1. Archetypes in HL7 v2 Andrew McIntyre Medical-Objects HL7 International May 2009

2. Overview HL7 v2 in widespread use in Australia Many legacy applications Administrative models well covered Limited support for Clinical Models Need for Structured Clinical data SNOMED-CT support Patient history/Family History transfer Decision Support Registries Archetypes allow detailed Clinical Models No changes required to standard Backward compatible

3. Long-term goals Support of Complex Clinical Models No limit on complexity Allow reuse of models Represent model in V2/V3/CDA/CCD formats Smooth migration of legacy applications Complexity hidden from legacy applications Common clinical models in use Allows data transfer across systems Allows data transfer across encodings Allow rich SNOMED-CT use Support post-coordination

4. The Present Australian Situation Clinical Models basic Blob of text in single OBX Blob of RTF (un-escaped) in single OBX Little or No semantic interoperability Opaque documents eg. PDF No atomic data, minimal terminology Pathology Models improving Atomic data Terminology (LOINC) in private labs Hamstrung by unreliable imports of HL7 Many packages lack CE (Coded Entry) support

5. Development up to present 2006: Archetypes in V2 implementation Part of Medical-Objects ITOL project Lymphoma wizard Archetypes for Registry notification Archetypes for GLIF/GELLO data structures Total HL7 solution Experience used to inform standards work Proven round trip semantic interoperability CEN Archetypes used Used for AS4700.2 Lab system with GELLO Messages are being delivered to existing PMS systems now

6. Archetypes Built on a domain model CEN 13606 – European Standard OpenEHR Domain model is mappable Existing HL7 V2 data models Medication/Allergies already exist Archetype content is mapped to OBX segments or messages Existing HL7 semantics are preserved Existing applications are mostly unaware Minimal overhead

7. Archetypes Describe semantic relationships Between atomic data items Between archetypes Between/within terminologies Constrain data Occurrences Cardinality Terminology Datatypes/Constraints Provide metadata that is lacking Potential overlap with SNOMED-CT/V3 models Minimal overlap with V2 Exception is Medications/Allergies

8. Archetypes Allow organisations to define data structures Discharge summaries Registry notification Referral requirements/prerequisites Notifications EHR notes transfer Ideally standard Archetypes used Allow easy interoperability Some metadata better than none however Decision support needs flexibility to define its own custom data structures

9. Archetype Options CEN Archetype Generic structure Standards based Developed in conjunction with OpenEHR OpenEHR Similar to CEN Have diverged Extended semantics that are OpenEHR specific Not a formal standard

10. CEN Philosophy The challenge for EHR interoperability is to devise a generalised approach to representing every conceivable kind of health record data structure in a consistent way. This needs to cater for records arising from any profession, speciality or service, whilst recognising that the clinical data sets, value sets, templates etc. required by different health care domains will be diverse, complex and will change frequently as clinical practice and medical knowledge advance. This requirement is part of the widely acknowledged health informatics challenge of semantic interoperability.

11. Example Archetypes

12. Archetype Data Model An Identifier for the Archetype A tree of Atomic data elements Elements map to single OBX OBX - 4 Observation sub ID used Organised by Non Terminal Nodes Nodes usually descriptive Data does not change Not required for semantics as can be inferred Useful for human readers Headers Represented by display OBX segment Data model is not the same tree as metadata Occurences > 1 in archetype requires extra nodes

13. The HL7 V2 Version Archetype Nodes have –Cardinality –Occurrences The data structure is similar to an xml representation –Dotted SubID used to build the tree

14. OBX Tree Structure Only nodes that are valued need inclusion Missing nodes inferred by Archetype Requires receiver to have access to archetype for Semantic interoperability

15. Walking the path OBX|6|NM|163031004^diastolic^SNOMED-CT^at0005^^openEHR- EHR- OBSERVATION.blood_pressure.v1|1.1.1.1.1.1.1.1.2|100|mm[Hg]^^I SO+|||||F

16. Overview of encoding Three OBX types: Header RP Segment –OBX|1|RP|ENTRY^^EN 13606|1|openEHR-EHR- OBSERVATION.blood_pressure.v1^Blood pressure measurement&99A-A892E160ECDB6613&L^TX^Octet- stream||||||F Non Terminal OBX –OBX|6|CE|15431-0^^LN^CLUSTER^^EN 13606|1.1.12|103764000^Non reportable items^SNOMED- CT^at0047^Non reportable items^CEN-FULL-BLOOD- COUNT.v1||||||F Terminal OBX – Data –OBX|2|NM|14749-6^Glucose^LN^22569008^^SNOMED- CT|1.1.6|7.8|mmol/L^^ISO+|<7.8|+|||F

17. Potential Alternatives CDA Solves problem of inadequate HL7 parsers This is small piece of puzzle however Does not solve all semantic issues Minimal existing CDA support in Australia Requires overnight upgrade of all pms systems CCR/CCD ASTM standard +/- CDA format ?Useful for GP interoperability project Could be archetyped and carried in V2 Handbooks Provide detailed Human readable specs Has not worked to date

18. Conclusions Archetypes allow data models to be defined Usable in HL7 V2 and CDA Archetypes in V2 would allow migration Requires solid HL7 parsers Prerequisite for any semantic interoperability Investment required in low level technology Standards Compliance Would improve quality of existing messages Allows possibility of taking next step Common archetypes ideal Useful without this however