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Innovation in Re-using EHRs for Clinical Trials The Case of the EHR4CR Project. The 9 th NRI-Conference in Promoting Health Research and Innovation May 13 th 2014 Bergen, Norway. Mats Sundgren AstraZeneca. Objectives.

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    1. Innovation in Re-using EHRs for Clinical Trials The Case of the EHR4CR Project The 9th NRI-Conference in Promoting Health Research and InnovationMay 13th 2014 Bergen, Norway Mats Sundgren AstraZeneca

    2. Objectives • Setting the Scene: the Opportunities for Efficient Clinical Research • Overview of the EHR4CR Project • The EHR4CR Platform & Services • Governance & the EHR4CR Institute • Concluding Remarks

    3. Setting the Scene: the Opportunities for Efficient Clinical Research

    4. This need has driven Life Science innovation personalised medicine Medicines in Development in 2012 A large number of medicines are in development in order to… • leverage new science • expand treatment options • improve quality of life • provide value for money Sequencing of the Human Genome Source: PhRMA 2012 Profile of the Pharmaceutical Industry

    5. The inefficiencies become obvious at the clinical trial interface Parallel industry-centric growth in ICT Physician/ Investigator Patient Care Data Electronic data capture of Clinical Trial data 57% of R&D investment is within Clinical Development1 In some countries nearly 90% of all healthcare records are digital • Over 40% of clinical trial data are entered into health record and EDC1 Patient health records Clinical trial research data 1. Integrating Electronic Health Records and Clinical Trials: An Examination of Pragmatic Issues, Michael Kahn, University of Colorado.

    6. The clinical trial journey today is fragmented with many hurdles • Key data for Pharma: • Previous trial performance in this area • Available patients with inclusion/exclusion criteria listed • Ability to access patients through referrals or other means • Evidence of good quality and operations • Data for Hospitals: • Number of Eligible and accessible patients • Knowledge of previous trial performance • Key data for Pharma: • Screening/recruitment rate • Numbers of screening dropouts • Numbers of patients randomised • Data for Hospitals: • Identification of eligible patients coming through clinic & elsewhere • Numbers that have consented & randomised • Key data for Pharma: • Country standard of care for disease area • Ethics and local regulatory knowledge • Previous trial performance in this area • Operational/scientific expertise if area is new • Data for Hospitals: • Upcoming studies that may fit • Hospital patient population and expertise TRIAL DESIGN PATIENT RECRUITMENT • Protocol design • Early feasibility • Site input • Country and early site selection • Patient recruitment/ screening • Consent • Randomisation FEASIBILITY/SITE SELECTION TRIAL EXECUTION • Detailed feasibility • Site selection • Contracting • Site training • First patient, first visit  • Visits/follow-up • Safety Reporting • Data management • Last patient enter treatment • End of study REPORTING • Data lock • End of study report • Study publication • Study outcome 

    7. There is a need to bridge the gap We have imagined an environment where de-identified patient data can be re-used within healthcare and research for clinical research purposes… • Across countries • Across systems • Across sites …to speed up protocol design, patient recruitment, data capture, safety reporting… De-identified data for Clinical Research Patient health records

    8. This can create value for hospitals • Enhanced reputation • Greater visibility of hospital/clinicians in scientific community. Improved ability to participate in/conduct clinical trials • Better patient care • Improved route to inclusion in clinical trials. Enhances treatment options, giving patients access to trial drugs and care pathways with no cost to the Trust • Better quality EHR data • Improved monitoring, performance benchmarking, reporting and management (e.g. reimbursement coding) Drives optimisationof patient care and improved efficiencies Improved clinical research Improved efficiencies and interconnectivity with other hospitals facilitates, streamlines and enriches clinical research • Income stream • Better placed to generate income from clinical research. • At a time of squeezed budgets, income from research can help drive innovation and efficiency with better outcomes for patients

    9. But a win for all stakeholders is critical • Pharma, academia, CROs • Clinical trial development will become more efficientby reducing the time it takes to bring new drugs to market, thus generating substantial value • Hospitals • Able to participate in more clinical research programmes, benefiting their patients • Health authorities • Access to new and better evidence to underpin health policy, strategy and resource planning • Health community/governments • Able to offer improved quality of healthcare with reduced healthcare costs • EU • More attractive for R&D investment Patients Faster access to safe and effective medicines, improving health outcomes across Europe

    10. Public Private Partnerships can achieve something that individual groups cannot realise alone Developing a platform and services to re-use EHR data • Political support • Engage multiple stakeholder communities • biopharmaceutical companies, patient organisations, academia, hospitals, small- and medium-sized enterprises (SMEs) and public authorities • Transfer of knowledge • Public deliverables • Consensus and synergy Supported by Moving towards deployment of a sustainable ecosystem Overcoming barriers that limit access to EHRs for research Offering a new paradigm for clinical research in Europe

    11. The EHR4CR Project 11

    12. A unique initiative • Mandated by IMI • One of the largest European public/private partnership projects in this area • 4-year project (2011-2015) • Budget of € >16m For further information see www.ehr4cr.eu or contact Geert Thienpont (EuroRec) geert.thienpoint@ramit.be

