CDISC Presentation


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hoot72 is now caregraf. This is the CDISC presentation with "caregraf" instead of "hoot72".

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  • There are green field demos already
  • vague generic “go for you” terms page on baltimore becomes linkable data about baltimore web didn’t make hyperlinks or protocols or page layout the power, the scale was link anywhere
  • Nodes and Literals ... Codes would break down Detailed discussion of semi-structured (not going to get into this aspect) Observable ( OBX|4|CE|30949-2^Vaccination adverse event outcome^LN|1|005^required hospitalization^NIP|) NIP= National Immunization Program within the Center for Disease Control
  • One standard code is 30949-2. For the astute: better if code became URI.
  • Beyond an isolated set of patients
  • From: HCLS == the w3c Health Care and Life Sciences Interest Group Patient Data is secure - “intranet” LINK OUT Typical Report: chase type (Ontology) in a world of (EMR) particulars. 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.
  • Middleware - format gets out of the way. IT gets out of the reformatting business.
  • Growing in number ... Billions of triples, ready to be leveraged, all these URIs. Gen purpose (demographics) and PubMed, Drug Bank, GeneID, Diseasome Arrows representing linking out to another conceptual scheme CDASH ODM (machine readable) CDISC SDTM and other terminology goes through an extensive process of definition, development, and review before it is declared ready for release. Terminology that has completed this process is tagged as "Production," and now includes some 50 SDTM codelists with about 2,200 terms covering demographics, interventions, findings, events, trial design, units, frequency, and ECG terminology. This terminology is maintained and distributed as part of NCI Thesaurus
  • CDC Example. We will have standard and local ontologies, standard and local queries there may be several different ways to express the same concept. Human users may be able to recognise that these are essentially the same, but the rules for doing so must be made explicit to be usable by computer. -- Why is Terminology hard?, Alan Rector
  • ME to learn of CDISC work. See how to leverage all the work. ... Here at the Drug Information Association (DIA), you can see a “live” implementation of the interoperability that is possible between Electronic Health Record (EHR) systems and Electronic Data Capture (EDC) systems used for clinical research, which leverages the Integrating the Healthcare Enterprise’s (IHE) Retrieve Form for Data Capture (RFD) integration profile along with CDISC’s ODM and CDASH standards Contrast to RDIF XFORMs.
  • Get Real The Integration Control Number (ICN) - ASTM e1714-95 standard for a universal health identifier. Like the efforts in the showcase to interop EMRs
  • MUMPS ( M assachusetts General Hospital U tility M ulti- P rogramming S ystem) EMR NOT LEFT OUT OF THE PICTURE, not just a “old” aside.
  • Very early on this.
  • The big picture ... Concept and Concrete, Users and Contributors in one web Trial Recruitment, Drug Safety, Outcomes research
  • More than the two ways here
  • CDISC Presentation

