Healthcare data is often complex and is rarely standardised between different providers. The consequence is that data-driven activities seek to establish common data models and remove the variances found in the source data. Whilst this can make the research process simpler, it can make reproducibility harder, as to replicate the research would require everyone to convert the data in the same way with the same precision.
We will focus on one common data model, OMOP, that has been gaining significant traction. The first morning will be a refresher and an introduction to OMOP, so if you have not heard about it before, or need a bit of a renewal of understanding, join us in the morning session of day 1.
The rest of the event will focus on how teams currently covert their data to OMOP, throughout the event there will be insight and discussion on current best practice, innovative and cutting-edge solutions and how these are being brought together.
Who should attend:
- Anyone who has heard about OMOP and would like to know how to get datasets to be ready to be part of global partnerships
- Anyone who has developed a tool to help in the curation of data to OMOP
- Anyone who has an interest in data provenance processes
Outcomes:
Academic paper – all attendees will be attributed as co-authors.
Throughout the event, we will be posing questions for debate and deliberation to develop an academic position paper for publishing.
