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Weekly OHDSI Digest - June 24, 2024

WEEKLY COMMUNITY CALL MEETING

Please join us Tuesday, June 25 (11 am ET), for a session focused on recent publications that have come out of the OHDSI community. We will hear from the following lead authors about studies that highlight either OMOP or OHDSI tools/practices:

• Nhung Trinh, Researcher, University of Oslo

Effectiveness of COVID-19 vaccines to prevent long COVID: data from Norway (The Lancet Respiratory Medicine)

• Theresa Burkard, Postdoctoral Data Scientist, University of Oxford

Calculating daily dose in the Observational Medical Outcomes Partnership Common Data Model (Pharmacoepidemiology & Drug Safety)

• Egill Fridgeirsson, Scientific Researcher, Erasmus MC

Comparing penalization methods for linear models on large observational health data (JAMIA)

• Cindy Cai, Assistant Professor of Ophthalmology, Johns Hopkins University

Similar Risk of Kidney Failure among Patients with Blinding Diseases Who Receive Ranibizumab, Aflibercept, and Bevacizumab: An Observational Health Data Sciences and Informatics Network Study (Ophthalmology Retina)

Everybody is invited. Calendar invites went out last week. If you did not receive one, please use this link to join the meeting. All recordings from these weekly calls are available within our Teams environment and will be posted on both our YouTube page and our OHDSI.org Community Calls page.

WEEKLY WORKING GROUP MEETINGS

Upcoming Workgroup Calls – OHDSI

OHDSI SHOUTOUTS

Congratulations to the team of Nora Tabea Sibert, Johannes Soff, Sebastiano La Ferla, Maria Quaranta, Andreas Kremer, Christoph Kowalski on the publication of Transforming a Large-Scale Prostate Cancer Outcomes Dataset to the OMOP Common Data Model—Experiences from a Scientific Data Holder’s Perspective in Cancers.

• Congratulations to the team of Egill A Fridgeirsson, Ross Williams, Peter Rijnbeek, Marc Suchard, and Jenna Reps on the publication of Comparing penalization methods for linear models on large observational health data in JAMIA.

• Congratulations to the team of Katja Hoffmann, Igor Nesterow, Yuan Peng, Elisa Henke, Daniela Barnett, Cigdem Klengel, Mirko Gruhl, Martin Bartos, Frank Nüßler, Richard Gebler, Sophia Grummt, Anne Seim, Franziska Bathelt, Ines Reinecke, Markus Wolfien, Jens Weidner, and Martin Sedlmayr on the recent publication of Streamlining intersectoral provision of real-world health data: a service platform for improved clinical research and patient care in Frontiers of Medicine.

• Congratulations to the team of Nicolas Alexander Schulz, Jasmin Carus, Alexander Johannes Wiederhold, Ole Johanns, Frederik Peters, Natalie Rath, Katharina Rausch, Bernd Holleczek, Alexander Katalinic, the AI-CARE Working Group & Christopher Gundler on the recent publication of Learning debiased graph representations from the OMOP common data model for synthetic data generation in BMC Medical Research Methodology.

OHDSI UPDATES

Thank you to everybody who shared brief reports for the 2024 Global Symposium. We had more than 140 submissions this year, including more than 20 software demos. The review process will begin this week when the scientific review committee meets this Thursday at 11 am ET.

• To carry out the OHDSI mission, we need an active and willing global network of data partners, and we need the ability to quickly identify those that might be the right fit for a specific clinical research question. Last year we piloted this effort through the Save our Sisyphus challenge and are now ready to move forward based on our learnings. The OHDSI Evidence Network workgroup is excited to initiate a network study that will describe the OHDSI Network in a publication, and will also create an open public resource designed to facilitate evidence generation faster and better than ever by building on methodologies developed by thought leaders around the world. You can access the protocol here, and you can learn more about this effort from a recent OHDSI Evidence Network update. Come join us on this exciting journey!

• The next edition of the CBER BEST Seminar Series will be held Wednesday, June 26, at 11 am ET. Jenna Wong, Assistant Professor in the Department of Population Medicine at Harvard Medical School and Harvard Pilgrim Health Care Institute, will lead a session on Applying Machine Learning in Distributed Networks to Support Activities for Post-Market Surveillance of Medical Products: Opportunities, Challenges, and Considerations. The full schedule for the CBER BEST Seminar Series, including past presentations, is available here.

• The July 2 community call will be our annual “Newcomer Introductions” session. We invite any of our newer members of the OHDSI community to join the call, introduce themselves and share about how they hope to collaborate with the community. To ensure the opportunity to take part in this session, please fill out this brief form.

• The workshop on “AI for Reliable and Equitable Real-World Evidence Generation in Medicine” at the International Conference on Artificial Intelligence in Medicine (AIME) will take place on July 9, 2024 at Salt Lake City, Utah. The workshop focuses on advancing the understanding and exploring the transformative role of artificial intelligence (AI) in analyzing real-world data (RWD) for real-world evidence (RWE) generation. Speakers and panelists from informatics, biostatistics, computer science, and related fields across academic institutions, federal agencies, and healthcare providers will be joining us for the workshop.

OHDSI GLOBAL SYMPOSIUM

Registration is now open for the 2024 Global Symposium , which will be held Oct. 22-24 at the Hyatt Regency Hotel in New Brunswick, N.J., USA. The three-day event will feature tutorials on Day 1, plenaries and the collaborator showcase on Day 2, and workgroup activities on Day 3.

• Day 1 will open with a single tutorial in the morning: An Introduction to the Journey from Data to Evidence using OHDSI. There will be four advanced tutorials during the afternoon: An Introduction to the Journey from Data to Evidence using OHDSI; Developing and Evaluating Your Extract, Transform, Load (ETL) Process to the OMOP Common Data Model; So, You Think You Want To Run an OHDSI Network Study?; and Using the OHDSI Standardized Vocabularies for Research. You can select your tutorials during the registration process.

Book Your Hotel Sleeping room OHDSI Symposium (hyatt.com)

Share in Collaboration for Tuesday, Oct. 22 by filling out this form

JOB OPENINGS

Job Openings

Daniel Prieto-Alhambra announced an opening for a Postdoctoral Researcher in Real World Evidence to join the Pharmaco- and Device epidemiology research group at the Botnar Research Centre, NDORMS, University of Oxford. This person will be leading or co-leading real world evidence studies, analysing real world health data mapped to the OMOP common data model and write study reports and scientific manuscripts. More details and an application link are available here; the application deadline is 12 pm on July 1, 2024.

Aki Nishimura announced that Johns Hopkins University is seeking postdoctoral fellows. The fellows would work on methodological research in pharmaco-epidemiology to address medication and device utilization, effectiveness, and safety relevant to health, lung, and blood diseases. More information and application details are available here.

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Please continue to collaborate in our MS Teams environment, check out the OHDSI website and forums , and follow us on all platforms, including Twitter and LinkedIn to get continued updates and information on everything happening in our community

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