1. Data Normalization Milestones

2. Data Normalization  Goals –To conduct the science for realizing semantic interoperability and integration of diverse data sources –To develop tools and resources enabling the generation of normalized EMR data for secondary uses

3. Data Normalization  Information Models Target Value Sets Raw EMR Data Tooling Normalized EMR Data Normalization Targets Normalization Process

4. SHARPn Data Normalization Team  PIs: Dr. Chris Chute; Dr Stan Huff  Program Management Team –Manager: Lacey Hart; Assistant: Erin Martin  Members Hongfang Liu (Lead) Calvin Beebe (co-Lead) Tom Oniki (co-Lead; Modeling Lead) Harold Solbrig (CTS2 Lead) Vinod Kaggal (Implementation Lead) Kyle Marchant (CEM DB Lead ) Joey Coyle (Modeling) Teresa Conway (Modeling) Nathan David (Modeling) Edinardo Potich (Modeling) Cyndalynn Tilley (Modeling) Les Westberg (CEM DB) Kevin Peterson (CTS2) Siddhartha Jonnalagadda (Pipeline) Dingcheng Li (Pipeline)

5. Modeling -Accomplishments  CORE and Secondary Use Models/terminology patient, meds, labs, administrative dx and procedure, disease/disorder  Definition of value sets in terms of standards where possible

6. Modeling - Accomplishments  Request site (in pilot)  CEM Browser

7. Modeling - Future work  Request site full launch  Browser launch  Browser enhancements (terminology integration, knowledge repository integration)  Better documentation  Model enhancements  Tooling – explore collaborations

8. Value Sets- Accomplishments  SHARP Value Sets published as CTS2 Resolved Value Sets –ICD-9 –RxNorm –LOINC –ECIS –SNOMED-CT

9. Value Sets- Accomplishments  CTS2 Services Created For –SNOMED-CT Simple Refsets and Dynamic Value Set Definition –ECIS Value Sets and Maps  CTS2 Participation in CIMI effort

10. Value Sets - Future work  CTS2 Service for RxNorm and UMLS access –Allow creation of new value sets –Links to concept descriptions and relationships  Integrate BioPortal Value Set Services –Bridge Bioinformatics Ontology / Clinical Terminology

11. Value Sets – Future Work  Complete ECIS Server –Will aid in CEM to ADL migration  CTS2 Services available to CIMI project  Integration –Create Pipeline specific services coupled directly to CTS2 –Tighter coupling of Concept Domains and Value Sets –Ajax Widgets for viewing, integrating and Authoring

12. Pipeline - Accomplishments  Architecture revision to make pipeline highly configurable –Enable seamlessly pipeline integration of components from different data sources (e.g., NLP)  Generic pipeline components –XML Initializer

13. Pipeline - Accomplishments  Highly configurable syntactic and semantic mappings –Allow four kinds of syntactic mapping – constant, 1:1, 1:n, and inference  Two options to process data –XML tree-based (achieve semantic mapping through UIMA annotations) –Template based (achieve translation directly in CEM annotations)

14. Pipeline – Future work  Integrate NLP normalization pipeline into data normalization  GUIs to simplify the configurations of the pipeline –syntactic mapping –Semantic mapping  Integrate the two options provided to process data into a single project

15. CEM to DB - Accomplishments Completed the following CEM to DB Mirth Channel Development –Patient CEM Channel (Add and Update) –NotedDrug CEM Channel (Add) –AdministrativeDiagnosis CEM Channel (Add) –Lab (Quantitative, Narrative, Ordinal, and Titer) CEM Channel (Add)

16. CEM DB - Accomplishments Completed CEM DB Design and Development –Patient CEM Tables  Demographics including Names, Addresses, Telecom, and Language  Patient Cross Reference and External IDs –Clinical CEM Tables  Index Data  Source Data  Patient Data

17. HL7 to XDR Channel - Accomplishments Completed the following HL7 to XDR channels for data exchange –HL7 AdminDX to XDR Channel (Sender) –HL7 Lab to XDR Channel (Sender) –HL7 Noted Drug to XDR Channel (Sender) –HL7 Message Separator (Sender) –HL7 Receive Message Separator (Receiver) –ReceiveXDR and Extract HL7 (Receiver)

18. Next Steps for Channels and CEM DB  Next Steps –Complete the Update feature for Clinical CEM Channels –Enhance the Error Handling and resending of error Message for channels –Additional Relational field data storage for Clinical CEM Messages –Support CEM changes and new data types

19. In summary  Continue effort in tooling for –Modeling (through CEMBrowser and Request Site) –Value sets (through CTS2) –Pipeline set up (GUIs for configuration and tools for generating semantics mapping) –CEM XML -> CEM DB, CEM RDF, etc