Trustworthy Reuse of Health Data “Perspective from the EU” Prof . Dr. Georges De Moor, Ghent University, Belgium

2. Trustworthy Reuse of Health Data “Perspective from the EU” Prof. Dr. Georges De Moor, Ghent University, Belgium EuroRec President European Institute for Health Records

3. The European Continent and the E.U. Population Europe = 720 million Population E.U. = 500 million Only “European” part of Russia and Turkey included From Wikipedia, the free encyclopedia

4. Europe Figures for the population of Europe vary according to which definition of European boundaries is used. According to the United Nations, the population within the standard physical geographical boundaries is about 720 million using the definition which has been used for centuries. The European Union (E.U.) population is about 500 million. There are 27 E.U.- Member States and each is responsible for its own National Health System (cf. subsidiarity principle). There is no central Health Authority in Europe. 17 countries have adopted the Euro as currency: they constitute together the Eurozone. The languages of the European Union are languages used by people within the member states of the European Union. They include the 23 official languages of the European Union along with a range of others. The most widely spoken mother tongue in the EU is German, while 51% of adults can understand English. The eHealth market is highly fragmented (e.g. over 900 EHR system vendors).

5. Back to Confucius… “… is truth best apprehended in terms of many little things or in terms of one big thing? …” 551 BC - 479 BC (Ben T. Williams, Computer Aids to Clinical Decisions, CRC Press, 1982)

6. Accelerating and Leveraging Knowledge Discovery “… many little things …” Real fine-grained Patient Level Data (fromrepresentativesamples of longitudinal EHRs) interpretation Information E.B.M. interpretation Knowledge

7. E.B.M. E. ? B. M. Data E xplanation Based Medicine Patient (personalised medicine) Information E conomy Based Medicine Health Authorities (cost containment) Knowledge E vidence Based Medicine Clinicians (treatment protocols, care pathways, clinical guidelines, decision support systems, ¨VPH” & other models)

8. A Caricature Data Explanations Patient Care LOCAL/ REGIONAL Information Economy Health Reforms NATIONAL Knowledge Evidence Science GLOBAL (Wisdom)

9. Stakeholders (cf. perceived benefits) Patients Clinicians (in Primary, Secondary and Tertiary Care settings) Clinical Investigators Contract Research Organisations (CROs) Pharmaceutical Industry Hospital Administrators Academia EHR Systems Vendors Trusted Third Parties (TTPs) and Trusted Services Providers (TSPs) Health Authorities Health Care Planners Regulators

10. Stakeholders and Forces in Place Who can influence? … the one who … pays / invests ? regulates ? knows? (and many other: e.g. who owns, who…?)

11. ClinicalTrials OtherResearch … Adverse Event Registries Marketing Knowledge Bases & Models (VPH) Public Health Management Decision Support Systems EHRs and some examples of data Re-use Patient TRUST Clinicians (PHR) EMR PrivacyEnhancing Techniques Billing

12. Trustworthy Reuse of Health Data • “Perspective from the EU” • Focus of this presentation on: • the EHRs as data sources • and • the reuse of data for Research

13. What is an Electronic Health Record? • “One or more repositories, physically or virtually integrated, of information in computer processable form, relevant to the wellness, health and health care of an individual, capable of being stored and communicated securely and of being accessible by multiple authorised users, represented according to a standardised or commonly agreed logical information model.  Its primary purpose is the support of life-long, effective, high quality and safe integrated health care” • (Kalra D. Editor. Requirements for an electronic health record reference architecture. ISO 18308. International Organisation for Standardisation, Geneva, 2011)

14. EuroRec • The EuroRec Institute (EuroRec) is a European independent not-for-profit organisation, whose main purpose is promoting the use of high quality Electronic Health Record systems (EHRs) in Europe. • EuroRec is overarching a permanent network of national ProRec centres and provides services to industry (developers and vendors), healthcare systems and providers (buyers), policy makers and patients. • EuroRec produced and maintains a substantial resource with ± 1700 functional quality criteria for EHR-systems, categorised, indexed and translated in 19 European languages. The EuroRec Use Tools help users to handle this resource.

