2019/10/17 - "Evidence generation for HTA: what role for the OMOP Common Data Model and EHDEN?"

Most countries in Europe have formal health technology assessment processes to inform clinical practice and/or the coverage and reimbursement of new medical technologies. Some bodies focus on the relative effectiveness of technologies, while others additionally assess cost-effectiveness, i.e. are any additional costs justified by the additional benefits? Because HTA bodies are typically interested in the long-term (usually lifetime) impact of technologies in clinical practice, clinical trials alone are not sufficient to inform decisions, and modelling is often required.

Models are data hungry, usually requiring data on disease prevalence, natural disease history, treatment utilisation, long-term effectiveness and safety, health-related quality of life, and healthcare utilisation. It can be challenging to find and access datasets containing all appropriate data and using multiple datasets requires analysts to be familiar with the structure and coding of each, and to develop separate analysis scripts. As such, the federated data network which EHDEN aims to develop and the OMOP common data model (OMOP-CDM) and associated tools (through the OHDSI network) have the potential to alleviate some of these challenges. In this webinar, we discuss the uses of HTA, the challenges of evidence generation for HTA, and think about how the OMOP-CDM, OHDSI tools, and the EHDEN network can support such evidence generation, how these tools and networks could be further developed to better support HTA, and where challenges are likely to remain in the future.

2019/09/04 - "Reducing cancer deaths and complications by leveraging OMOP and OHDSI."

Surgery is the major treatment option for colorectal cancer, which today is the third most common form of cancer worldwide. However, understanding when and how to apply surgery, in combination with drugs, radiotherapy and other medical treatment options, is an ongoing field of research.

In this webinar, Ismail Gögenur, director of the Center for Surgical Science at Zealand University Hospital in Denmark, will explain how his team is utilising the OMOP Common Data Model and the OHDSI tools to achieve a holistic view on the risk profile and treatment options for colorectal cancer patients. While earlier webinars focused on the EHDEN project, the OMOP CDM itself and ways to generate medical evidence, this one will focus on arguably the most impactful aspect: using OMOP, OHDSI and EHDEN to make better decisions in clinical practice, reducing mortality and complications by the smart use of medical data at scale.


2019/06/18 - "The future of primary care research in Catalonia - SIDIAP’s journey of adopting the OMOP common data model."

In this 3rd installment of the EHDEN webinar series, Kees van Bochove (www.thehyve.nl) invited Talita Duarte Salles and Leonardo Mendez Boo from SIDIAP (www.sidiap.org) to discuss their journey of adopting the OMOP CDM. Listen to the recording to learn more about SIDIAP, their journey and how they benefited from adopting OMOP.

2019/05/22 - "EHDEN Webinar - 21st Century Real World Open Science"

In this webinar of the EHDEN webinar series, Peter Rijnbeek (Erasmus Medical Center) and Nigel Hughes (Janssen Pharmaceutica) discuss the European Health Data & Evidence Network. They explain the scope and objectives of EHDEN and how they believe EHDEN will transform the way real-world evidence is being generated. Additionally, the open call processes is explained and in particular, how SMEs and data sources can both contribute and benefit from EHDEN.

2019/03/28 - "From question to publication in 5 days - How EHDEN and OHDSI change medical evidence generation through open science."

In this 1st webinar of the EHDEN webinar series, Kees van Bochove (The Hyve) and Daniel-Prieto Alhambra (University of Oxford) discussed the EHDEN and OHDSI Study-a-thon which was organized at the University of Oxford in December 2018. They explained the concept of this 5-day meeting and how they were able to go from question, to cohort characterization, to data analysis and ultimately to evidence generation in only 5 days.