Integrating SNOMED CT with other Meaningful Use vocabulary standards (LOINC, RxNorm, HCPCS, CPT-4) and billing terminologies (NDC, ICD-9, ICD-10) using the UMLS
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This document discusses integrating SNOMED CT and other clinical terminology standards like LOINC, RxNorm, HCPCS, and CPT-4 with billing codes like ICD-9, ICD-10, and NDC using the Unified Medical Language System (UMLS). It describes challenges with mapping terms between different clinical terminologies and standards, and demonstrates a UMLS-based terminology server that can reconcile medications using RxNorm and NDC codes. The server allows integrated querying of real EHR data from Froedtert hospital through Epic Clarity reports.
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Integrating SNOMED CT with other Meaningful Use vocabulary standards (LOINC, RxNorm, HCPCS, CPT-4) and billing terminologies (NDC, ICD-9, ICD-10) using the UMLS
- 1. Integrating SNOMED CT with other Meaningful Use vocabulary standards (LOINC, RxNorm, HCPCS, CPT-4) and billing terminologies (NDC, ICD-9, ICD-10) using the UMLS Tomasz Adamusiak MD PhD @7omasz 1
- 2. Landscape of many standards 2
- 3. HIMSS14, February 26, Orlando, FL ROUNDTABLE ON SEMANTIC INTEROPERABILITY 3
- 4. UMLS Eruption SCT:1806006 rash NOS ICD-10:R21 Cutaneous eruption SCT:112625008 Exanthema C0015230 4
- 5. UMLS Eruption Cutaneous NOS rash eruption SCT:1806006 SCT:112625008 ICD-10:R21 Exanthema C0015230 5
- 6. Dealing with heterogeneous sources UMLS MU-oriented 6
- 7. Login: showcasedemo Pass: showcasedemo Use the link or google clinminer Click on demo 7
- 8. Demo and evaluation: 100 000 clinical avatars x 90 days x genotypeguided warfarin dosing 8
- 9. Clinical Avatars 11 MILLION OBSERVATIONS (20 TERMS)
- 10. Custom UMLS-based terminology server
- 11. RxNorm UMLS
- 12. SNOMED CT UMLS
- 13. Medication reconciliation via National Drug Code (NDC) and RxNorm https://clinminer.hmgc.mcw.edu/clinminer#ontology/search/31722-331-01 31722-331-01 100 tablets of Warfarin Sodium 4 MG Camber Pharmaceuticals 13
- 14. Integrated querying and reporting 14
- 15. How does it work with real EHR data? 15
- 16. Pilot cohort Transformed via UMLS Froedtert Epic Clarity reports ClinMiner LDS 2/16 16
- 17. 1.5 million observations (7000 terms) 17
- 18. Limitations? WE NEED BETTER LOINC – SNOMED CT MAPPINGS 18
- 19. LOINC is more granular 19
- 20. CPT maps to SNOMED CT and MedDRA 20
- 21. But not to LOINC 21
- 22. Some tests map on LOINC part level 22
- 23. Endgame in semantic integration 23
- 24. Thank you Mary Shimoyama PhD Stacy Zacher Glenn Bushee Bradley Taylor Clinical Avatars Vincent A. Fusaro PhD Peter J. Tonellato PhD This project was funded in part by the Advancing a Healthier Wisconsin endowment at the Medical College of Wisconsin and the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through grant UL1 RR031973. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Laboratory for Personalized Medicine Harvard Medical School 24