15. EHRs: Trends… • Patient-centered (gatekeeper?) and longitudinal (life-long) records • Multi-disciplinary / multi-professional/ participative • Transmural, distributed and virtual(incl. cloudcomputing and apps) • Structured and coded (cf. semanticinteroperability) • More metadata(tagging and coding!) in EHRsatgranularlevel • Intelligent (cf. decisionsupport modules, clinicalpathways, VPH models…) • Personalised (the specificdata fromindividual patients used in models) • Preventive • Predictive(use of personalgenetic data in predictivemodels ) • More sensitive content (privacy protection!) • Integrative

16. Towards Integrated Health Biosensors Genomic data Environmental Data Phenomic data Integrated Health Records

17. The growing role of EHRs in Translational Bioinformatics • The implementation of EHRs in inpatient and outpatient settings is expanding rapidly, providing large patient-based longitudinal data sets. • In parallel genotyping technology is also advancing quickly. • There is therefore an increasing potential to bring functional genomics and genetics data to the “bedside”. • The potential impact is very large in terms of personalisedmedicine, pharmacogenomics, redefining diseases classification and understanding drug repositioning. • EMBL-EBI IndustryProgramme Workshop (28th to 29th February 2012).

18. A Two Way Translational Challenge • The bio-informatics research communities need to understand better the kinds of diverse inputs that different professionals and specialties have to interpret, the kinds and quality and time spans of data that need to be co-interpreted, the nature and criticality of the decisions being made, and how accurate the modeling projections would have to be in order to be useful. • Reciprocally, clinical communities need to understand better what future opportunities and solutions are in the pipeline, how these might impact on care decisions, any adaptations to physical and virtual team-working that should be anticipated and prepared for.

19. Significantchanges in ICT to beanticipated… • Everything driven by “BIG” data (genomics, proteomics, metabolomics…): processes in healthcare are data intensive! • In 2008: 1bn PCs (today: shift also from personal to personalised computing!) • In 2020: 10 bnmobile connected devices …Mobile computing will further encourage people to use web services more often (in Q4 2011: already more than 1 million Apps from within the group of bigger stores, incl. approx. 20000 are health related applications) • Will the rise of the Cloud create an explosion of consumer focused web services, also including cloud based Personal Health Records to be directly adopted by consumers?

20. Cloud Computing Cloud computing is no longer a buzz term but a reality … With the opportunity for on–demandSoftware-as-a-service, migrating IT services to the clouds is an opportunity that is hard to ignore… But cloud computing on itselfwillnotsolve the real problems in eHealth

21. Recent & Ongoing Projects with Involvement of EuroRec

22. Unlocking the Data: many E.U.-Projects

23. The EHR4CR Project A joint undertaking between Academia & Industry Overview of the EHR4CRproject Electronic Health Record systems for Clinical Research

24. Electronic Health Records for Clinical Research • The IMI EHR4CR project runs over 4 years (2011-2014) with a budget of +16 million € : • 10 Pharmaceutical Companies (members of EFPIA) • 22 Public Partners (Academia, Hospitals and SMEs) • 5 Subcontractors • Mats Sundgren(EHR4CR Coordinator, AstraZeneca) • Georges De Moor (EHR4CR ManagingEntity, EuroRec) • The EHRCR project is - to date - one of the largest public-private partnerships aiming at providing adaptable, reusable and scalable solutions (tools and services) for reusing data from Electronic Health Record systems for Clinical Research. • Europe is uniquely placed for large scale reuse of health data: the widespread adoption of eHealth, the variety of health environments and the diversity in its population offer the opportunity to exploit a wealth of “real world” data that will help better understanding more complex health problems (e.g. co-morbidity in ageing population etc.)

