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Trends in Electronic Health Records (EHRs) and the importance of Quality Labeling in the context of the use of EHRs in

Trends in Electronic Health Records (EHRs) and the importance of Quality Labeling in the context of the use of EHRs in

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Trends in Electronic Health Records (EHRs) and the importance of Quality Labeling in the context of the use of EHRs in

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  1. Trends in Electronic Health Records (EHRs) and the importance of Quality Labeling in the context of the use of EHRs in Care and Research Prof. Dr. Georges De Moor University of Gent, Belgium EuroRec President European Institute for Health Records (EuroRec)

  2. 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)

  3. 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 several European languages. The EuroRec Use Tools help users to handle this resource.

  4. EHRs: Trends… • Patient-centered (gatekeeper?) and longitudinal (life-long) records • Multi-disciplinary / multi-professional • Transmural, distributed and virtual • Structured and coded (cf. semanticinteroperability) • More metadata and coding in EHRsatgranularlevel! • Intelligent (cf. decisionsupport,clinicalpathways, VPH…) • Personalised(to populatemodelswithspecific data from an individual patient) • Predictive(use of predictivemodelsand personalgeneticdata) • More sensitive content (! privacy protection) • Integrative 4

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

  6. Significant changes 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 encourages people to use web services more often (in Q2 2011: already more than 1 million Apps within the group of bigger stores) • Will the rise of the Cloud create an explosion of consumer focused web services, e.g. cloud based Personal Health Records to be directly adopted by consumers?

  7. 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

  8. Clinical trials,functional genomics,public health databases Integrating information Centring services on citizens Creating and using knowledge Decision support, knowledge management and analysis components Date: 1.7.94 EHR repositories Whittington Hospital Healthcare Record John Smith DoB : 12.5.46 Personnel registers,security services Mobile devices Clinical applications Clinical devices, instruments Social computing: forums, wikis and blogs Integrated Electronic Health Record

  9. Clinical Trials & Research Safety and Adverse Event Registers Marketing Knowledge Mgmt Platforms Healthcare Management Decision Support Systems PHRs, EHRs and the Re-use of EHR data Patient TRUST Clinicians & others PHR EHR (EMR, EPR…) Privacy Enhancing Techniques Billing

  10. 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 implied consent

  11. EHRs certification: why? • Care Providers: assurance and trust in quality and functionality of EHRs and other eHealth solutions • Vendors: competitive advantage,improve market access, de-fragment market • Health Care Authorities: high quality systems offer amongst other better inter-operability which is important for the continuity in the care. • Patients: better quality of records thus more safety, better privacy… in their care

  12. The EuroRec Repository Current status  (1) • At present, the EuroRec Repository contains +/- 1700 Criteria/ Fine Grained Statements with + 15000 index links. The majority of the Fine Grained Statements are referencing one or more Source Statements (at the moment +/- 4000 links exist) and can be grouped into Good Practice Requirements. The current database contains +/- 200 of these Good Practice Requirements. • A large number of these criteria have been translated into 19 European languages (Bulgarian, Croatian, Czech, Danish, Dutch, Estonian, French, German, Greek, Hungarian, Italian, Polish, Portuguese, Romanian, Serbian, Slovakian, Slovenian, Spanish and Lithuanian) and other languages (e.g. Russian) as well. EuroRec Seals 1 and 2

  13. The EuroRec Repository

  14. The EuroRec Use Tools

  15. The EHR-Q-TN (Thematic Network) Progress:  Validation of existing quality criteria and tools Further translation of existing quality criteria Market analysis resulting in an updated inventory of EHR system vendors in Europe (843) and an exhaustive contact list of Health authorities and policy makers Expanding the harmonisation of certification  via the “Seal 2” criteria Roadmapfor the future

  16. EHR Quality Labelling & Certification Current status in US and Europe (1)  US: ARRA and HITECH act and Meaningful use of Certified EHRtechnology approach. Currently: 6 Authorised Testing and Certification bodies  Europe: national certification schemes in place in 10 member states and starting harmonisation of certification through the EuroRec  “Seals 1 and 2” now in 27 countries (cf. the EHR‐Q‐TN project). Remark: there is an 80‐90 % commonality between the functionalcertification criteria of Europe and of the US… but regulations differ!

  17. EHR Quality Labelling & Certification Current status in US and Europe (2) • The launch of the permanent program for Certification of Electronic Health Records was delayedin the US until mid-2012. • ONC recently released new rules for EHR certification: • “WASHINGTON – The Office of the National Coordinator for Health IT released Feb. 24 its proposed rule for the certification of electronic health record systems”

  18. EuroRec’s EU funded research projects (1) Past Projects

  19. EuroRec’s EU funded research projects (2) Other Projects

  20. EuroRec’s EU funded research projects (3) Starting Projects Prospects (3 in the pipeline): …EUCLID, RD-CODE, Antilope

  21. Overview of the EHR4CR projectElectronic Health Record systems for Clinical Research

  22. Electronic Health Records for Clinical Research • The IMI EHR4CR project runs over 4 years (2011-2014) with a budget of +16 million € (EuroRec acts as Managing Entity): • 10 Pharmaceutical Companies (members of EFPIA) • 22 Public Partners (Academia, Hospitals and SMEs) • 5 Subcontractors • 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. • Electronic Health Record (EHR) data offer large opportunities for the advancement of medical research, the improvement of healthcare, and the enhancement of patient safety.

