|7:30 – 8:30am
|8:00 – 8:30am
|8:30 – 10:00am
|Welcome to the journey: Overview of OHDSI : past, present, future
- Speaker: Patrick Ryan,PhD, Sr. Director and Head, Epidemiology Analytics, Janssen Research & Development
- Description: Observational Health Data Sciences and Informatics (OHDSI, pronounced “Odyssey”, http://ohdsi.org) is an international collaborative whose goal is to create and apply open-source data analytic solutions to a large network of health databases to improve human health and wellbeing. OHDSI’s mission is to transform medical decision making by creating reliable scientific evidence about disease natural history, healthcare delivery, and the effects of medical interventions through large-scale analysis of observational health databases. We will provide an overview of OHDSI’s focus to research, develop, and apply shared solutions for 3 key analytical use cases: clinical characterization, population-level estimation, and patient-level prediction. We will highlight the progress to date and provide a vision for how an open-science approach to evidence generation can accelerate observational research around the world.
|10:00 – 10:15am
|10:15 – 11:15am
|OHDSI in action: Real-world evidence for clinical characterization
- Speaker: George Hripcsak MD, MS, Chair of the Department of Biomedical Informatics at Columbia University Medical Center
- Description: The Observational Health Data Sciences and Informatics (OHDSI) collaboration created an international data network with hundreds of millions of patient records from countries on four continents. To characterize the diversity of populations and the variance in care, OHDSI studied treatment pathways for three common diseases. The time from envisioning the study to analyzing the results from the first seven sites was just three weeks. Heterogeneity among treatment pathways was studied, looking at country, type of practice, and type of record (health record versus claims data) as sources of variance. Trends in monotherapy were studied, as well as uniqueness of the pathways. Large-scale international observational research appears to be feasible.
|11:15 – 12:15pm
|OHDSI in action: Open-source analytics for patient-centered evidence
- Speaker: Jon Duke, MD, Senior Scientist, Regenstrief Institute
- Description: OHDSI’s mission is to transform medical decision-making by creating reliable scientific evidence from observational health data. Implicit in this mission is the translation of the knowledge generated by the OHDSI community into tools that benefit and inform patients and providers directly. In this session, we will introduce one such tool recently developed by the community that connects traditional health information resources with data generated by the OHDSI network. Specifically, we will delve into the drug product labeling for several commonly prescribed medications and show how OHDSI can complement and illuminate the safety information found in these important documents.
|12:15 – 2:45pm
|OHDSI collaborator showcase
- Poster session of OHDSI research
- OHDSI 101 and ETL 101 stations
- Software demonstrations of OHDSI open-source tools:
- HERMES for vocabulary exploration
HERMES (Health Entity Relationship and Metadata Exploration System) is a web based tool for searching and navigating the vocabulary within the OMOP Common Data Model (CDM). In addition to the search and navigation capabilities, HERMES also provides features to curate and export custom sets concept identifiers for use in cohort definitions.
Presenter: Frank DeFalco, Associate Director of Epidemiology Analytics, Janssen Research and Development
- CALYPSO for study population exploration
CALYPSO (Criteria Assessment Logic for Your Population Study in Observational data) is a web user interface to define, instantiate and evaluate a study population and the implications of inclusion criteria
Presenter: Christopher Knoll, Manager of Epidemiology Analytics, Janssen Research and Development
- CIRCE for cohort definition
CIRCE (Cohort Inclusion and Restriction Criteria Expression) is a cohort definition and syntax compiler tool for the latest version of the OMOP common data model
Presenter: Christopher Knoll, Manager of Epidemiology Analytics, Janssen Research and Development
- HERACLES for quality of care
HERACLES (Health Enterprise Resource And Care Learning Exploration System) is an application that allows you to explore healthcare quality, cost, and practice patterns using the OMOP Common Data Model. HERACLES provides high-level visualization tools and deep-dive capabilities to look at standardized quality metrics (e.g., NQF) as well as utilization across a variety of patient cohorts.
Presenter: Jon Duke, MD, Senior Scientist, Regenstrief Institute
- ACHILLES for data characterization
ACHILLES (Automated Characterization of Health Information at Large-scale Longitudinal Evidence Systems) is a platform which enables the characterization, quality assessment and visualization of observational health databases. ACHILLES provides users with an interactive, exploratory framework to assess patient demographics, the prevalence of conditions, drugs and procedures, and to evaluate the distribution of values for clinical observations.
