OHDSI 2024 – OHDSI

2024 OHDSI Global Symposium

Oct. 22-24 • New Brunswick, N.J. • Hyatt Regency Hotel

The 10th annual OHDSI Global Symposium brought together more than 470 global collaborators for three days of sharing research, building new connections and pushing forward our mission of improving health by empowering a community to collaboratively generate the evidence that promotes better health decisions and better care.

This page will host all materials from OHDSI2024, including video presentations (when available) from the main conference and tutorials, slide decks, posters, demos and more.

State of the Community

Where Have We Gone and Where Are We Going?
(George Hripcsak, Columbia University)

Expand OHDSI Initiative for Eye Care and Ocular Imaging Challenge
(Amberlynn Reed, Natiional Eye Institute)

Titan Awards
(George Hripcsak, Columbia University & Marc Suchard, UCLA)

Plenary: Clinical Insights from LEGEND-T2DM

Introduction to LEGEND-T2DM
(Moderator: Aline Pedroso, Yale University)

Comparative Effectiveness of Second-line Antihyperglycemic Agents
(Arya Aminorroaya, Yale University)

Effectiveness of First-line Antihyperglycemia Agents
(Phyllis Thangaraj, Yale University)

Comparative Safety of SGLT2 for Risk of Diabetic Ketoacidosis
(Hannah Yang/Evan Minty, University of Calgary)

Comparative Safety of GLP1-RA and the Risk of Thyroid Tumors
(Daniel Morales, University of Dundee)

Plenary: Value Proposition for Participating in OHDSI Network Studies like LEGEND-T2DM

Introduction to OHDSI Evidence Network / Marketplace
(Moderator: Clair Blacketer, Johnson & Johnson)

Reflections from US Department of Veterans Affairs
(Scott Duvall, VA)

Reflections from SIDIAP (Spain)
(Talita Duarte-Salles, IDIAP)

Reflections from a Global Commercial Data Provider
(Atif Adam, IQVIA)

Plenary Q&A: Lessons Learned on LEGEND-T2DM Journey

Moderator: Fan Bu, University of Michigan

Panelists: LEGEND-T2DM co-authors

Plenary Panel: JACC-OHDSI Partnership

Moderators:
Nicole Pratt, University of South Australia
Marc Suchard, UCLA

Panelists:
Harlan Krumholz, Yale University
Seng Chan You, Yonsei University
Yuan Lu, Yale University

Collaborator Showcase Lightning Talks

Moderator: Linying Zhang, Washington University School of Medicine in St. Louis

1) The missing link: Cross-species EHR data linkage offers new opportunities for improving One Health (Kathleen Mullen, University of North Carolina)
2) Comparing probabilistic and rule-based phenotype algorithms for hypotension and angioedema to the experience observed in randomized clinical trials (Joel Swerdel, Johnson & Johnson)
3) Exploring the interplay between metabolic syndrome and brain volume in depression: Basis for Phenotype-

Based Classification (Sujin Gan, Ajou University)
4) Software demonstration: CohortConstructor – an R package to support cohort building pipelines (Edward Burn, University of Oxford)
5) A Oneshot and Lossless Federated Generalized Linear Mixed Effect Model (Jiayi Tong, Johns Hopkins University)
6) NCO-Calibrated DID Analysis: Addressing Unmeasured Confounding in Difference-in-Differences Analyses Using Negative Control Outcomes Experiments (Dazheng Zhang, University of Pennsylvania)
7) Health Trends Across Communities in Minnesota: a Statewide Dashboard Leveraging the OMOP CDM to Monitor the Prevalence of Health Conditions (Samuel Patnoe, HealthPartners Institute)
8) How Often: Large Scale Incidence Rate Calculation of Health Outcomes for Drugs Nested by Indication (Hsin Yi Chen, Columbia University)

Closing Talk: Collaborating on Evidence at Scale

Collaborating on Evidence at Scale
Patrick Ryan, Johnson & Johnson/Columbia University

Collaborator Showcase Posters & Lightning Talks

There were 136 accepted submissions for the 2024 Collaborator Showcase, including posters, software demos and the lightning talks you can find above. This research was both developed and peer-reviewed within the community, and it focuses on several pillars of OHDSI: data standards, methodological research, open-source development, clinical applications, and building community.

Please visit the link below to visit the posters, brief reports and other supplementary materials for our showcase submissions. Each submission will be profiled in the #OHDSISocialShowcase, so please make sure you follow OHDSI on Twitter/X, LinkedIn and Instagram.