  23. Partners

  24. 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) • Pilots for validating the solutions • The EHR4CR Business Model, for sustainability

  25. The EHR4CR Scenarios • Protocol feasibility • Patient recruitment • EHR-EDC integration • Pharmaco-vigilance • across different therapeutic areas (oncology, inflammatory diseases, neuroscience, diabetes, cardiovascular diseases etc.) • across several countries (under different legal frameworks)

  26. Business benefits • 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. hospitals). • The EHR4CR approach will thus also enable research and clinical trials to be delivered more cost effectively. • Both vendors of certified products and hospitals (source data) that will be accredited will have a competitiveadvantage. • The EHR4CR business model for re-using EHR data in research aims at offering benefits for all stakeholders and strengthen the collaboration amongst all the partners in research.

  27. 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 is continuing research on best practice for EHRs to be used for research

  28. Accelerating and leveraging knowledge discovery • Firstly, we need to accelerate the discovery of new knowledge from large populations of existing health records • EHRs can provide population prevalence data and fine grained co-morbidity data to optimise a research protocol, and help identify candidates to recruit • almost half of all Pharma Phase III trial delays are due to recruitment problems

  29. Example clinical questions • Find the age and gender of patients who have been diagnosed with Hodgkin's disease, where the initial diagnosis occurred between the ages 50 and 70 inclusive • What is the percentage of patients diagnosed with primary breast cancer in the age range 30 to 70 who were surgically treated and had post operative haematoma/seroma? • What percentage of patients with primary breast cancer who relapsed had the relapse within 5 years of surgery? • What is the average survival of patients with Chronic Myeloid Leukaemia (CML) and both with and without splenomegaly at diagnosis?

  30. The two way translational challenge • The bio-informatics research communities need to understand better the kinds of diverse inputs that different professionals and specialities 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 modelling 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

  31. ARGOS book: editor Georges J.E. De Moor • 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 Records in the US and Europe • Semantic interoperability • Modelling 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

  32. Drivers for “semantic” interoperability • The adoption, use and interoperability of Electronic Health Records has become a major focus of European and US eHealth policies, strategies and investments • Drivers for Integrated EHRs and Semantic Interoperability are: • Manage increasingly complex clinical (multi-professional) care • Let interact multiple locations of care delivery • Deliver evidence based health care • Need for intelligent decision support in medicine • Better exploit biomedical research • Improve safety and cost effectiveness of health care • Enrich population health management and prevention • Empower and involve citizens

  33. Semantic Interoperability (S.I.)  (ctd) S.I. requires widespread and dependable access to published andmaintained collections of coherent and quality assured semanticresources: “the detailed clinical models or clinical archetypes”. Clinical archetypes are a formal, rigorous and standardised (interoperable) specification for an agreed consensus or best practice representation of clinical data structures(within an electronic health record). They provide a standardised way of specifying EHR clinical data hierarchies and the kinds of data values that may be stored within each kind of entry. An archetype defines (or constrains) relationships between data values within an EHR data structure, expressed as algorithms, formulae or rules. (ISO/EN13606 Definition of Archetype)

  34. Semantic Interoperability (S.I.) (ctd.) New generationpersonalised medicineunderpinned by ‘-omics sciences’ and translational research needs to integrate data from multiple EHR systems with data from fundamental biomedical research, clinical and public health research and clinical trials. Clinical data that are shared, exchanged and linked to newknowledge need to be formally represented to become machine processable.  This is more than just adopting existing standards or profiles, it is “mapping clinical content to a commonly understood meaning”. ! Remark: one can exchange in a perfectly standardised message complete meaningless information, hence the importance of ‘content’- related quality criteria (clinically meaningful) and of “true” semantic interoperability.

  35. 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 • using practical exemplars in heart failure and coronary prevention • involving major global SDOs, industry and patients

  36. Semantic Interoperability  (S.I.)  (ctd) S.I. requires widespread and dependable access to archetypes : Hence the need of archetypes and templates mapped to EHR‐interoperability standards and bound to well specified multi‐lingual value sets, indexed and associated with each other via ontologies and referenced from modular care pathway components. (Multilingual:not only to support cross-border care but also to enable cross-border aggregation of research data!)

