Hi Chuck, Happy Thanksgiving!
>From my experience here and looking at most i2b2 installs on babel (though I >defer to Jim Campbell): 1. Practically we’re largely ICD9 centric for diagnoses (and park IMO terms below the ICD9 folders for) because that’s how most of the data was recorded. I think once you’ve got basic concept terms like DX-ID in Epic that roll up using IMO to either SNOMED or ICD, you can build folders to hold them. I see actually more SNOMED used within Epic “smart data elements” that could be contained in notes (but are difficult to extract from Clarity; we want to tackle that once we get Chronicles access sorted out). My sense is most clinicians/researcher are familiar with ICD9 like folders so informatics teams have built from the UMLS or pulled from Harvard’s starter i2b2 demo data ontologies. “Most” people clinically don’t think in terms of SNOMED as an interface terminology which is probably why you don’t see it as much and until lots of raw data is coded in SNOMED it may not have as much visibility. Now Jim Campbell is the SNOMED/LOINC leader for us and I think we’ve got pathways for how we manage these conceptual linkages but practically much on purely diagnoses sits in ICD9 like flavors. Trent at Vandy might also comment. I think as we work past phase 1 and get the fundamental observations interoperable, people can prototype different i2b2 folders that use different interface “folders”/terminologies for researchers. But, for now, ICD9 like folders will cover the immediate needs we will see. I think because i2b2 allows you to search by text, browser folders and see counts, it helps the end user compensate for precise mapping deficiencies to some degree. 2. Now for cancer registries, ICDO-2/3 is used and Dan built a reasonable ontology for NAACCR files. 3. For microbiology results, Cerner nicely maps organisms to SNOMED which we’d like to replicate as well for our Epic data. That’s one place I’ve seen SNOMED used in an i2b2 install. See under CMH Microbiology. 4. For meds, it’s RXnorm. Depending on your EMR, you can either crosswalk off the vendor product (FDB/Multim) based on something like a gcnseq_no, off a representative NDC for the formulary file, or do NLP with something like MedEX. Not sure SNOMED would ever play a role there. 5. Labs are LOINC. 6. For clinical observables, look at some of the GPC clinical measurements folder on babel. Jim and the Nebraska team have mapped those to LOINC. Lots of other great things like cardiovascular results that will be great to see us map to LOINC as well for interoperability. Lori Phillips is probably best equipped to comment on i2b2 philosophy and Jeff Klann on where SCILHS is headed. Russ On Nov 26, 2014, at 2:01 PM, Borromeo, Charles <ch...@pitt.edu<mailto:ch...@pitt.edu>> wrote: Hi Russ, We are trying to extend our i2b2 ontology to cover more of the medications and diagnoses (our initial ontology only covered the elements required by our rare disease). I have not seen any evidence of the GPC or the Harvard CDRN importing the SNOMED ontology into i2b2. Is there a technical reason for this? I have not tried importing SNOMED yet and I was curious if there were some issues I needed to understand. Thanks, Chuck Borromeo PaTH Network Russ Waitman, PhD Director of Medical Informatics Assistant Vice Chancellor for Enterprise Analytics Associate Professor, Department of Internal Medicine University of Kansas Medical Center, Kansas City, Kansas 913-945-7087 (office) rwait...@kumc.edu<mailto:rwait...@kumc.edu> http://www.kumc.edu/ea-mi/ http://informatics.kumc.edu<http://informatics.kumc.edu/> http://informatics.gpcnetwork.org – a PCORNet collaborative
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