Tutorials

An Introduction to the Journey from Data to Evidence Using OHDSI

The journey from data to evidence can be challenging alone but is greatly enabled through community collaboration. In this tutorial, the faculty will introduce you to OHDSI. Specifically, about the tools, practices, and open-science approach to evidence generation that the OHDSI community has developed and evolved over the past decade. Faculty will highlight the ways community individuals can participate as well as receive value from the community’s outputs. The course will include topics such as open community data standards – including the OMOP Common Data Model and OHDSI Standardized Vocabularies,

open-source analytic tools – including HADES and ATLAS, and the conduct of open network studies for methodological research & clinical applications.

Faculty:
Daniel Prieto-Alhambra, University of Oxford, Erasmus M.C.
Jenna Reps, Janssen Research & Development
Mui Van Zandt, IQVIA
Erica Voss, Janssen Research & Development
Linying Zhang, Washington University in St. Louis

Developing and Evaluating Your Extract, Transform, Load (ETL) Process to the OMOP CDM

The OMOP Common Data Model (CDM) has become one of the most widely used international health data standards. Standardizing data to the OMOP CDM requires development of an extract, transform, load (ETL) procedure that converts source data into the CDM structure while observing the appropriate conventions and adhering to the OHDSI standardized vocabularies. The OHDSI community maintains and provides resources for the OMOP CDM standard, Standardized Vocabularies, and THEMIS ETL conventions, and has developed a series of open-source analytic tools to support both ETL development

and evaluation (including WhiteRabbit, CDMInspection, and DataQualityDashboard).

In this tutorial, students will learn about the tools and practices developed by the OHDSI community to support the journey to establish and maintain an ETL to standardize your data to OMOP CDM and enable standardized evidence generation across a data network.

Faculty:
Clair Blacketer, Janssen Research & Development
Evannette Burrows, Janssen Research & Development
Melanie Philofsky, Odysseus Data Services, Inc.
Katy Sadowski, Boehringer Ingelheim

Using the OHDSI Standardized Vocabularies for Research

The OHDSI Standardized Vocabularies serves as a foundation to data standardization process within the OMOP CDM. It also can be tremendously useful tool for enabling the appropriate design of analyses that can be executed across a network of databases. A core component within essentially all analysis is the specification of phenotypes and associated code lists to represent exposures, outcomes, and other features. In this tutorial, students will learn how to take advantage of the OHDSI standardized vocabularies as an analytic tool to support your research, including searching for relevant clinical concepts, navigating concept relationships, creating Conceptsets and

understanding source codes that map within these expressions. Students will also learn where the OHDSI standardized vocabularies is used throughout OHDSI’s standardized analytic tools.

Faculty:

Anna Ostropolets, Janssen Research & Development
Vlad Korsik, Odysseus Data Services, Inc.
Azza Shoaibi, Janssen Research & Development
Polina Talapova, SciForce
Oleg Zhuk, Odysseus Data Services, Inc.

So, You Think You Want To Run an OHDSI Network Study?

Reliable real-world evidence generation requires appropriate analyses applied to data sources fit-for-purpose for the research question of interest. The OHDSI community has developed open-source standardized analytics tools that can be executed across a network of OMOP CDM databases and processes to facilitate collaborations between researchers throughout the evidence generation process from design through implementation and dissemination. In this tutorial, students will learn about the steps along the journey to turn your research question into reliable evidence and how to lead an OHDSI network study.

Faculty:
Yong Chen, University of Pennsylvania
Ben Martin, Johns Hopkins University
Nicole Pratt, University of South Australia
Anthony Sena, Janssen Research & Development
Andrew Williams, Tufts University
Seng Chan You, Yonsei University Health System

Conducting ‘Off-The-Shelf’ Characterization Studies Using DARWIN EU® Tools and the OMOP CDM

The European Medicines Agency (EMA) and the European Medicines Regulatory Network established the Data Analysis and Real-World Interrogation Network (DARWIN EU®) coordination center to provide timely and reliable evidence on the use, safety and effectiveness of medicines for human use, including vaccines, from real world healthcare databases across the European Union (EU). The DARWIN EU team has established a data network standardized to the OMOP CDM and has developed a series of open-source analytics tools that run atop the OMOP CDM to conduct characterization studies for

disease natural history, drug utilization, and treatment patterns. In this tutorial, students will learn from leaders in the DARWIN EU team about how to execute characterization analyses against their OMOP CDM instance using DARWIN EU packages, including how to define inputs to the standardized analytics and how to interpret standardized results. Students will also learn how DARWIN EU tools relate to and connect with OHDSI’s broader open-source analytics ecosystem.

Faculty:
Edward Burn, University of Oxford
Daniel Prieto-Alhambra, University of Oxford; Erasmus M.C.
Martí Català Sabaté, University of Oxford
Maarten van Kessel, Erasmus M.C.