25. Partners

26. Project Objectives • To promote the wide scale re-use of EHRs to accelerate regulated clinical trials, across Europe • EHR4CR will produce: • A requirements specification • for EHR systems to support clinical research • for integrating information across hospitals and countries • The EHR4CR Technical Platform (tools and services) • The EHR4CR Business Model, for sustainability • Pilotsfor validating the solutions (i.e. the TP and the BM)

27. The Scenarios • Clinical Trial Feasibility (= the year 1 focus) • Patient Recruitment (*) • Clinical Trial Execution • Drug Surveillance Reporting • across different therapeutic areas (oncology, inflammatory diseases, neuroscience, diabetes, cardiovascular diseases etc.) • across several countries (under different legal frameworks) A joint undertaking between Academia & Industry • (*) half of all Pharma Phase III trial delays are due to recruitment problems!

28. The Business Model Specify in detail the product and service offering; Include an impact analysis on multiple stakeholders; Deliver a self-sustaining economic model incl. sensitivity analysis; Define governancearrangements for the platform services; Define operating procedures and Trusted Third Party service requirements; Identify the value proposition and incentives for each of the key players and stakeholders impacted by EHR4CR; Define accreditation and certification plans for EHR systems capable of interfacing with the platform; Define a roadmap for pan-European adoption and for funding future developments. A joint undertaking between Academia & Industry

29. The Technical Platform Support the feasibility, exploration, design and execution of clinical studies and long-term surveillance of patient populations; Enable trial eligibility and recruitment criteria to be expressed in ways that permit searching for relevant patients across distributed EHR systems, and to confidentially initiate participation requests via the patients’ authorisedclinicians; Provide harmonisedaccess to multiple heterogeneous and distributed EHR systems and integration with existing clinical trials infrastructure products (e.g. EDC systems); Induce improvements of data quality to enable routine clinical data to contribute to clinical trials, and importantly vice versa, thereby reducing redundant data capture. A joint undertaking between Academia & Industry

30. The First Year Results (1) Platform Architecture Design A joint undertaking between Academia & Industry

31. The Semantic Interoperability Issue • A Semantic Interoperability Layer is part of EHR4CR Platform Architecture • Semantic Interoperability and Data Quality Markers: • in CARE: Faithfulness (cf. biases in coding, window dressing for reimbursement) • in RESEARCH: Faithfulness and Consistency • Importance/Specificity of Context (depending on the context in which data are captured, the meaning and the value of the data may vary…)

32. rapid bench to bed translation / personalised care real-time knowledge directed care Wellness Fitness Complementary health Public health Health care management Clinical audit Education Research Epidemiology Data mining implied consent de-identified Disease registries Screening recall systems Social care Occupational health School health Teaching Research Clinical trials explicit consent Long-term shared care (regional national, global) Citizen in the community Point of care delivery Continuing care (within the institution) +/- consent Health Information Flows needing Interoperability (Kalra D., UCL, UK) implied consent

33. Semantic Interoperability Resource Priorities • Widespread and dependable access to maintained collections of coherent and quality-assured semantic resources • clinical models, such as archetypes and templates • rules for decision making and monitoring • workflow logic • which are • mapped to EHR interoperability standards • bound to well specified multi-lingual terminology value sets • indexed and correlated with each other via ontologies • referenced from modular (re-usable) care pathway components • SemanticHealthNet will establish good practices in developing such resources

34. ARGOS semantic interoperability recommendations Nine strategic actions that now need to be championed,as a global mission 1. Establish good practice 2. Scale up semantic resource development 3. Support translations 4. Track key technologies 5. Align and harmonisestandardisation efforts 6. Support Education 7. Assure quality 8. Design for sustainability 9. Strengthen leadership and governance (10. Support Research)

35. Book (IOS Press: editor Georges J.E. De Moor) A TRANS ATLANTIC PROJECT • Foreword by Herman Van Rompuy‐ E. Council President • Memorandum of Understanding signed by: • NeelieKroes - Eur. Commission Vice-President • Kathleen Sebelius – Secretary of HHS • Policy briefs for Transatlantic cooperation • The current status of Certification of Electronic Health Recordsin the US and Europe • Semantic interoperability • Modeling and simulation of human physiology and diseases with a focus on the Virtual Physiological Human • Policy Needs and Options for a Common Approach towards Measuring Adoption, Usage and Benefits of eHealth • eHealthInformatics Workforce challenges A NEXT TRANS ATLANTIC PROJECT? … on reuse of Health data for Research?

