EuroRec Annual Conference 2006 EHR systems and certification Archetypes: the missing link? Dr Dipak Kalra Centre for Health Informatics and Multiprofessional Education (CHIME) University College London Dr Dipak Kalra Centre for Health Informatics and Multiprofessional Education (CHIME) University College London

Presentation outline What is the challenge? What are archetypes and what do they do? What does one look like? More about archetypes the requirements the information model archetypes within the standard the tools Archetype quality criteria: the openEHR Clinical Review Board Certifying archetypes: Q-REC and EuroRec

The challenge: Semantic Interoperability the meaningful sharing and combining of health record data between systems the consistent use of modern terminology systems and medical knowledge databases the integration and safe use of computerised protocols, alerts and care pathways by EHR systems data quality and consistency to enable rigorous secondary uses of longitudinal and heterogeneous data: public health, research, health service management

Responding to the challenge Standardising the capture, representation and communication of clinical (EHR) data: generic models for representing clinical data e.g. ISO/EN Part 1, HL7 CDA Release 2 clinical terminology systems e.g. LOINC, SNOMED-CT agreed clinical data structure definitions archetypes = formal representations of “EHR-domain” knowledge

Where is EHR-domain knowledge found today? clinical guidelines and care pathways the data schemata (models) of existing clinical systems the lay-out of computer screen forms used by these systems for data entry and for the display of analyses performed data-entry templates, pop-up lists and look-up tables used by these systems shared-care data sets, messages and reports used locally and nationally templates and forms used for the documentation of clinical consultations or summaries within paper records health information used in secondary data collections the pre-coordinated terms in terminology systems

Problems with this EHR domain knowledge, today embodied in guidelines, existing EHR systems, message definitions, paper documents etc. not sharable between formats and systems multiple overlapping definitions with no ability to cross- reference those that exist good domain modelling practice cannot be shared few of these formats cater for knowledge evolution authorship is driven by ad hoc teams systems expertise dominates over domain expertise data instances don’t usually reference the knowledge artefact used to “shape” them

Archetype Definition 1. An EHR archetype is an agreed, formal and interoperable specification of the data and their inter-relationships that must or may be logically persisted within an electronic health record for documenting a particular clinical observation, evaluation, instruction or action 2. An openEHR / EN archetype represents this specification as a set of constraints, expressed in a standardised form, for instantiating a particular EHR Reference Model

What’s 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

Adverse reaction (web browser view: Ocean Informatics)

Ancestry Archetypes originate from R&D results, , arising from: EC Framework project: GEHR, Synapses, Synex The Good Australian Health Record Project unified and developed further by the openEHR Foundation There have been several stages in the evolution of the work, each has been implemented and piloted in live clinical demonstrators The archetype approach is now being standardised by CEN TC/251 in EN 13606

Archetype representation requirements - in EN Definition: core clinical concept Description sets: usage and evidence in different languages Publication status Data structure node-by-node constraints Mapping these to attributes, associations and necessary context in an EHR Reference Model Data value constraints Term and concept bindings Conditional references to other EHR instances

13606 Part 2 Archetype Model

Archetype Definition Language Assertion syntax derived from F-logic specially designed to represent constraints on a reference model Currently the most complete representation of an archetype Used by the current generation of (open source) authoring tools Included in as an optional exchange format for archetypes NOT assumed or required to be the way archetypes are actually used within EHR systems

13606 Parts 1 & 2: EHR Extracts and archetypes System A SenderSystem B Receiver EN Common Archetype Reference Model conforms to TRANSFORM Merge Extract EHR Extract Data Capture using EHR-AEHR-B Archetype Library based on selected from Interpretation points to Query uses FORM TRANSFORM Care Pathway Archetypes using Archetypes

Archetype tools A few authoring tools are already in use all conform to the same model all use Archetype Definition Language as the persisted form A workbench tool may be used to review the inside of an archetype or to examine the library of archetypes in a repository Parsers can validate archetypes against the formal specification EHR servers are in development that will use archetype information to validate instances and retrieve or query EHR data using archetypes

Adverse reaction (editor view: University of Linköping)

Archetype Editor: University of Linköping - Family History

Archetype Editor: University of Linköping - Blood pressure, binding to SNOMED CT and to UMLS

Archetype Editor: Ocean Informatics - Blood pressure

Archetype Workbench: Ocean Informatics

catalogue, synthesise Templates, forms, data sets, clinical guidelines, used in real, diverse health settings Formal representation of detailed clinical models (archetypes) Detailed Clinical Models A collaborative project of openEHR & HL7 develop guidelines for “good” archetypes and templates Data element collections Indexed repository (ADL+OWL?) mapped to and used within: openEHR Reference Model CEN/ISO HL7 R-MIMs

The missing link? 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 The next 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

The openEHR Clinical Review Board Recently established to oversee the authorship, peer review and governance arrangements for archetype development to specify the requirements for archetype tools and repository services to collate and share the experience of archetype development and use internationally and to collaborate with other bodies wishing to adopt the archetype approach within products or as part of their e-Health programmes

Q-REC Inventory and Register of EHR Archetypes (It is not the goal of Q-REC to develop archetypes) The goals are: to identify high quality archetypes which will have been developed elsewhere and to make them available to a broader community to develop formal methods of validating the design and content of archetypes to develop a formal process of verification and certification for archetypes to develop, in collaboration with the openEHR Clinical Review Board, an archetype repository

The value of archetypes Empowerment of healthcare professionals enable clinical data sets and structures to be shared enable managed clinical and health service evolution Offer a tractable way of binding generic EHR models to compositional terminology Provide target knowledge representations for use by guideline and care pathway systems EHR entries identify the Archetypes used when the data were created, and/or to which they map aids future interpretation, analysis, computation contributes towards semantic interoperability