Semantic Interoperability

A complex and multi-level issue This is more than a discussion about whether we should adopt SNOMED or not It is a difficult issue that will require a stepwise approach Because of the complexity itself Because of the costly change or replacement of legacy systems Because of ‘psycho-political’ issues EU versus US Best theoretical model versus actually used Because of technical/scientific issues (ontology and information model discussions) Therefore: “Think big, act small” “Big” in time: foresee the future “Big” in space: global universal “Big” in scope: health care + life sciences Mark the road and act consistently in the same direction but with small steps

Think big The ultimate goal is defined in the ‘Semantic Web Stack’ designed by Tim Berners Lee, the inventor of the www Ultimately we need to be able to share ‘proofs’ and ‘trust’ to fully be interoperable Even if I understand the meaning of what you say, are you entitled to say this anyway ?

‘Semantic’ & ‘Interoperability’ The scope ‘Semantic’ & ‘Interoperability’ Semantic= understand the meaning Need to standardize both domain and clinical content of the information The content: e.g. the clinical data itself: patient x has ‘hypertension’  terminologies, classification systems (ICD, SNOMED, IPCP, …) The domain: e.g. hypertension is a ‘medical condition’  domain ontologies and reference models such as EN 13606 (OpenEHR) with archetypes, HL7 RIM with templates, CDA, CDISC Interoperability= being able to collaborate Need to standardize the communication itself (exchange models): HL7 V2.x, V3, CEN 13606, XDS Need to standardize distributed and adaptable workflow: still a major challenge Decision support: how can we share rules and guidelines ? no standard yet Proof and trust: no standards yet We are only at the beginning …

EU Member states are not aligned Challenges No unified approach between US and EU, although both are on speaking terms This is a blocking factor for development and implementation of concrete projects because of the international scale of some of the stakeholders (e.g. industry) A lot of work to re-factor existing systems: need for resources from both industry and customers Clinical care and Clinical Research are still silos (although this meeting proves that things are changing) Still a lot of psychological – scientific – political discussion on the reference model (Open EHR versus HL7 RIM) EU Member states are not aligned

Proposals for next steps (1/3) We need to make clear statements on where we are heading to and what the current status is Who is ‘we’ ? The EC, The industry, the customers, global initiatives like IHE, the member states Need for a concrete roadmap with timeline: this helps industry and customers to plan ahead Be realistic the holy grail does not exist Therefore: adopt the IHE model: bring industry + customers together The ultimate validation comes from customers IHE has proven that it can be done (profiles, XDS, …). Let’s take the same approach and put our semantic interoperability under this umbrella Make EU – US consolidation a priority ! Redesign our European approach, if necessary Redesign the US approach, if necessary

Proposals for next steps (2/3) Give incentives for semantic interoperability Proposals for FP7 and FPx calls should take this into account Instead of (only) giving funding for the development of European standards give incentives for efforts to consolidate global standards Foster translational medicine initiatives (connect HC and LS) The W3C HCLS Interest Group For example the DebugIT project Fund interoperability projects of the stakeholders It is more than ‘just’ a technical implementation issue Stakeholders are asked to invest in the ‘bigger’ picture. This requires vision, resources and courage

Proposals for next steps (3/3) In the translational medicine domain Involve drug agencies of the member states Open and standardized access to be used for decision support systems Standardize adverse event reporting in the clinical IT systems Standardize results and outcome of clinical trials let clinical IT systems have computer readable access to evidences Support IHE initiatives for profiling ‘secondary use of clinical data’