    13. Brings together key stakeholders • 35 participants including pharmaceutical industry, academia , hospitals, small and medium-sized enterprises, patient associations and public authorities 11 hospital sites Advisory boards and other experts

    14. To address key challenges to enable the re-use of EHR for clinical research • InteroperabilityEHRs generated by single institutions (the doctor has a set of information for each patient; if the patient goes to another doctor there is another set of information) • Separate and disparate systems • Incompatible EHR systems • Different models • Variable quality, uniformity and organisation of the data • Different coding and content standards • Structured (e.g. prescriptions) versus unstructured (e.g. clinical narrative) • Different languages across Europe • Data security, privacy & ethics • Complying with ethical, legal and privacy requirements that differ from country to country is critical to gain acceptance with the general public, patients and medical professionals • Confidence in data • All data has to be complete and accurate at the point of capture. A single error presents risk that can be magnified as data transmits downstream • Scalability and sustainability • Solutions need to be adaptable and reusable and governed within a sustainable ecosystem

    15. Project deliverables TECHNICAL PLATFORM BUSINESS MODEL A SET OF TOOLS AND SERVICES A set of tools and services A self-sustaining economic model A roadmap for pan-European adoption Validated through pilots • Different therapeutic areas (e.g. oncology, neuroscience, diabetes, CVS…) • Several countries (under different legal frameworks) Protocol Feasibility Patient Identification and Recruitment Clinical Trial Data Exchange

    16. Protocol Feasibility Protocol design based on estimates and not optimised • With no, or limited, access to actual patient data, trial design is based on discussions with expert clinicians • Increased amendments, slower than expected enrolment, costly changes to add new sites and countries, even failed trials • Will we find sufficient numbers of the right patients? A third of protocol amendments are avoidable1 , at a cost of $0.5mper amendment.2 • Do the inclusion/ exclusion criteria make sense? • How long will the trial take? Drug Information Journal, Vol 45, 2011 Industry Standard Research, 2010

    17. Patient Recruitment A major cause of trial delay • With no searchable patient database, identifying and recruiting suitable patients and trial sites are principal causes of trial delays • Delayed trials increase the burden for sites, waste costly resources and slow access to new drugs The percentage of studies that complete enrolment on time: 18%in Europe, 7%in the US1 Almost halfof all trial delays caused by patient recruitment problems2 Each day a drug is delayed from market, sponsors lose up to $8m3 1. State of the Clinical Trials Industry: A Sourcebook of Charts and Statistics, Center Watch, 2008. 2. Study Participant Recruitment and Retention in Clinical Trials: Emerging strategies in Europe, the US and Asia, Business Insights, June 2007. 3. Beasley, “Recruiting” 2008 4. Tufts -http://clinicalperformancepartners.com/wp-content/uploads/2012/07/Fixing-Feasibility-Final-Jan-2012.pdf

    18. Model: a free market ecosystem DATA PROVIDER DATA PROVIDER Data Provider • An organisation that contributes data for EHR4CR e.g. hospital EHR4CR INSTITUTE NETWORK PROVIDER NETWORK PROVIDER • Data aggregation and access services through standard EHR4CR interfaces INTERCONNECT Service Provider • An organisation that provides EHR4CR services to Service Users PROTOCOL DESIGN & FEASIBILITY UK DATA ONCOLOGY DATA Applications access and deliver EHR4CR services SERVICE PROVIDER SERVICE PROVIDER SERVICE PROVIDER SERVICE PROVIDER 1 2 3 Service User APPLICATION PROVIDERS APPLICATION PROVIDERS APPLICATION PROVIDERS APPLICATION PROVIDERS APPLICATION PROVIDERS APPLICATION PROVIDERS APPLICATION PROVIDERS APPLICATION PROVIDERS • An organisation that uses EHR4CR services such as a pharmaceutical company or an academic institution SERVICE USER SERVICE USER SERVICE USER

    19. The EHR4CR Platform and Services

    20. The EHR4CR platform – an open architecture • Open platform • Service Oriented Architecture • Standards based • Maximal service decoupling • Objectives • Avoid vendor lock-in • Stimulate alternative tool development • Open to different semantic interoperability approaches • Create added-value by enabling service re-use beyond EHR4CR Infrastructure Semantics (end-user) Tools Hospital Connectors

    21. EHR4CR Overview – data flow RESEARCH CENTRE e.g. pharmaceutical company EHR4CR PLATFORM HOSPITAL/DATA PROVIDER  QUERIES AND RESULTS ACROSS MULTIPLE SITES FEASIBILITY CLINICAL DATA WAREHOUSE EHR4CR SERVICES EHR EXTRACT TRANSFORM LOAD STUDY CRITERIA  QUERY WORKBENCH ELECTRONIC CASE REPORT FORM CANDIDATE LIST QUERY RECRUITMENT WORKBENCH RECRUITMENT PROGRESS RECRUITMENT PROGRESS RECRUITMENT PROGRESS RECRUITMENT PROGRESS RECRUITMENT PROGRESS RECRUITMENT PROGRESS RECRUITMENT PROGRESS RECRUITMENT PROGRESS RECRUITMENT PROGRESS RECRUITMENT PROGRESS #COUNT QUERY #COUNT RECRUITMENT PROGRESS QUERY RECRUITMENT PROGRESS  RECRUITMENT