    1. 1. Care graf <ul><li>CDISC 2009 </li></ul> Health-Care, meet the Semantic Web
    2. 2. Care graf - .org <ul><li>“ Promotes the deployment of the Semantic Web in Health-Care” </li></ul><ul><li>Incubate ideas, openly </li></ul><ul><li>Not Green Field - “now focus” </li></ul>
    3. 3. : Just Another Format? <ul><li>Technology: Web Stack++ </li></ul><ul><ul><li>Reuse: HTTP, URIs </li></ul></ul><ul><ul><li>+ Form (RDF) Schema (OWL) Query (SPARQL) </li></ul></ul><ul><li>Link documents -> Link data </li></ul><ul><li>Same ol’ Power: Link ANYWHERE </li></ul><ul><ul><li>Begone CD-ROM: no islands </li></ul></ul><ul><ul><li>Incremental: new adds on, reuse, open </li></ul></ul>
    4. 4. A Linked Patient CodingSystem Code observation observationValue Doe personName familyName givenName middleName about Patient type Identifiers and Time not shown URI: LN 30949-2 CodingSystem Code 005 NIP John Fitzgerald
    5. 5. Now Just Ask ... <ul><li>All Patients with adverse outcome from vaccine ... </li></ul>SELECT DISTINCT ?givenName ?familyName WHERE { ?patient cg:personName [ cg:givenName ?givenName ; cg:familyName ?familyName ] . [ cg:about ?patient ; ?assert [ cg:nameOfCodingSystem &quot;LN&quot; ; cg:simpleIdentifier &quot;30949-2&quot; ] ] }
    6. 6. Move out and up <ul><li>Question: Patients taking “Weight Loss Drugs” </li></ul><ul><li>Patient Web: very particular </li></ul><ul><ul><li>Patient drugs as NDC codes: DESOXYN TABLETS (00074337701) ... </li></ul></ul><ul><li>Too big a gap? </li></ul>
    7. 7. Enter the Ontologies! Name NDC: 00074337701 Desoxyn 5MG Tablet Name SameAs Ingredient Medication SameAs RxNorm Stanford Drug Ontology Hoot72 Patient 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
    8. 8. The Ontologies? <ul><li>“ an implementable model of the entities that need to be understood in common in order for some group of software systems and their users to function and communicate at the level required for a set of tasks” -- Alan Rector </li></ul><ul><li>Concepts Related : hierarchies, equivalence ... </li></ul><ul><li>The “middleware” of the Semantic Web </li></ul><ul><li>Interoperability: concept not format focus </li></ul><ul><li>OWL (WOL) - Web Ontology Language </li></ul><ul><li>Growing every day: in Colleges, Corporations, ... </li></ul>
    9. 9. Ontologies are Standing by URIs for CDISC Terms?
    10. 10. Not just “Standards” CodingSystem Code Text Local Code LOINC Code SameAs <ul><li>Enable standard, off-the-shelf queries </li></ul><ul><li>Definition is incremental </li></ul>LN 13317-3 CodingSystem Code Local 182253 MRSA Culture
    11. 11. CDISC piles in? <ul><li>Roadmap: “The separation of content standards from the means of transporting that content” </li></ul><ul><li>Terms: to OWL and Endpoints </li></ul><ul><li>“ BRIDGing” in OWL </li></ul><ul><li>Trials as querable Graphs </li></ul>
    12. 12. But ... “Patient Gap” <ul><li>“Trapped”, “Silo’ed” </li></ul><ul><li>Ontologies Left Waiting </li></ul><ul><li>EMRs Hold Back </li></ul>
    13. 13. Reality: from Vets <ul><li>Concrete EMR - VistA </li></ul><ul><ul><li>VA: Largest U.S. Care Provider </li></ul></ul><ul><ul><li>128 VistAs, federated, 14+ Million in MPI - ICNs </li></ul></ul><ul><ul><li>Available under FOIA </li></ul></ul><ul><li>Not VistA Special: Applies to others </li></ul>
    14. 14. Every EMR, an EndPoint <ul><li>Put onto the Web ... </li></ul><ul><li>Lucky: MUMPS repositories </li></ul><ul><ul><li>Network-Format ala Semantic Web </li></ul></ul><ul><ul><li>VistA’s FileMan (no scale to test) </li></ul></ul><ul><li>Now to SPARQL ... </li></ul>
    15. 15. FMQL: SPARQL-like <ul><li>Specification in progress </li></ul><ul><li>Initial goal: limited Patient, meta data dumps </li></ul>SELECT ?name ?diagnosis ?age ?history FILE &quot;PATIENT&quot; WHERE {?r &quot;NAME&quot; ?name ; &quot;DIAGNOSIS&quot; ?d . ?d &quot;DIAGNOSIS&quot; ?diagnosis ; &quot;AGE AT ONSET&quot; ?age ; &quot;HISTORY&quot; ?history }
    16. 16. Many Users, Contributors One Semantic Web for Health-Care Linked Health Data Patient Doctor Manager Researcher Insurance Informatics
    17. 17. Summary <ul><li>Semantic Web growing in Health-Care </li></ul><ul><li>But a “Patient Gap” </li></ul><ul><ul><li>can be bridged NOW </li></ul></ul><ul><li>CDISC can drive it forward </li></ul><ul><li>More: </li></ul>