients.

OHDSI collaborators are invited to submit to showcase their work during the OHDSI Symposium Collaborator Showcase on October 18th, 2017.  There are four ways to participate. Multiple submissions are welcome but only one abstract is required per research topic. This means that for each research topic you’d like to present, you only need to submit one abstract and indicate all the mediums which you would like to present in.

  1. Poster: a poster-board to present a static display summary of your latest research.
  2. Software Demonstration: a table with screen/monitor to provide interactive display of open-source analytics.
  3. Video: a 10-minute recorded content, to be run with other accepted videos and posted at ohdsi.org
  4. Lightning talk: a 7-minute podium presentation to verbally share your story with the community.

For accepted software demonstrations, a table and monitor will be provided for you at the symposium. For accepted video submissions, if your video is in your native language, it is suggested that your video contain English subtitles.

Abstracts will be peer-reviewed by the OHDSI Symposium Organizing Committee, and selected for presentation by September 25th, 2017.  Those collaborators will then showcase their work at the OHDSI Symposium on October 18th, 2017.


– Observational data standards and management

– Methodological research

– Open-source analytics development

– Clinical research from OHDSI’s analytic use cases:

– Clinical characterization

– Population-level estimation

– Patient-level prediction