Presenter: Lee Evans, Owner, LTS Computing LLC
- Methods Library
We are developing a library of open-source tools for large-scale analytics, including population-level estimation and patient-level prediction. Our population-level estimation work is focused on developing open-source software for safety surveillance and comparative effectiveness. Already available is a tool for new-user cohort studies using propensity and outcome models generated through large-scale regularized regressions. Still under development but soon available are tools for patient-level prediction and other study designs such as self-controlled case series and self-controlled cohorts, as well as tools for evaluating and calibrating population-level estimation methods
Presenters: Martijn Schuemie, PhD, Director of Epidemiology Analytics, Janssen Research and Development
Marc Suchard, MD, PhD, Professor, Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles
- Vocabulary Resources
The Standard Vocabulary is a foundational tool initially developed by some of us at OMOP that enables transparent and consistent content across disparate observational databases, and serves to support the OHDSI research community in conducting efficient and reproducible observational research.
Presenter: Christian Reich, MD, PhD, Vice President of Real World Evidence Systems, IMS Health
Nick Puntikov, CEO, Odysseus Data Services, Inc
- LAERTES Knowledge Base
Our knowledge base workgroup is developing an open-source repository of standardized evidence about drug-outcome relationships from disparate sources, including published literature, product labeling, spontaneous adverse event reporting, and existing bio-medical ontologies. The knowledge base will serve as the primary source to enable the construction of test cases (positive controls and negative controls) to facilitate systematic evaluation of method performance.
Presenter: Richard D. Boyce, PhD, Assistant Professor of Biomedical Informatics, University of Pittsburgh School of Medicine
- APHRODITE for phenotype development
APHRODITE (Automated PHenotype Routine for Observational Definition Identification Training and Evaluation). Typically, patient groups corresponding to a phenotype are selected by rule-based definitions, whose development is time-consuming. Machine learning approaches, which are an alternative approach for electronic phenotyping, are hampered by the paucity of manually labeled gold standard corpora for training. Aphrodite uses to OHDSI standard concept ids specific to the phenotype of interest to create “silver standard” training corpora to construct phenotype models. Aphrodite uses such silver standard corpora, in conjunction with expert knowledge codified in existing ontologies and a comprehensive representation of the patient clinical record, to learn phenotype models.
Presenter: Juan M. Banda, PhD, Postdoctoral Scholar – Center for Biomedical Informatics Research, Stanford University School of Medicine
During this time, lunch will be provided
|2:45 – 3:45pm
|Panel Discussion – Experiences from the OHDSI international data network
Description: A common data model (CDM) allows for the systematic analysis of disparate observational databases. The concept behind this approach is to transform data contained within disparate databases into a common format (data model), and then perform systematic analyses using a library of standard analytic routines that have been written based on the common format. The OHDSI data network has adopted the Observational Medical Outcomes Partnership (OMOP) CDM which currently covers over 600 million patients within 11 countries around the world. During this panel session we will hear from OHDSI data holders from America, Europe, Asia and Africa. Each panelist will share their perspectives on: (1) Why they chose to participate in the network (2) The benefits and challenges of the data network and (3) Shared strategies to make our collaboration stronger.Panelists:
- Christian Reich, MD, PhD, Vice President of Real World Evidence Systems, IMS Health
- Rae Woong Park, MD, PhD, Professor, Ajou University School of Medicine, South Korea
- Peter Rijnbeek, PhD Assistant Professor, Erasmus Medical Center
- Parsa Mirhaji, MD, PhD, Director of Clinical Research Informatics at Montefiore Healthcare System, Albert Einstein College of Medicine
- Paul Biondich, MD, Founder and President, OpenMRS
|3:45 – 4:00pm
|4:00 – 5:30pm
|Panel Discussion – The Value and Challenges of Evidence from Observational Data: A Multi-Stakeholder Perspective
Description: To close out the day, we want to hear back from the broader healthcare community. The aim of this panel is to give each stakeholder group an opportunity to share their perspectives about the OHDSI program and how OHDSI tools could benefit their work. This discussion will focus on:
(1) Multi-stakeholder perspectives on the current state of observational data use for generating evidence to support decision making
(2) The most immediate / largest needs that require evidence from observational data
(3) Reflections about the objectives of the OHDSI community and progress that has been made to date
(4) Key drivers within each stakeholder group which will enable reliable evidence generation from observational data
- Moderator: David Madigan, PhD, Executive Vice President and Dean of the Faculty of Arts and Sciences at Columbia University
- Robert Ball, MD, MPH, ScM, Deputy Director – Office of Surveillance and Epidemiology, CDER, US Food and Drug Administration
- Invited: Robert Califf, MD, Deputy Commissioner of Medical Products and Tobacco, US Food and Drug Administration
- Nareesa Mohammed-Rajput, MD, Medical Director of Clinical Informatics, Suburban Hospital part of Johns Hopkins Medicine
- Maryan Zirkle MD, MS, MA, Program Offier – CER Methods and Infrastructure Program, PCORI
- Lesley Wise, Vice President of PV Risk Management and Pharmacoepidemiology, Takeda Pharmaceuticals