<scribe> scribe: ericP
<mscottm2> Background: Msgs came in through msg queueing system, HL7 2.X msg was parsed, distilled into components necessary for analysis and RDF created
<mscottm2> Eric: <checking> validating reports real-time?
<mscottm2> who is talking?
<mscottm2> tx
<mscottm2> eschrip: coded representation for topic, such as particular antibiotic for TB and another - whether there was a response.
<mscottm2> ericp: how were they tied together?
<mscottm2> eschrip: each reporting body (State?) created its own software
JoshMandel: did all the states have a common hl7 guideline?
<mscottm2> JoshMandel (?): When does validation happen, before or after RDF?
<mscottm2> eschrip: we apply some OWL reasoning and also use Jess to the msg
cecyl: initial submission is paper-based
... first electronic view is when the state gets a copy of all the paper forms
<mscottm2> ericp: trying to ascertain if the assertion of efficacy is tied to the event (msg).
eschrip: [biosynth demo]
... working from collection of different kinds of messages, those that appear in a given clinic or lab
... system sends them all to a processing point
... processing does:
... .. categorize events for reported disease, e.g. upper-respiratory issues
... .. identify syndromes, trends, etc.
... reported e.g. when a doctor did a test for anthrax, regardless of disposition
... parsing clinical data, different 'cause e.g. TB forms are would be normalized
... called for a rete engine
... unified patients based on hospital IDs, no inter-clinic links
... we were able to establish liklyhoods of different diseases
... rete used to asses symptoms, followup tests, etc.
... we classified into Cecil's disease ontology
ericP: if you were able to push the processing down, is there value to reporting in RDF?
<eschrip> That was Craig
<eschrip> (Craig dialed in from Salt Lake City)
cecil: drawing from e.g. prescriptions, facebook, etc. folks were able to beat CDC's influenza predictions by two days
<mscottm2> Google predicted an outbreak in influenza 2 days earlier than CDC could do it by looking at search patterns
eschrip: using RDF for messaging isn't as interesting as RDF for querying
... biosynth data lifetime is very short
... for TB, we keep it around longer to eliminate duplicates
... for a Quality of Care project, we kept data for the stay of a patient
... need validation
ericP: what if we used SPARQL for validation?
eschrip: we used OWL, and SPIN a little
... we used lots of SPARQL to examine the data, even in OWL format
... yes, a story should be told that novel JSON is the same as novel RDF for self-discovery requirements
JoshMandel: there are a couple JSON schema language, and i expect validators
... in RDF/SPARQL land, you'd have a zillion little validating queries?
ericP: maybe monolithic
cecil: how do a write a standard query for population health when there's not single query point
... GELLO provides a canonical model to which you'd map via d2r, etc.
... talking to chris chute, stan huff, ken madel, the SHARP grants are trying to create standard APIs
JoshMandel: at Harvard, we're creating canonical models
... has the same flavor of pushing the mapping back to the source system
ericP: when you have combinations of models, can one message meet multiple models?
JoshMandel: yes
... we have a payload validator which:
... .. is there a code?
... .. is it RxNorm?
... .. is there a dose?
cecil: i'm leading the clinical model CIMI task force
... FHIR use cases are similar to the narrow use cases
... you don't need the monolithic model when you know your target
... HL7 has Common Message Element Types for e.g. the lab domain
... aggregates e.g. SMART models
<scribe> scribenick: ericP
Craig: we have an org which is trying to move into a managed care model
... (instead of payment for test types, etc.)
... we're building towards being able to do decision support and risk analysis
mscottm2: when you've got finer granularity than state-level, you can do interesting mashups of, say, epidemic data
... is your data public? can we watch a virus traverse the states?
eschrip: the format depends on the organization
... infectious disease may be different from ...
Craig: they want to control and vet the data before publication, way into the episode of an outbreak
... there are many bits and pieces of information which preceed a diagnosed case
<Bosse> I need o leave, thanks for an interesting discussion. /Bosse
cecil: EpiInfo, if you can demonstrate a need to know of edidemiology info
... most states have a weekly fact sheet of what's happening, what needs attention
... even though i get that data, i can't really use it beyond figuring out how to use it late