Re: Using RDF, Datalog, OWL-RL and a "RIM lite ERPA Ontology" to calculate HEDIS Quality measures

Even better.  I can just present it to you on a webex or another kind of 
call.






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From:   David Booth <david@dbooth.org>
To:     Peter Hendler/CA/KAIPERM@KAIPERM
Cc:     its@lists.HL7.org, public-semweb-lifesci@w3.org
Date:   09/29/2015 03:15 PM
Subject:        Re: Using RDF, Datalog, OWL-RL and a "RIM lite ERPA 
Ontology" to  calculate HEDIS Quality measures



Excellent!   Unfortunately I will miss your presentation.  Can we get 
your slides?  Even better, if your presentation is recorded that would 
be awesome.

Thanks,
David Booth

On 09/29/2015 05:38 PM, Peter.Hendler@kp.org wrote:
> At KP, and working with Ian Horrock's group at Oxford, we have been
> experimenting with their new RDF, Datalog, OWL-RL triple store called
> "RDFox".
>
> We have calculated the HEDIS Diabetes quality measure on a population of
> over 400,000 patients real data.
>
> We still have to compare our numerators and denominators to results
> calculated with SQL and traditional DB tables.
>
> I will be presenting a very simple version of this at HL7 at the AID
> work group in Atlanta on Monday Q3.
>
> I believe this is the first time a complex HEDIS quality measure has
> been calculated with RDF, OWL and Datalog and SPARQL on a large
> population of real patients.
>
> I will not be presenting the complete complex HEDIS measure (which would
> take days), but a smaller example to explain how it all works.
>
> We used SNOMED subsumption to generate a small value set of SNOMED codes
> that are "kinds of Diabetes".  Using that SNOMED VS, we found all the
> patients who had a visit coded for Diabetes.  Then we searched all of
> their HgBA1C values and then found the "last value".  We could then look
> at the numerical results of the HgBA1C and find how many of them were
> below 7% (good control).
>
> In order to do this we had previously created an OWL ontology based on
> Entities in Roles that Participate in Acts.  It is not the full HL7 V3
> RIM, but only what was needed for this exercise.
> This "KCOM" model is what we presented before at HL7 AID meetings.
> This entire project would not have been possible to do without first
> mapping the raw clinical data to this ERPA OWL backbone ontology.  All
> of our queries were based on this ERPA (Entities in Roles Participating
> in Acts).
>
> RDFox is multi threaded and we were able to run the data materialization
> on 8 threads on an 8 core machine with 64 Gig RAM.  It ran in only a few
> hours and we have already found ways to speed it up further.
>
> Hope to see you at HL7 Atlanta.
>
>
>
>
>
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