A few items to consider in advance include: We would advise that you start this process early on in your implementation. One of the biggest efforts when implementing OMOP comes from the mapping of Epic terminology to the OMOP standards. This means that data transformation will be less of a lift for your data engineering team. The Caboodle and OMOP data models are similar and based on a dimension-fact star schema model.Organizations commonly add external claims data to their Caboodle database. Your OMOP requirements may include data not natively in your Caboodle database, but you can easily add that data for your OMOP implementation, which will also help to expand your Enterprise reporting capabilities. Caboodle was designed to be extensible.This is in part because Epic designed the database around usability. For healthcare organizations that use Epic as their EHR, the use of Epic’s Caboodle database as the source for OMOP data has been the best option from what we have seen thus far. You should also think about the effort that will need to be spent modeling out the data to conform to OMOP standards. It is important to consider the source of where your EHR data will be coming from and to use a source that allows for extensibility. If you’re considering utilizing this resource for future or current research collaboration, this post will highlight considerations for the build and deployment of the OMOP common data model and potential limitations you may encounter as well as some limitations we have encountered. This allows users to generate research datasets utilizing a wide variety of data sources. In addition to EHR data, the OMOP model can support administrative claims data. This is accomplished through the use of standardization in medical terminologies based on a set of concepts and vocabularies that OHDSI maintains. The Observational Medical Outcomes Partnership (OMOP), from Observational Health Data Sciences and Informatics (OHDSI), is a common data model enabling healthcare organizations to participate in multi-site and even worldwide research studies with other organizations. Written by Matthew Kesler and Steven LaRue Introduction
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