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Semantic Mapping and HL7

This document discusses the critical need for semantic mapping within the healthcare domain, specifically relating to HL7 standards such as RIM and RMIMs. It outlines how most current mapping tools fail to adequately address structural clashes in complex messaging systems, leading to inaccuracies. By developing shareable mappings and focusing on semantic interoperability, we can facilitate accurate translations between existing models and enhance data integrity across healthcare systems. The paper also highlights ongoing progress with various mapping projects, emphasizing the benefits and scalability of these mappings.

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Semantic Mapping and HL7

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  1. Semantic Mapping and HL7 robert.worden@charteris.com

  2. Why Mapping? • HL7 have built UML semantic models of healthcare (RIM, RMIMs, CDA…) • If everybody migrated to these models, many interoperability problems would be solved • Suppliers cannot do this; they have big commitments to other models and structures • They could map to the HL7 models; mapping is much easier than migrating • So HL7 needs to publish shareable mappings to existing standards and data structures

  3. Why Semantic Mapping? To Handle Structure Clashes • Most mapping tools only map data values • These are the leaves of message trees • Structure clashes (e.g. multiplicity) arise on non-leaf nodes, deep in the trees • Most mapping tools don’t address them • Therefore the translations don’t work • So people drop the tools and hand-code Message B Message A mappings

  4. Structure Clashes Arise from Associations • ‘Deep’ message A represents the association X=>Y by nesting of elements • ‘Shallow’ message B represents the same association by shared key values • This causes a structure clash • You cannot translate from A to B without knowing how they each represent the same association • Therefore semantic mapping is needed, to drive accurate translations object Class X association association property Class Y Message A Message B UML Class Model

  5. Mappings in Progress • Pharmacy V2-V3 (Pharmacy TC) • Various V2-V3 (ItalTBS) • HIPAA X12 to V3 (FM TC) • CCR – CCD (various vendors) • Relational database – V3 (basic demonstrator)

  6. Example: CCR and CCD • CCD and CCR are complex structures (typical nesting depth: 6 – 12) • They have many structure clashes (CCR uses shared keys) • They have both been mapped to a CCD semantic model (a few days’ work for CCR) • The mappings give accurate translations and round trips – translating thousands of data items • Mapping exposes the problems in CCR

  7. Mappings for ARRA/HITECH V3 RMIM NCPDP CDA + Templates V 2.5.1 CCR Application Data Model Application Database HIPAA X12 Application Database Application Database

  8. Benefits and Issues • Mappings reveal the problems clearly and early • Any-to-any translations can be generated from the mappings (=>rapid testing) • By mapping an application data model to CDA, you will get translations to and from CDA, V2.5.1, CCR …. • Managing templates is a big problem • Versions are a big problem

  9. Semantic Mappings - Summary • Declarative, simple where they can be simple, viewable (e.g. Excel) • A specification for semantic interoperability • Auto-generate runnable transformations • N*(N-1) transformations from N sets of mappings • Rapidly testable (=> test-driven mapping) • Mapping exposes semantic problems (gaps, ambiguities)

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