I am working on a data quality assessment project where we are taking open-access research datasets and evaluating their data quality against a re-operationalized existing framework. To do this more effectively, my colleagues and I felt we should map these open-access datasets to a common model, such as OMOP CDM. I’m wondering if anyone has had experience doing this with non-EHR data (e.g. clinical research datasets). Similarly, any resources or feedback you might have about how best to proceed with this task (especially if there is a better data model for my projects’ needs) are greatly appreciated. Please let me know if I can clarify/answer any questions.
Yes, OMOP CDM has been used for many different datasets beyond just EHR.
That includes national wellness surveys, like NHANES, clinical registries,
like SEER, and administrative claims. @clairblacketer had a nice poster
two years ago at the OHDSI Symposium about using CDM for registries in
particular:
Hi Patrick! Thanks for your response, a colleague of mine had sent over the same poster! I’ve tried using Usagi before and found it fairly difficult to navigate. Would you mind sharing resources on how you were able to properly load the NHANES survey dataset into Usagi? I’m interested to see if I can replicate it with a table from a BioLINCC dataset. Thanks so much!