About Us

Important:

These original OMOP resources are no longer supported. You can find the latest developments by visiting the OHDSI website.



History

During it's years as an active project, OMOP has demonstrated the feasibility of establishing a common infrastructure which can accommodate observational data of different types (both claims and EHRs) from sources around the world, and successfully developed and executed large-scale statistical analyses capable of enabling active drug safety surveillance across prescription medications.


Background

America’s drug-approval process has set the global standard for rigorous safety and effectiveness review, but even with clinical trials and other safeguards, it is impossible to fully understand the impact of any particular medical intervention until it is widely used. Once on the market, drugs are further studied by pharmacoepidemiologists and other researchers, who work diligently to identify safety issues and potential unanticipated benefits. Many important discoveries have been made, but researchers were always hampered by a reliance on voluntary reporting as the primary source of data. As a result, there is growing interest to use other sources of data generated within the healthcare setting. Unlike clinical trials, the use of observational data and methods to monitor medical product safety is challenged by the lack of accepted research methods and practices, leading to the well-known phenomenon of multiple studies of the same intervention yielding vastly different results.


OMOP’s Challenge

In 2007, recognizing that the increased use of electronic health records (EHR) and availability of other large sets of marketplace health data provided new learning opportunities, Congress directed the FDA to create a new drug surveillance program to more aggressively identify potential safety issues. The FDA launched several initiatives to achieve that goal, including the well-known Sentinel program to create a nationwide data network.

In partnership with PhRMA and the FDA, the Foundation for the National Institutes of Health (FNIH) launched the Observational Medical Outcomes Partnership (OMOP), a public-private partnership. This interdisciplinary research group has tackled a surprisingly difficult task that is critical to the research community’s broader aims: identifying the most reliable methods for analyzing huge volumes of data drawn from heterogeneous sources.

Employing a variety of approaches from the fields of epidemiology, statistics, computer science and elsewhere, OMOP seeks to answer a critical challenge: what can medical researchers learn from assessing these new health databases, could a single approach be applied to multiple diseases, and could their findings be proven? Success would mean the opportunity for the medical research community to do more studies in less time, using fewer resources and achieving more consistent results. In the end, it would mean a better system for monitoring drugs, devices and procedures so that the healthcare community can reliably identify risks and opportunities to improve patient care.


OMOP’s Work

Officially launched in late 2008 as a two-year pilot, OMOP worked to design experiments testing a variety of analytical methodologies in a range of data types to look for drug impacts that are already well-known. The initial findings were inconclusive, and the team found more challenges than answers.

From this initial base, the project moved forward with additional research, and found greater success. Over the course of 2011 and 2012, research yielded greater confidence that particular methods used with particular types of data can reliably identify correlations between individual medical interventions and specific health outcomes. While there is still work to be done, the findings suggest meaningful progress toward the ultimate goal.


OMOP’s Future

Having achieved its mission as envisioned by the founding members of the partnership, the OMOP Partnership concluded at FNIH in June. The OMOP research investigators have formed a new collaborative, the Observational Health Data Sciences and Informatics OHDSI to continue its mission of developing tools and evidence to support the appropriate analysis of observational data.

Research Investigators

William DuMouchel, PhD

Chief Statistical Scientist, Oracle Health Sciences

Bill's current research focuses on statistical computing and Bayesian hierarchical models, including applications to meta-analysis and data mining. He is the inventor of the empirical Bayesian data mining algorithm known as Gamma-Poisson Shrinker (GPS) and its successor MGPS, which have been applied to the detection of safety signals in databases of spontaneous adverse drug event reports. These methods are now used within the FDA and industry. From 1996 through 2004 he was a senior member of the data mining research group at AT&T Labs. Before that, he was Chief Statistical Scientist at BBN Software Products, where he was lead statistical designer of software advisory systems for experimental design and data analysis called RS/Discover and RS/Explore. He has been on the faculties of the University of California at Berkeley, the University of Michigan, MIT, and most recently was Professor of Biostatistics and Medical Informatics at Columbia University from 1994-1996. He has authored approximately fifty papers in peer-reviewed journals and has also been an associate editor of the Journal of the American Statistical Association, Statistics in Medicine, Statistics and Computing, and the Journal of Computational and Graphical Statistics.

Abraham G. Hartzema PharmD, MSPH, PhD, FISPE

Professor and Eminent Scholar, Perry A. Foote Chair in Health Outcomes and Pharmacoeconomics
Professor, Department of Epidemiology and Biostatistics, College of Public Health and Health Professions, University of Florida

Dr. Hartzema investigates health outcomes with an emphasis on pharmacoepidemiology, passive and active drug safety surveillance systems, therapeutic risk management, and program evaluation. He has served as principal and co-investigator on major grants from the National Institutes of Health, government entities, foundations and the pharmaceutical industry. He has co-authored and edited three books, two of which are in multiple editions, two monographs, one of which is translated in several languages, and has published and presented more than 100 chapters, journal articles, abstracts and presentations. He has served on the Scientific Board of the International Pharmaceutical Federation, and serves or served on eight editorial boards. He is the recipient of the 2007 UF Foundation research Award. He is an elected Fellow of the International Society for Pharmacoepidemiology. In 2008-2009, he spent his sabbatical in the Immediate Office of the Food and Drug Administration’s Commissioner working on the Sentinel system.

