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Certification of EHRs: The Q-Rec Repository for Archetypes

Certification of EHRs: The Q-Rec Repository for Archetypes. Dr Dipak Kalra University College London d.kalra@chime.ucl.ac.uk. World of Health IT 2007. Q-Rec’s Objectives.

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Certification of EHRs: The Q-Rec Repository for Archetypes

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  1. Certification of EHRs:The Q-Rec Repository for Archetypes Dr Dipak Kalra University College London d.kalra@chime.ucl.ac.uk World of Health IT 2007

  2. Q-Rec’s Objectives • To develop formal methods and a mechanism for the quality labelling andcertification of EHR systemsin Europein primary care and in acute hospital settings • EuroRec Institute is coordinating partner • QREC has 12 partners and 2 subcontractors • Project duration is 30 months (Jan 2006 - Jun 2008)

  3. The Q-Rec repository • The Q-Rec repository will comprise several kinds of artefact relating to the quality labelling and benchmarking of EHR systems: • EHR system requirements • EHR system conformance criteria • EHR system test plan items • An inventory of quality labelled (certified) EHR systems • An inventory of EHR related standards • An inventory of terminology and coding schemes • A directory of certified EHR archetype repositories • A directory of reviewed open source specifications and components

  4. The Q-Rec repository • The Q-Rec repository will comprise several kinds of artefact relating to the quality labelling and benchmarking of EHR systems: • EHR system requirements • EHR system conformance criteria • EHR system test plan items • An inventory of quality labelled (certified) EHR systems • An inventory of EHR related standards • An inventory of terminology and coding schemes • A directory of certified EHR archetype repositories • A directory of reviewed open source specifications and components Focus of this presentation

  5. A reminder about archetypes • A formal, rigorous and standardised (interoperable) specification for a representation of a clinical data structure within an electronic health record • de facto (in use) or • agreed consensus or • best practice • Formal knowledge models of clinical domain concepts • e.g. “blood pressure”, “prescribed drug”, “fundoscopy examination” • Define data quality constraints to be placed on the organisation and content of record entries • specify which EHR constructs are to be used • define mandatory items, data values, bindings to terminology • may incorporate rules that enact steps within care pathways

  6. What is in an archetype? • An archetype defines a data structure, including optionality and multiplicity, data value constraints, and relevant bindings to natural language and terminology systems • An archetype might define or constrain relationships between data values within a data structure, expressed as algorithms, formulae or rules • An archetype may logically include other archetypes, and may be a specialisation of another archetype • Its metadata defines its core concept, purpose and use, evidence, authorship and versioning

  7. NHS Adverse Event archetype (draft)

  8. Example archetypes: from openEHR.org

  9. A growing library of archetypes

  10. Archetypes • Formally developed by the openEHR Foundation • European (CEN) & draft International (ISO) standard: 13606-2 • growing interest within several eHealth programmes • May be used as a clinical data mapping specification when EHR’s are communicated between systems • The combination of a generic EHR Reference Model and the use of archetypes contribute towards achieving semantic interoperability • as exemplified by openEHR and CEN/ISO 13606

  11. Towards interoperability, with quality • For EHR data to be safely communicated and interpreted, archetypes need to be well defined and well managed • The current set of challenges is: • to define good practice for archetype authorship • to improve the binding between archetype leaf nodes and large co-ordinated terminologies such as SNOMED-CT • to design ontologies to cross-reference similar archetypes and equivalent archetype nodes • to support the appropriate retrieval of EHR data instances that conform to similar archetypes

  12. Q-Rec: a directory of certified archetype repositories • It is not the goal of Q-REC to develop archetypes • The goal is to identify through an inventory and then to certify, high quality archetypes which have been developed elsewhere and to make them available to a broader community • to establish a process by which “good” archetypes can be designed • to develop formal methods of validating the design and content of archetypes • to develop a formal process of verification and certification of archetype developers and publishers • to develop, with openEHR, a best practice archetype repository specification

  13. The openEHR Foundation • Oversee the authorship, peer review and governance arrangements for archetype development • specify the requirements for archetype tools and repository services • collate and share the experience of archetype development and use internationally • collaborate with organisations and vendors wishing to adopt the archetype approach within products or e-Health programmes • collaborate with EuroRec, through the Q-Rec project, on quality criteria for archetypes

  14. Dimensions of quality, for archetypes • Clinical guidance • patient profiles and situations for which it is suitable • translations of textual content • when this archetype and the evidence should be reviewed • Transparency • clinical validation, including multi-professional inputs • the clinical evidence used, its currency • Provenance • authorship and professional endorsement • currency, version management • jurisdictional approval and formal certification

  15. Dimensions of quality, for archetypes • A declared set of clinical use cases for which EHR data instances are comparable • Inclusive (superset) of the data item requirements across those use cases • Consistent naming conventions • Minimal mandatory properties unless necessary across all of the use cases • Maximum re-use across archetypes • Simplest possible structure to meet these needs

  16. Dimensions of quality, for archetype repositories • Standardised constraint specification • Editorial approval processes • clinical verification • technical verification • Repository technical management • Semantic indexing, search and retrieval facilities • Access control and licensing • Management and distribution of updates • Certification

  17. For more information about The EuroRec Institute and Q-Recwww.eurorec.org

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