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Semelhante a Throw the Semantic Web at Today's Health-care
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Throw the Semantic Web at Today's Health-care
- 3. Possible? A View for Everyone Linked Health Data Patient Doctor Manager Researcher Insurance IT
- 4. One Enabler: Silo’s chat Source: Neotool, V3 vs V2 “ HL7 version 2 is a major breakthrough and market success. More than 93% hospitals in US are using this standard” - Health Level Horizon (HLH) Project
- 7. What if? From obscure Soup to query-ready Graph OR|20010331605||ORU^R01|20010422GA03|T|2.3.1|||AL|725^^^^MR||Doe^John^Fitzgerald^JR^^^L||20001007|M||2106-3^White^HL70005|123 Peachtree St^APT 3B^Atlanta^GA^30210^^M^^GA067||(678) 555-1212^^PRN||||||||||Peachtree Clinic|101 Main Street^^Atlanta^GA^38765^^O^^GA121|(404) 554-9097^^WPN|101 Main Street^^Atlanta^GA^38765^^O^^GA121|
- 10. Two plus Two Hoot72 Mapper HL7 Messages HL7 Message Definitions Hoot72 Ontology Clinical Data Graph
- 11. Observation (OBX) PID||| 1234^^^^SR~1234-12^^^^LR~00725^^^^MR || Doe^John^Fitzgerald^JR^^^L | ... OBX|4|CE| 30949-2 ^Vaccination adverse event outcome^ LN |1| H ^required hospitalization^ NIP005 | LN 30949-2 CodingSystem Code H NIP005 CodingSystem Code observation observationValue Doe John Fitzgerald personName familyName givenName middleName context Patient type Identifiers and Time not shown
- 18. RxNorm picks Joe Name NDC: 00074337701 Desoxyn 5MG Tablet Name SameAs Ingredient Medication SameAs RxNorm Stanford Drug Ontology Hoot72 Graph * Dotted: composite of links to save space ** w3c HCLS Example RxNorm:6816 Methamphetamine Methamphetamine StanDrug: C0025611 Name Obese May Treat Patient Joe NDC: 00074337701
- 19. Ontologies are Standing by
Notas do Editor
- Beyond the paper piles, our health data is in data silo’s
- Many practitioners - more perfect union Not covering Security or Ownership (both contentious and often take over) Primary and Secondary uses Patient-accessible, Doctor-complete Trial Recruitment, Drug Safety, Outcomes research ... right now, more Iraq, than US
- HL7 carries much of our health data HL7 everywhere means v2. Don’t Blink or you’ll miss V3. Another story ... Only one enabler. Going to ignore the filing cabinets for now
- Of course, more structured than your average tweet Pick out message type, patient name, contact relationship, body weight observation
- Step back and inside the soup again and ... Most of all you see codes! Messages are just the trucks. “What do you drive?” fixation. LN=LOINC for labs, CVX == , HL7’s 162 table says?, MVX [???]
- Back in the real world Work in progress with codes. Restructuring. Mapping. Entering the Semantic Web. Patient data still off in bunkers
- Ala web of documents, all documents get a URI. Everything gets a URI. Payoff soon.
- Automatic
- Links are labeled Nodes and Literals
- One standard code is 30949-2.
- - Some warehouse now - even their HL7. Modeled their own way. - People are sick of moving to “the next best” format, this year’s “solution to every problem” - but not just another reformat/syntax work: yes semi-structured data in graphs but real payoff is linkage
- URI == open address
- CDC Example. Query only standard if
- Middleware or Active Data.
- Linked Data! From: HCLS == the w3c Health Care and Life Sciences Interest Group A same-as into RxNorm and the greater ontologies can be leveraged Stanford Drug Ontology gives compounds that treat conditions. RxNorm relates compounds to branded drugs. Hoot72 Clinical Data has branded drugs. RxNorm not yet an ontology but has web api so can represent it as a SPARQL end point Simplied to fit. Ingredient = consists of to ingredient to brand name etc.
- Growing in number ... Billions of triples, ready to be leveraged Obvious PubMed, Drug Bank, GeneID But also take demographics - geo names, census data
- Graph enhancers ... in context. Skill levels. They will vary, depending on the extent of modeling done. And so will the quality of your Clinical Care data. Better links. Yields more.
- Dangerous part. The bit people are concerned about. Real “meaningful use”?