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caTIES adoption update at UAMS

caTIES adoption update at UAMS. Umit Topaloglu, Ph.D. UTopaloglu@uams.edu. Agenda. caTIES Platform , Version, and Database Interface Engine component of caTIES are we using HL7 Pipeline. De-ID Pipeline. Tie Pipeline. Current usage. UAMS specimen search caTissue I2B2.

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caTIES adoption update at UAMS

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  1. caTIESadoption update at UAMS Umit Topaloglu, Ph.D. UTopaloglu@uams.edu

  2. Agenda • caTIES • Platform, Version, and Database • Interface Engine • component of caTIES are we using • HL7 Pipeline. • De-ID Pipeline. • Tie Pipeline. • Current usage. • UAMS specimen search • caTissue • I2B2

  3. UAMS’ Process Flow

  4. caTies instance at UAMS • caTIES Version • 3.71 (was 3.6) • Platform • Windows Server 2003. • Windows Services - Java Service Wrapper (JSW). • Database • MySQL (single server: public + private). • Interface Engines • Java Composite Application Platform Suite (JCAPS). • Mirth Connect.

  5. Components of caTIES • HL7 Pipeline • Picking up HL7 reports from a centralized report folder. • De-id Pipeline • Harvard Scrubber (HS) • De-identification with pattern matching (Customized Regex Rules). • Tie Pipeline • Concept coding the de-identified reports. • Pathology Reports, Radiology, Reports and Transcripts. • Index Pipeline • De-activated. • We are using our own GUI interface.

  6. flow

  7. Methodology • De-identification Processes: • Remove PHI known to be associated with patient based on the HL7 header. • E.g. Name, MRN, Accession #, etc. • Predictable PHI patterns removal using a series of regular expression clauses. • E.g. SSN=[^a-z^A-Z^0-9]+[0-9]{3}-[0-9]{2}-[0-9]{4} • Remove pathologist names that exists in the pathologist name list. HL7 Pipeline De-id Pipeline (Harvard Scrubber) Remove PHI based on HL7 header Remove PHI pattern Regular Expression List Remove Pathologists’ Name Pathologist Name List Tie Pipeline caTIES

  8. caTIES use • Specimen Search • We have easy to use specimen search for the tissues available at the UAMS Tissue Procurement • Results include reports processed by the caTIES • caTissue • We process surgical path reports and put into caTissue • I2B2 • We have mapped concept codes generated by the caTIES to the I2B2 which is our new direction for cohort discovery.

  9. Specimen Search

  10. Specimen Search- reports

  11. Specimen Search- tissue info

  12. Specimen Search-concept codes

  13. Specimen Search- deid report

  14. Specimen Search- tumor registry

  15. Use in caTissue

  16. I2B2 Integration • Since we have caTIES in place to process free text reports, we have mapped the concept code generated by caTIES to I2B2 using UMLS semantic mapper. • each concept accompanies a semantic type • the mapper performs a search based on the semantic type of a concept against the semantic network • A leaf node in the network, which matches the semantic type of the concept are located. • This path is called concept path

  17. I2B2 integration

  18. Publications related to caTIES • V. Yip, U. Topaloglu, Concept Integration from the caTIES to the i2b2 Using the UMLS Semantic Network, ACM IHI 2010 • Vincent Yip, Mete Mutlu; Umit Topaloglu, Sinan Kockara, "Concepts Discovery for Pathology Reports with an N-gram Based Model", 2010 AMIA Summit on Translational Bioinformatics. • Umit Topaloglu, Cheryl Lane, William R. Hogan, Jiang Bian, Vincent Yip, Thomas Kieber-Emmons, Laura F. Hutchins. A System for Indexing Clinical Documents for Clinical and Translational Research. caBIG Annual meeting 2010.

  19. Questions? Contact information: Umit Topaloglu Ph.D. utopaloglu@uams.edu 501- 686 - 7238 Thanks for listening

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