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Yosemite part-4 webinar-final

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In our series on The Yosemite Project, we explore RDF as a data standard for health data. In this presentation, we will discuss with Claude Nanjo, a Software Architect at Cognitive Medical Systems, ways to expose clinical knowledge as OWL and RDF resources on the Web in order to promote greater convergence in the representation of health knowledge in the longer term. We will also explore how one might rally and coordinate the community to seed the Web with a core set of high-value resources and technologies that could greatly enhance health interoperability.

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Yosemite part-4 webinar-final

  1. 1. Towards a Web of Clinical Knowledge Experience gained from DoDTAPS Research Project Claude Nanjo December 2014 SemanticWeb.com
  2. 2. Overview •The healthcare challenge •Exposing clinical knowledge on the Web as RDF •Transforming clinical content –An example from the DoDTAPS project •Getting closer to this vision
  3. 3. The Challenge The US Healthcare System is highly heterogeneous. How do we converge?
  4. 4. The Rapid Growth of Health Knowledge Information will need to be sharable and machine-processableif it is to scale
  5. 5. Exposed and Richly Linked Knowledge …
  6. 6. … That is computable, Reusable, and Actionable CaptureExposeTransformProcess & AnalyzeCHCS$ ICD9$to$SNOMED$ DX$transla4on$ NLP$parse$of$$ Med$SIG$into$ $discrete$data$ Name$parse$ into$discrete$data$ Address$parse$ into$discrete$data$ graph$ alignment$ Cluster$ Node$ Cluster$ Node$ Cluster$ Node$ Graph$ transform$&$ distribu4on$ Hadoop$ $ csv$ Clients$ ActImprove Outcomes
  7. 7. This Ecosystem Already Exists! Computing
  8. 8. EXPERIENCE GAINED FROM DODAND VA RESEARCH PROJECTS
  9. 9. Our Focus Today CaptureExposeTransformProcess & AnalyzeCHCS$ ICD9$to$SNOMED$ DX$transla4on$ NLP$parse$of$$ Med$SIG$into$ $discrete$data$ Name$parse$ into$discrete$data$ Address$parse$ into$discrete$data$ graph$ alignment$ Cluster$ Node$ Cluster$ Node$ Cluster$ Node$ Graph$ transform$&$ distribu4on$ Hadoop$ $ csv$ Clients$ ActImprove Outcomes
  10. 10. TAPS RDF Pipeline CHCS Model Transformation ICD9 to SNOMED DX translation NLP parse of Med SIG into discrete data Name parse into discrete data Address parse into discrete data graph alignment Cluster Node Cluster Node Cluster Node Graph Federation Graph transform & distribution Hadoop csv Clients Graph Clients
  11. 11. RDF Pipeline Definition For more information on the RDF Pipeline Framework, please visit: http://rdfpipeline.org/
  12. 12. Deterministic Model Transformation: CHCS Address to FHIR Address
  13. 13. Non-Deterministic Model Transformation: From CHCS SIG to FHIR
  14. 14. Leveraging SPARQL for Terminology Alignment
  15. 15. Deterministic, Declarative, Reusable Transformation
  16. 16. WHAT’S NEXT A multi-pronged approach
  17. 17. Capture Knowledge Declaratively CaptureExposeTransformProcess & AnalyzeCHCS$ ICD9$to$SNOMED$ DX$transla4on$ NLP$parse$of$$ Med$SIG$into$ $discrete$data$ Name$parse$ into$discrete$data$ Address$parse$ into$discrete$data$ graph$ alignment$ Cluster$ Node$ Cluster$ Node$ Cluster$ Node$ Graph$ transform$&$ distribu4on$ Hadoop$ $ csv$ Clients$ ActImprove Outcomes
  18. 18. Why we need standards to guide clinical capture •RDF makes the processing of clinical information staight-forward. –Lots of tooling –It is a known semantic model with a number of supported representations (RDF/XML, Turtle, …) •RDF cannot solve all problems –Transformations are expensive even with RDF –Hard to maintain –Transformations are lossyand not always deterministic •Need standards to converge on –Standards that allows convergence towards a common clinical baseline. –Great strides being made in the standards world –Customization and localization increase TCO
  19. 19. A few encouraging developments •The adoption of FHIR (Fast Healthcare Interoperability Resources) –an implementer-friendly resource-oriented, REST-based clinical resource framework –http://www.hl7.org/implement/standards/fhir/summary.html •The RDF Semantic Interoperability SWG at HL7 –Goal: To help expose HL7 standards using OWL/RDF –Discussion on an OWL ontology for FHIR and a FHIR RDF representation •Convergence of two existing communities –HL7 –W3C Semantic Web for Health Care and Life Sciences Group –http://wiki.hl7.org/index.php?title=RDF_for_Semantic_Interoperability
  20. 20. Expose Resources and Reusable Logic CaptureExposeTransformProcess & AnalyzeCHCS$ ICD9$to$SNOMED$ DX$transla4on$ NLP$parse$of$$ Med$SIG$into$ $discrete$data$ Name$parse$ into$discrete$data$ Address$parse$ into$discrete$data$ graph$ alignment$ Cluster$ Node$ Cluster$ Node$ Cluster$ Node$ Graph$ transform$&$ distribu4on$ Hadoop$ $ csv$ Clients$ ActImprove Outcomes
  21. 21. Encouraging developments •ONC’s Clinical Quality Framework Initiative –The harmonization of CDS and Clinical Quality models through FHIR –CDS ontologies? •CDS Collaborative –Collaboration between the University of Utah (OpenCDS) and Cognitive Medical Systems (Socratic Grid) –Declarative rules to be exposed on the Web –Enable access to clinical decision support services that leverage the web and RDF
  22. 22. Knowledge Discovery CaptureExposeTransformProcess & AnalyzeCHCS$ ICD9$to$SNOMED$ DX$transla4on$ NLP$parse$of$$ Med$SIG$into$ $discrete$data$ Name$parse$ into$discrete$data$ Address$parse$ into$discrete$data$ graph$ alignment$ Cluster$ Node$ Cluster$ Node$ Cluster$ Node$ Graph$ transform$&$ distribu4on$ Hadoop$ $ csv$ Clients$ ActImprove Outcomes
  23. 23. Other prototypes from the TAPS project •Record linkage through FHIR normalization using RDF –CHCS and VISTA •Patient Cohort Classification System •PTSD Capacity Planner
  24. 24. Provide Support At the Point of Care CaptureExposeTransformProcess & AnalyzeCHCS$ ICD9$to$SNOMED$ DX$transla4on$ NLP$parse$of$$ Med$SIG$into$ $discrete$data$ Name$parse$ into$discrete$data$ Address$parse$ into$discrete$data$ graph$ alignment$ Cluster$ Node$ Cluster$ Node$ Cluster$ Node$ Graph$ transform$&$ distribu4on$ Hadoop$ $ csv$ Clients$ ActImprove Outcomes
  25. 25. The Ask •Help us get there, get involved in an initiative •Engage the community •Contribute to Open Linked Knowledge

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