We are hoping to develop a controlled vocabulary for Social Determinants of Health (SDoH). Before we create our own vocabulary, we would very much appreciate knowing if others are working on (or have completed) standard vocabularies for national SDoH screening Instruments - especially PRAPARE, AHC, and/or We Care. Thanks!
SNOMED is getting better under their social_context root.
I attended an AMIA symposium presentation a couple of years ago when they did a big survey of tools and vocabularies out there for SDOH. And I found the link on PubMed is below
Are you watching the N3C SDoH demo right now? You should join that group. It’s good.
Thanks very much for this link. BTW.
May I ask did you go forward with developing a controlled vocabulary for Social Determinants of Health?
(came across your question, because we would also very much need such a vocabulary)
Would love to collaborate on this!
This is something the community should do, i.e. you. There is a clear demand for something like that, but it needs some amount of consolidation across different use cases, groups and countries. When you are ready you can simply submit through the community contribution, and we can bring it in.
Before starting a whole new project, I suggest looking at the work the Gravity project is doing w/HL7. Their standards are apparently already part of USCDI.
Michael, there was an effort a couple of years ago in the HealthEquity group led by Jake to cover the various efforts to develop SDoH ontologies and promote consensus about them and their use in EHRs. That include the Gravity work as well as others. The SDoHO a good recent effort by a combination of OHDSI investigators who NLP thought leaders. It is reported on in this paper: Systematic design and data-driven evaluation of social determinants of health ontology (SDoHO) - PubMed (nih.gov). At the upcoming OHIDS Symposium Polina will present the great work she’s done on developing a vocabulary that can be added to the OMOP Vocab that based in part on the SDoHO. We are starting to work with that in an NLP study focused on demonstrating the value of NLP for acquiring and representing SDoH data.