  37. Information models Business requirements Security Computational services Clinical knowledge EHR Communication Security ISO/EN 13606-4 ISO 22600 Privilege Management and Access Control ISO 14265 Classification of Purposes of Use of Personal Health Information EHR system reference model openEHR EHR interoperability Reference Model ISO/EN 13606-1 HL7 Clinical Document Architecture Clinical content model representation openEHR ISO/EN 13606-2 archetypes ISO 21090 Healthcare Datatypes ISO EN 12967-2 HISA Information Viewpoint Terminologies: SNOMED CT, etc. Clinical data structures: Archetypes etc. ISO 18308 EHR Architecture Requirements HL7 EHR Functional Model ISO EN 13940 Systems for Continuity of Care ISO EN 12967-1 HISA Enterprise Viewpoint EHR Communication Interface Specification ISO/EN 13606-5 ISO EN 12967-3 HISA Computational Viewpoint HL7 SOA Retrieve, Locate, and Update Service DSTU Interoperability standards relevant to the EHR

  38. Requirements the EHR must meet: ISO 18308 The EHR shall preserve any explicitly defined relationships between different parts of the record, such as links between treatments and subsequent complications and outcomes. The EHR shall preserve the original data values within an EHR entry including code systems and measurement units used at the time the data were originally committed to an EHR system. The EHR shall be able to include the values of reference ranges used to interpret particular data values. The EHR shall be able to represent or reference the calculations, and/or formula(e) by which data have been derived. The EHR architecture shall enable the retrieval of part or all of the information in the EHR that was present at any particular historic date and time. The EHR shall enable the maintenance of an audit trail of the creation of, amendment of, and access to health record entries.

  39. Contextual building blocks of the EHR Part or all of the electronic health record for one person, being communicated EHR Extract High-level organisation of the EHRe.g. per episode, per clinical speciality Folders Set of entries comprising a clinical care session or document e.g. test result, letter Compositions Sections Headings reflecting the flow of information gathering, or organising data for readability Entries Clinical “statements” about Observations, Evaluations, and Instructions Clusters Multipart entries, tables,time series,e.g. test batteries, blood pressure, blood count Elements Element entries: leaf nodes with valuese.g. reason for encounter, body weight Data values Date types for instance values e.g. coded terms, measurements with units

  40. ISO EN 13606-1 Reference Model

  41. Research Health Records Medical Knowledge Epidemiology Clinical outcomes Pathologicalprocesses Descriptions, findings, intentions Bio-sciences Prompts, reminders Clinical audit Evidence ontreatmenteffectiveness Diseases and treatments Professionalism and accountability Care plans EHR and knowledge integration These areas need to be represented consistently to deliver meaningful and safe interoperability

  42. Clinical data standards are needed! • To formally model theclinical domain concepts • e.g. “smoking history”, “discharge summary”, “fundoscopy” • To encapsulate evidence and professional consensus on how clinical data should be represented • published and shared within a clinical community, or globally • imported by vendors into EHR system data dictionaries • To support consistent data capture, adherence to guidelines • To enable use of longitudinal EHRs for individuals and populations • To define a systematic EHR target for queries: for decision support and for research Archetypes (openEHR and ISO 13606-2)

  43. Example archetype for adverse reaction

  44. privacy workflow record structure and context terminologysystems EHR reference model data types near-patient device interoperability archetypes templates architecture identifiers for people policy models structural roles functional roles purposes of use care settings pseudonymisation Consistent representation, access and interpretation Rich EHR interoperability guidelines care pathways continuity of care clinical terminology systems terminology sub-sets value sets and micro-vocabularies term selection constraints post-co-ordination terminology binding to archetypes semantic context model categorial structures

  45. 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 harmonise standardisation efforts 6. Support education 7. Assure quality 8. Design for sustainability 9. Strengthen leadership and governance

  46. Semantic Interoperability  (ctd) Longer term: In the longer term a governance organisationneeds to be nominated • to support, oversee and quality manage the future developmentof semantic interoperability resources  (clinical models) for health • and to develop an action plan for future research and educational investments. A role for

  47. Past, ongoing and future EU efforts • Deployment of certification at Pan-European level (EHR-Q-TN) • Strenghtening collaboration with others (HITCH, RD-CODE? and next CIP Thematic Network project ?) • Continued international cooperation with e.g. the US (ARGOS and EU-US Stewardship event ?) • Further development of the certification criteria for the re-use of EHR data for clinical research (EHR4CR, EURECA and EUCLID?) • Personalised Medicine and mobile device issues: integration of biomedical data, PHRs and otherissues (INBIOMEDvision and eHealth Innovation) • More focus on semantics, on clinicians’ involvement and on EHR-content-related certification criteria (SemanticHealthNet, SALUS, Eureca)

  48. The Future • EuroRec will continue to raise awareness at the pan-European level, in particular towards Healthcare Authorities or Policy Makers (cf. the BELGRADE DECLARATION and other initiatives…) and industry • EuroRec will strengthen its network via further EC funded projects (and by involving its ProRec centers through new mechanisms ) (cf. also EuroRec’s complete market inventory and roadmap) • Eurorec believes in new technologies and new paradigms (existing legacy systems are often a handicap) • Europe needs to organise in the longer run structural funding for EHR and eHealth related Certification activities (EuroRec should play for the medical software a role analogous to the one played by the European Medicines Agency (EMA) for new medicines (cf. safety etc.)

  49. THANK YOU! Prof. Dr. Georges J.E. De Moor‐‐