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Certification of EHRs: The Q-Rec Repository for Archetypes Dr Dipak Kalra University College London [email protected] World of Health IT 2007 Q-Rec’s Objectives • To develop formal methods and a mechanism for the quality labelling and certification of EHR systems in Europe in 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) 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 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 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 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 NHS Adverse Event archetype (draft) Example archetypes: from openEHR.org A growing library of archetypes 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 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 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 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 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 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 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 For more information about The EuroRec Institute and Q-Rec www.eurorec.org