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Clarity Medication Mapping to NDF-RT

Clarity Medication Mapping to NDF-RT. Design and Current Status. Outline. Brief Tour of RxNorm Tables Used Design Current Status (Results) Next Steps Code Walkthrough Discussion. RxNorm Concept Names and Sources ( rxnconso ).

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Clarity Medication Mapping to NDF-RT

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  1. Clarity Medication Mapping to NDF-RT Design and Current Status

  2. Outline • Brief Tour of RxNorm Tables Used • Design • Current Status (Results) • Next Steps • Code Walkthrough • Discussion

  3. RxNorm Concept Names and Sources (rxnconso) http://www.nlm.nih.gov/research/umls/rxnorm/docs/2012/rxnorm_doco_full_2012-3.html (starting section 12.4) • “Primary” table – consists of all RxNorm Concepts • Example: A medication and synonyms - there may be several rows for a single concept. • Disulfiram (generic) and Antabuse (brand name) are both the same concept and have the same RxCUI. • RxCUI: Concept Unique Identifier (unique per concept, may be many rows with the same CUI) • RxAUI: Atom Unique Identifier (unique per entry in the table) • SCUI: Source-asserted Concept Identifier • The identifier as provided by the source (NDDF, NDFRT, RXNORM, etc.) • TTY: Term Type (preferred term, synonym, ingredient, etc.)

  4. RxNorm Tables: Others • Simple Concept and Atom Attributes (RXNSAT) • Example: Used to match NDC and find VA Class types • Related Concepts (RXNREL) • Example: Parent/Child relationships of VA classes, “ingredient_of”, etc. • Source Information (RXNSAB) • Source abbreviation/full name (NDFRT/National Drug File), version, etc. • Documentation for Abbreviated Values (RXNDOC) • Full name for abbreviations used in other tables

  5. RxNav: Relationshipshttp://rxnav.nlm.nih.gov

  6. VA Class Ontology http://bioportal.bioontology.org/ontologies/47101/?p=terms&conceptid=N0000029067

  7. Map Clarity Medications to RxCUI: GCN/NDC • Clarity Medication List • clarity.clarity_medication • GCN (Generic Code Sequence Number - First Databank Inc.) • clarity.rx_med_gcnseqno • rxnorm.rxnconso (code column when sab = NDDF, and tty != ‘IN’) • NDC (National Drug Code) • clarity.clarity_ndc_codes • rxnorm.rxnsat (atv column where atn = NDC)

  8. The Leftovers: Match with MedExNLPhttp://knowledgemap.mc.vanderbilt.edu/research/content/medex-tool-finding-medication-information • For the medications that don’t match using GCN/NDC, use MedEx (NLP) • map directly to RxCUI via the drug name in clarity • “NAME” (arbitrarily preferred) • “GENERIC_NAME” • Issues • Closed source (though, open source soon as per authors) • Windows Only right now (Linux binaries won’t run with our current configuration on our servers) • Not integrated into our ETL (“manual technical-debt”) • Linking results with input is problematic

  9. Map to Drug Form and VA Class • Map Medications to Semantic Clinical Drug and Form (SCDF) or Semantic Branded Drug and Form (SBDF) • Example Clarity Medication: “ANTABUSE 250 MG PO TAB” • Example SBDF: “Disulfiram Oral Tablet” • Map Medications to Veterans Administration class (VA Class) • Example: “[AD100] ALCOHOL DETERRENTS”

  10. Resulting I2B2 Hierarchy

  11. The Leftovers: No SCDF, SBDF, or VA Class! • Some medications didn’t map directly to SCDF, SBDF, or VA Class • Sometimes, it was because the drug mapped to an ingredient. • Example: “CEFAZOLIN INJ 1GM IVP” (medication id 210319, MedEx mapped to RxCui 2180 “CEFAZOLIN” an “ingredient”)

  12. The Leftovers: Map via “ingredient” relationships • Use “ingredient_of” and “constitutes” relationships • Use “isa” relationships to get SCDF/SBDF • Help! Results in 21.7 Million results from 20,354 Medications! • A huge number of components, packs, and associated SCDFs/SBDFs • Reduce this by mapping to the SCDF/SBDFs we already have mapped from direct links • Is there a better way?

  13. RxNav(Cefazolin)

  14. Putting Relationships Togetheri2b2 Ontology • Use prior mappings (Medications to SCDF/SBDF and Medications to VA Class) to then map the SCDF/SBDF to VA class. • Create table with parent/child relationships • Use these relationships to build i2b2 compatible ontology

  15. Resulting I2B2 Hierarchy

  16. Results Based on June 2012 data (Cimarron) • “Round 1”: • GCN + NDC Mapping • 89.4% of medication observations covered (100,395,527 total facts, 10,636,780 missing facts) • “Round 2”: • Added MedEx NLP • linking missing medications to SCDF/SBDF via "ingredient_of" relationship. • 94.39% of medication observations (100,395,527 total facts, 5,630,904 missing facts)

  17. Next Steps • Peer review of the code! • Manual mapping of some top concepts • Problem children thus far: http://informatics.kumc.edu/work/attachment/ticket/1246/unmapped_meds_20120823.csv • Review in more detail code from Dustin Key from Group Health (ghc.org) • Basic approach is the same as per overview • How to test/validate?

  18. References RxNormdocumentation http://www.nlm.nih.gov/research/umls/rxnorm/docs/2012/rxnorm_doco_full_2012-3.html KUMC Work Ticket http://informatics.kumc.edu/work/ticket/1246 UMLS Reference Manual http://www.ncbi.nlm.nih.gov/books/NBK9676/ RxNav http://rxnav.nlm.nih.gov/ BioOntology.org http://bioportal.bioontology.org Paper: “Enabling Hierarchical View of RxNorm with NDF-RT Drug Classes” http://www.ncbi.nlm.nih.gov/pubmed/21347044 MedEx http://knowledgemap.mc.vanderbilt.edu/research/content/medex-tool-finding-medication-information

  19. Code Walkthrough! epic_med_mapping.sql

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