    22. Security & Privacy • EHR4CR Security Framework • Advanced SOA security framework (cross-organisation Web Services) • Key points • All operations fully (end-user) authenticated through credential delegation • Seamless SSO between websites & services • Central Identity & Access Management (IAM) • Enforces platform-wide policies (e.g. contractual agreements) • Fully complementary to local access control (federates) • Unified platform audit trail SSO Access Control Audit

    23. Protocol Feasibility Service pilot • Tested viability and performance of EHR4CR platform to support protocol feasibility service • 11major hospitals in five countries • EHR4CR-compliant data warehouses were established at all pilot sites • Large set of eligibility criteria from EFPIA trials analysed to identify commonly used data elements (75 EHR data elements) • De-identified data from >five million patients was loaded for these elements into local EHR4CR-compliant data warehousesas far as available at the sites • 12 clinical studies evaluated, technical testing of four clinical studies • Germany (WWU, FAU) • France (AP-HP, U936) • UK (UoD, UoG, UoM, UCL, KCL) • Switzerland (HUG) • Poland (MuW)

    24. Protocol Feasibility Edit Eligibility Criteria Select sites of interest Launch queries Analyse results Accept Execute

    25. User acceptance and functionality testing • A subset of the previously selected 12 studies were used for two User Acceptance Test pilots • October 2012: Initial pilot with four studies, test scripts with 52 steps • January 2013: Extended pilot with 10 studies • User functionality testing • October 2013: Three independent testers, validation of patient counts

    26. End user view of the application: Protocol Feasibility Service query workbench

    27. End user view of the application: Results

    28. Protocol Feasibility Service pilot outcome • Conclusion of defined pilot success criteria: • Retrieving information from hospital sites: • Timely response but endpoints without data halt query execution • User functionality testing: patient counts validated for test dataset: • EHR chart review to validate precision of patient counts by EHR4CR platform (currently ongoing) • Query modification and re-running of queries: • Transnational platform across systems and hospitals:

    29. Validated solutions • Developed pilots to validate the solutions: • For different scenarios(e.g. protocol feasibility) • Across different therapeutic areas (oncology, inflammatory diseases, neuroscience, diabetes, cardiovascular diseases, respiratory diseases) • Across several countries (under different legal frameworks)

    30. GOVERNANCE AND THE EHR4CR INSTITUTE

    31. Build EHR4CR community and best practices The EHR4CR Institute Guardian of shared Intellectual Property Specifications and standards Accreditation and Certification Promotion of EHR4CR services Oversight, governance, auditing EHR4CR Institute • Critical to the sustainability of EHR4CR • Provides environment for EHR4CR ecosystem to develop • Not-for-profit, formally registered company providing services to registered members (e.g. data providers, data users, service providers) • Funded by license fee, subscriptions, certification, membership (cover cost of operations and providing services to registered members) • Incomes reinvested to improve services & fund public interest research

    32. Maintain a reference implementation Software Requirements Specifications Maintain specifications and standards Maintain conformance criteria, testing tools Develop resources Software components: platform and tools Publish policies and Standard Operating Rules Governance instruments EHR4CR project EHR4CR Institute

    33. Oversee and audit governance & security Certify service providers and EHR systems Educate and train research and ICT staff Accredit staff and organisations DATA PROVIDER DATA PROVIDER RESEARCH SPONSOR RESEARCH SPONSOR EHR4CR SERVICE PROVIDER APPLICATION PROVIDERS SERVICE USER NETWORK PROVIDER Govern the ecosystem SERVICE USER OTHER DATA AGGREGATORS The EHR4CR Institute will partner EuroRec, ECRIN and UKCHIP to: ICT SOLUTION PROVIDERS RESEARCH ORGANISATIONS APPLICATION PROVIDERS

    34. Privacy protection delivered on multiple levels • Personal data only processed by original data controller (treating physician) • EHR4CR only handles aggregate data with additional protections • Clinical Data Warehouse holds only pseudonymous data • Role-based access controls to limit access to aggregate data • Extensive audit trails with reporting • Integration of Operating Procedures with system functionality

    35. Concluding Remarks

    36. The EHR4CR project is an important initiative • Bringing together multiple stakeholders • Overcoming barriers that limit access to EHRs for research • Developing a platform and services for trustworthy re-use of EHR data Clinical researcher De-identified data for Clinical Research Patient health records

    37. Within an environment for trustworthy re-use • Segregationof EHR4CR data from EHR • Controllock/unlock access by hospital • Governanceindependent institute ensures data are accessed in a trustworthy way • De-identificationindividual patient anonymous • Consolidationonly aggregated patient numbers leave the hospital EHR4CR Institute Patient health records De-identified data for Clinical Research n= 16

    38. Thank You

    39. Video links • Platform demo • http://devworkbench-ehr4cr.custodix.com • EHR4CR Institute • http://youtu.be/fcRoy8jlu4A