David Madigan, PhD

Executive Vice President for Arts and Sciences and Dean of the Faculty of Arts and Sciences, Columbia University

Dr. Madigan received a bachelor’s degree in Mathematical Sciences and a Ph.D. in Statistics, both from Trinity College Dublin. He has previously worked for AT&T Inc., Soliloquy Inc., the University of Washington, Rutgers University, and SkillSoft, Inc. He has over 100 publications in such areas as Bayesian statistics, text mining, Monte Carlo methods, pharmacovigilance and probabilistic graphical models. He is an elected Fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He recently completed a term as Editor-in-Chief of Statistical Science.

Marc Overhage, MD, PhD

Chief Medical Informatics Officer, Siemens Health Services

Prior to joining Siemens where he leads product strategy and research, Dr. Overhage was the founding Chief Executive Officer of the Indiana Health Information Exchange and was Director of Medical Informatics at the Regenstrief Institute, Inc., and a Sam Regenstrief Professor of Medical Informatics at the Indiana University School of Medicine. He has spent over 25 years developing and implementing scientific and clinical systems and evaluating their value. With his colleagues from the Regenstrief Institute, he created a community wide electronic medical record (Indiana Network for Patient Care) containing data from many sources including laboratories, pharmacies, physician practices and hospitals in central Indiana. In order to create a sustainable financial model, he helped create the Indiana Health Information Exchange, a not-for-profit corporation. He has developed and evaluated clinical decision support including inpatient and outpatient computerized physician order entry and the underlying knowledge bases to support them.

Over the last decade, Dr. Overhage has played a significant regional and national leadership role in advancing the policy, standards, financing and implementation of health information exchange. He serves on the Health Information Technology Standards Committee and the Board of Directors of the National Quality Form as well as being engaged in a number of national healthcare initiatives. He is a member of the Institute of Medicine, a fellow of the American College of Medical Informatics and the American College of Physicians. He received the Davies Recognition Award for Excellence in Computer-Based Patient Recognition for the Regenstrief Medical Record System. Dr. Overhage was a resident in internal medicine, a medical informatics and health services research fellow and then chief medical resident at the Indiana University School of Medicine. He practiced general internal medicine for over 20 years including the ambulatory, inpatient and emergency care settings.

Christian Reich, MD, PhD

Global Head of Informatics, AstraZeneca PLC

Christian has more than 15 years of experience in life science research and medicine. He was a practicing physician in Berlin and Ulm, Germany before moving to the European Bioinformatics Institute to work on the Human Genome Project. He then joined the biotech industry in 1998, where he worked in various positions on typical challenges in drug research and development, such as gene sequence and expression analysis, clinical trial design and analysis, systems biology, and outcome research, applying computational methods to large scale biological data. Christian is the Head of Discovery Informatics at AstraZeneca. He received his bachelor’s degree in preclinical training from Humboldt University in Berlin and holds his M.D. and doctorate from the Medical University of Lübeck, Germany where he focused his research on T-cell activation and regulation.

Patrick Ryan, PhD

Head of Epidemiology Analytics, Janssen Research and Development

Dr. Ryan is leading efforts at Janssen to develop and apply analysis methods to better understand the real-world effects of medical products. As part of OMOP, he is conducting 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.

Martijn Schuemie, PhD

Associate Director, Epidemiology Analytics at Janssen Research and Development

Dr. Schuemie received his Master’s degree in Economics from the Erasmus University in Rotterdam, and his PhD in informatics from the Delft University of Technology. His past research includes phobia treatment using virtual reality, and text-mining in scientific literature. More recently, his work at the Erasmus University Medical Center is focused on the re-use of EHRs for research. He was one of the principal investigators of the EU-ADR project, heading the development and comparison of statistical methods for signal detection using EHRs, and developed techniques for text-mining patient records.

Paul Stang, PhD

Senior Director, Epidemiology, Janssen Research and Development

Dr. Stang has held a number of positions over the past 25 years in epidemiology and pharmacoepidemiology including the past 5 years as Senior Director of Epidemiology at Janssen Research and Development. Previously, he was a Vice-President at Cerner Corporation, which he joined after co-founding and serving as the Chief Scientific Officer of Galt Associates, a health care consulting and informatics start-up that was acquired by Cerner. He previously served in positions at other health care companies and academic medical centers including SUNY-Stony Brook Department of Neurosurgery, and the UNC Department of Neurosurgery.

Marc Suchard, MD, PhD

Professor, University of California, Los Angeles

Marc 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 2003 Savage Award, the 2006 Mitchell Prize, as well as a 2007 Alfred P. Sloan Research Fellowship in computational and molecular evolutionary biology and a 2008 Guggenheim Fellowship to further computational statistics. Recently, he received the 2011 Raymond J. Carroll Young Investigator Award for a leading statistician within 10 years post-Ph.D. He is an elected Fellow of the American Statistical Association.

Staff