36. Use of the EHR4CR Platform Global National Regional Local Personal

37. Platform: Use (and Migration?) (within 2 years?) Global National On-demand- software as- a- service Regional Local Personal

38. The First Year Results (2) Year 1 Focus: Protocol Feasibility (Scenario 1) Through detailed engagement with protocol managers within Pharma and the wider clinical research community, workflows were documented for establishing the feasibility of a trial protocol (is a protocol viable? Fine tuning the eligibility criteria to optimise trial design) A joint undertaking between Academia & Industry

39. The First Year Results (3) A formal and validated Software Requirements Specification • Contains approx. 75 use cases, over 200 requirements, a first user interface mock-up and a set of generic non-functional requirements. A joint undertaking between Academia & Industry

40. The First Year Results (4) An Inventory of Pilot Site EHR data items A joint undertaking between Academia & Industry • A top list of data elements has been identified (containing 81 EHR data elements) resulting from comparing commonly used eligibility criteria by the EFPIA partners with available data elements in the EHR/CDW and CDMS at the pilot sites. • - The current listing represents the first version of the data inventory. • - To validate and refine the data inventory a data export at all pilot sites has been performed. • - This has delivered information on the availability of the data elements at the sites.

41. The First Year Results (5) Business Modelling and Value Proposition • Business Model Template • SWOT Analysis Matrix • PEST Analysis Matrix A joint undertaking between Academia & Industry (Dupont D. Data Mining International)

42. Accreditation and Certification A joint undertaking between Academia & Industry • Accreditation of Clinical Research Units (ECRIN) and Certification of EHR systems (EuroRec) will accelerate the adoption of a more harmonised approach throughout Europe and serve as a powerful means for ensuring to the pharmaceutical industry the reliability and trustworthiness of the research partners (i.e. of the data providers, e.g. the hospitals). • Both the vendors of certified products and the accredited hospitals (with source data) will have a competitiveadvantage.

43. EuroRec profile for EHRs that are compliant with Clinical Trials requirements • Already in December 2009 EuroRec released a profile identifying the functionalities required of an EHR system in order to be considered as a reliable source of data for regulated clinical trials. • Details of the profile, including information designed to support use, are accessible from the EuroRec website. A sister profile has been endorsed by Health Level Seven® (HL7®). • As both the EuroRec and HL7 profiles draw upon the same standard requirements for clinical trials, ”conforming to one” will mean, in principle conformance to both. • These requirements have contributed into a Work Item in ISO (TC/215), to help shape a future International Standard. • The EHR4CR Project will expand the set of quality criteria for EHRs to be used for research…

44. The First Year Results (7) Other early deliverables … A joint undertaking between Academia & Industry • Overview of relevant IT standards • An inventory of information and knowledge models • An inventory of available and re-useable components meeting the functional and non-functional requirements • Requirements and specifications of the Security and Privacy Services • Definition of EHR4CR Information Models • Data acquisition specifications, concept for local interfaces • Dissemination material • …

45. The First Year Results (6) Publications A joint undertaking between Academia & Industry Business Strategy

46. Unlocking the Data: many E.U.-Projects

47. E.U.-Projects need to Converge ! Multiple Sources Clinical Data Warehouses Registries EHRs from Hospitals EHRs in Primary Care Settings Bio Banks Personal Health Records Bio-Informatics DBs … EuroRec Annual Conference: “Convergence Workshop” (Basel, Nov. 8, 2012)

48. Privacy Enhancing Technologies De-identification… pseudonymisation… sticky policies in EHRs… Reconciling the concept of a “central anonymous database” with “nominative access”… (Claerhout Brecht,Custodix NV, Belgium)

49. Privacy and Scientific Research !!! Restriction on access to available data is a major obstacle….

50. End THANK YOU! Prof. Dr. Georges J.E. De Moorgeorges.demoor@ugent.behttp://www.eurorec.org