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HL7 version 3

Explore HL7v3 database models, including Object Relational Mapping (ORM), Logical Data Model (LDM), and Physical Data Model (PDM), for efficient persistence of healthcare data. Learn about versioning, temporal aspects, and data integrity rules.

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HL7 version 3

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  1. HL7 version 3 Logical and Physical Database models Scope: ORM best practices, LDM/PDM, versioning, temporal aspects Slide contents published under the Creative Commons / Attribute-Share Alike license Source: www.ringholm.de/download/HL7v3_implementation.zip

  2. Persistence Overview Slide contents published under the Creative Commons / Attribute-Share Alike license Source: www.ringholm.de/download/implementation_mechanics.ppt

  3. Database models (Relational) RIM or RIM-based model: Conceptual Data Model RIM • Logical Data Model • Not DBMS specific, no tables, no keys LDM ORM – Object Relational Mapping PDM • Physical Data Model • DBMS specific, tables, keys

  4. Conceptual Data model - RIM • Enormous flexibility, at the cost of a very abstract structure. • makes enforcement of data integrity rules very difficult making it necessary to rely on stored procedures and application logic to enforce rules. • Low number of tables • less programming work, easier to learn, easier to add new functionality. More data in each table, need to tune queries. • Main use-case: • If you're creating a data store for ad-hoc queries, mining and exploration of all sorts of data from all sorts of different sources

  5. Conceptual Data Model – D-MIM • The D-MIM approach doesn’t differ that much from a RIM approach. • Most D-MIMs touch pretty much all of the RIM from a structural perspective. • Does allow for the enforcement of specific data integrity rules • Think of a D-MIM or R-MIM as a relational "view" on the underlying RIM structures.

  6. Persistence Persisting Data Types Slide contents published under the Creative Commons / Attribute-Share Alike license Source: www.ringholm.de/download/implementation_mechanics.ppt

  7. Data Types • At a lower level, the data types are complex to support. • Complex data types • Helper classes, or UDTs • Abstract data types • Specialize; or use helper classes • Collection data types • Helper classes

  8. Normalization – Helper Classes

  9. Data Type expansion – Helper Classes

  10. Watch for “Table Explosion”..

  11. CV with R1/R2 relations

  12. UDT – Data Types • Database data types are far removed from HL7 data types • Fill gap using ORM: • Complicated HL7 data type operations may lead to full tablescans • Current implementations: very limited nullFlavor support

  13. UDT – Data Types • User Defined Types (at the DBMS level) • A form of ORM at the database level • Allows for the definition of CD with SNOMED support, II with an OID check, or PQ with UCUM validation. • Native support for HL7 datatypes in SQL. • Full nullFlavor support

  14. UDT Example: PQ

  15. UDT Example: IVL<PQ>

  16. UDT Example: CV with SNOMED

  17. Persistence Physical Database Model Slide contents published under the Creative Commons / Attribute-Share Alike license Source: www.ringholm.de/download/implementation_mechanics.ppt

  18. Minimalize Joins • Add subjectId and AuthorId to Act table (and have a participation table) • BTW: recursion was deliberately excluded from ISO/R2 Data Types. • Hibernate: tune lazy loading and fetch mechanisms.

  19. Persistence Implementation Experience Slide contents published under the Creative Commons / Attribute-Share Alike license Source: www.ringholm.de/download/implementation_mechanics.ppt

  20. OntoReason / MD Anderson Data Type Specific Table Data Type Specific Table Data Type Specific Table Data Type Specific Table Data Type Specific Table Class_value_relation is a “Triple” for all Act attributes with non-DBMS data types

  21. OntoReason / MD Anderson

  22. Any Questions ? • Or: post your question/suggestions via • HL7 Wiki: http://bit.ly/d7tSsL • E-mail v3impl@ringholm.com

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