TRANSFoRm: Translational Research and Patient Safety in Europe The TRANSFoRm Consortium. Contacts: Co-ordinator – Professor Brendan Delaney, Guy’s and St Thomas’ Charity Chair in Primary Care Research, Dept of Primary Care and Public Health Sciences, King’s College London Technical Director – Dr Adel Taweel, Dept of Computer Science, King’s College London Project Administrator – Ms Rhosyn Tuta Workpackage Leads: Prof Paul van Royen, University of Antwerp, Dr Olga Kostopoulou, King’s College London, Prof Christian Ohmann, University of Dusseldorf, Prof Tom Fahey, RCSI Dublin, Dr Theo Arvanitis, The University of Birmingham, Prof Frank Sullivan, University of Dundee, Dr Siobhan Clarke, Trinity College Dublin, Dr Alec McLean, Quintiles UK, Dr Wolfgang Kuchinke, University of Dusseldorf. TRANSFoRm is part funded by the European Commission DG INFSO (FP ) The European policy context The EU has a longstanding strategy to promote greater safety and productivity for EU healthcare via advanced ICT, part of a broader strategy for growth and development via ICT known as i2010. This has been supported by several European Commission ‘Communications’ and a programme of scientific projects funded through the ‘Framework Programme’, currently FP7. These include: Cross-border interoperability (COM 3282) Empowerment and evidence-based care (COM 630) “together for health” There is also an intention to improve uptake and ease of use of the eHR, and to promote the development and adoption of international standards including Hl7, CDISC, BRIDG and CEN/ISO The TRANSFoRm project was funded under a competitive call from the ICT (Health) FP7 Work Programme, with the aims of: 1.Enabling integration between eHR and research information systems. 2.Enabling effective knowledge translation to support patient safety. These two aims are best encapsulated by the term ‘The learning Healthcare System’. SAFER CLINICAL PRACTICE MORE RESEARCH EVIDENCE TRANSFoRm -INTEGRATION -INTEROPERABILITY -SERVICES KNOWLEDGE TRANSLATION EPIDEMIOLOGICAL STUDIES AND RCTS The learning healthcare system Three Primary Care-based use cases span the project The project is based in Primary Care in Europe. The purpose of the three use cases is to: 1.Define the technical requirements. 2.Delineate the space within which regulatory issues, privacy, security and provenance will operate. 3.Lead to the development of technical validation and pilot studies in year 5. 4.Lead to proposals for full clinical studies to be funded subsequently. The projects are: 1.Genotype-phenotype study of a) risk of complications and b) response to oral therapy in Type II Diabetes Mellitus 2. Cohort study and an RCT of Proton pump inhibitors in Gastro-esophageal reflux disease. 3. Decision Support for the primary care diagnosis of Chest Pain Abdominal Pain Shortness of breath Supporting Clinical Research Semantic interoperability – shared detailed clinical concepts – linking ISO to a meta-data registry (ISO 11179) Shared processes – Middleware modules support business processes and integration of systems Standards-based representation of protocols – PCROM integrated with HL7 RIM via BRIDG Supporting Clinical practice User interface – APIs, open-source, object oriented ‘widgets’ support capture of detailed clinical concepts (Archetypes) AND support both decision support and research support Knowledge layer – web-services deliver evidence and business process rules to the eHR interface Clinical evidence – Clinical prediction rules and diagnostic evidence maintained via a diagnostic ontology Interoperability of research data Model based –CDISC ODM –BRIDG –PCROM ISO/IEC Metadata Registry standard Integrate Vocabulary service, Metadata registry and core interoperability model as a seamless service. CEN/ISO 13606: independence of semantic representation, terminology, interfaces and data storage is essential to progress the learning healthcare system. eHR Interface Clinical terminologies Semantic representation of clinical concepts Database The core informatics concepts behind the project Integration of Concepts –Development of Primary Care Research Object Model and map to BRIDG 3 –Detailed Clinical Models/Archetypes to jointly represent clinical and research data Integration of Terminology –LexGRID 5.0 for vocabulary services, enriched with ICPC2 Integration of Language –Essential in an EU context Using the models, based on use cases, to inform the development of sevices and middleware that have shared concepts: –Provenance model –Protect the data via provenance and common security model –A clinical prediction rule ontology and web- service –Middleware based on open source and standards and able to work with other standards-based systems Integration of detailed clinical information using Archetypes –A computable expression of a domain content model in the form of structured constraint statement based on a reference information model) –Often encapsulated together in Templates –Sit between lower level knowledge resources and production systems –Independent of interface and system Moving beyond simple interoperability of data to workflow integration For research –Seamless prompts, reminders and data collection For clinical practice –Stand alone diagnostic decision support systems have failed –Strong emphasis on development from decision science experimental approach Prompting v Alerting Data entry interface and design Knowledge translation Understanding how diagnostic decision support systems (DDSS) work with human judgment rather than as a substitute for it is essential. The project will explore, by an experimental study, the role of prompting with a list of differential diagnoses and alerting for potential missed diagnoses. In order to build DDSS integrated with the eHR we need to enable a much finer granularity of interaction between the eHR, the clinician and the underlying evidence. We will use the CEN/ISO standard to link evidence, in the form of an ontology of clinical prediction rules and likelihood ratios for symptoms and signs with clinical observations. Innovative user interface designs will be explored. The project takes the approach of developing and extending: -Use cases based on clinical projects -Models based on use cases and mapped to standards -Software development based on objects, standards and open source principles Outputs of the project will be: -Principles, innovative methods and approaches -Models, policies and frameworks -Models and software (both end user services and middleware) to support the learning healthcare system