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General Trends in EHR systems,


General Trends in EHR systems, EuroRec Projects and Prospects, Quality Labelling and Certification Prof. Dr. Georges De Moor EuroRec President – PowerPoint PPT presentation

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Title: General Trends in EHR systems,

General Trends in EHR systems, EuroRec
Projects and Prospects, Quality Labelling and
Certification Prof. Dr. Georges De
Moor EuroRec President European Institute for
Health Records (EuroRec)
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)

  • 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
  • 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
  • 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

EHRs Trends
  • Patient-centered (gatekeeper?) and longitudinal
    (life-long) records
  • Multi-disciplinary / multi-professional
  • Transmural, distributed and virtual
  • Structured and coded (cf. semantic
  • More metadata and coding in EHRs at granular
  • Intelligent (cf. decision support),clinical
  • Predictive (e.g. genetic data)
  • More sensitive content (!privacy protection)
  • Personalised
  • Integrative

Significant changes to be anticipated
  • 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 bn mobile 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?

Cloud Computing
Cloud computing is no longer a buzz term but a
reality With the opportunity for ondemand
Software-as-a-service, migrating IT services to
the clouds is an opportunity that is hard to
Towards Integrated Health
Environmental Data
Genomic data
Phenomic data
Integrated Health Records
Integrated Electronic Health Record
PHRs, EHRs and the Re-use of EHR data
Privacy Enhancing Techniques
Health information flows needing interoperability
implied consent
EHRs certification why?
  • Care Providers assurance and trust in quality
    and functionality of EHRs and other eHealth
  • 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
  • Patients better quality of records thus more
    safety, better privacy in their care

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
The EuroRec Repository
The EuroRec Use Tools
The EHR-Q-TN (Thematic Network)
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 a
contact list of Health authorities and policy
Expanding the harmonisation of certification  via
the Seal 2 criteria
Roadmap defined for the future
EHR Quality Labelling  Certification
Current status in US and Europe (1) 
US ARRA and HITECH act and Meaningful use of
Certified EHR technology approach. Currently 6
Authorised Testing and
Certification bodies 
Europe national certification schemes in place in
10 member states and starting harmonisation of ce
rtification 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 functional certification criteria of E
urope and of the US but regulations differ!
EHR Quality Labelling  Certification
Current status in US and Europe (2)
  • The launch of the permanent program for
    Certification of Electronic Health Records has
    been delayed in the US until mid-2012.
  • ONC 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

(No Transcript)
EuroRecs EU funded research projects (1)
Past Projects
Project acronym FP Timeline Topic
MediRec FP3 1994-1995 Declaration (Recom. 9)
ProRec FP4 1996-1998 Creation of first ProRec centres
Widenet FP5 2000-2003 Creation of EuroRec
Q-Rec FP6 2005-2008 Creation of Repository Tools
RIDE FP6 2006-2007 Roadmap for Interoperability
EHR-Implement FP6 2007-2010 National Policies for EHR Implementation in the European area social and organisational issues
EuroRecs EU funded research projects (2)
Other Projects
Project acronym FP Timeline Topic
EHR-QTN FP7 2009-2012 Thematic Network on Quality Labelling and Certification of EHR Systems
ARGOS FP7 2010-2011 Transatlantic Observatory for Meeting Global Health Policy Challenges through ICT-Enabled Solutions
HITCH FP7 2010-2011 Healthcare Interoperability Testing and Conformance Harmonisation
EHR4CR IMI call 2 2011-2015 Electronic Health Records for Clinical Research
INBIOMEDvision FP7 2011-2013 Promoting and Monitoring Biomedical Informatics in Europe
eHealth Innovation FP7 2011-2013 eHealth Innovation Scaling up eHealth facilitated personalized health services Developing a European roadmap for sustained eHealth Innovation
EuroRecs EU funded research projects (3)
Starting Projects
Project acronym FP Topic
EURECA FP7 Enabling information re-use by linking clinical research and care
SALUS FP7 Scalable, standard based interoperability framework for sustainable proactive post market safety studies
SemanticHealthNet FP7 Network of Excellence on semantic interoperability and European health infostructure
Prospects (3 in the pipeline) EUCLID,
RD-CODE, a next CIP TN ?(after EHR Q TN)
Overview of the EHR4CR project Electronic Health
Record systems for Clinical Research
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.

Project Objectives
  • To promote the wide scale re-use of EHRs to
    accelerate regulated clinical trials, across
  • EHR4CR will produce
  • A requirements specification
  • for EHR systems to support clinical research
  • for integrating information across hospitals and
  • The EHR4CR Technical Platform (tools and
  • Pilots for validating the solutions
  • The EHR4CR Business Model, for sustainability

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

Business benefits
  • Accreditation of Clinical Research Units and
    Certification of EHR systems 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
    competitive advantage.
  • 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.

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
  • 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 now been 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

ARGOS book editor Georges J.E. De Moor
  • Foreword by Herman Van Rompuy- E. Council
  • Memorandum of Understanding signed by
  • Neelie Kroes - 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 Informatics Workforce challenges

Drivers for semantic interoperability
  • The adoption, use and interoperability of Electron
    ic Health Records has become a major focus of
    European and US eHealth policies, strategies and i
  • Drivers for Integrated EHRs and Semantic
    Interoperability are
  • Manage increasingly complex clinical (multi profes
    sional) 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 ca
  • Enrich population health management and prevention
  • Empower and involve citizens

Semantic Interoperability  (ctd)
S.I. requires widespread and dependable access to 
published and maintained collections of coherent a
nd quality assured semantic resources the detail
ed 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)

Semantic Interoperability  (ctd)
S.I. requires widespread and dependable access to
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 car
e but also to enable cross-border
aggregation of research data!)
Semantic Interoperability SI Intro
New generation personalised medicine
underpinned 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 new knowledge need to be formally re
presented 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.
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
The EHR shall enable the maintenance of an audit
trail of the creation of, amendment of, and
access to health record entries.
Interoperability standards relevant to the EHR
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 EHR e.g. per
episode, per clinical speciality
Set of entries comprising a clinical care
session or document e.g. test result, letter
Headings reflecting the flow of information
gathering, or organising data for readability
Clinical statements about Observations, Evaluati
ons, and Instructions
Multipart entries, tables,time series, e.g. test
batteries, blood pressure, blood count
Element entries leaf nodes with values e.g.
reason for encounter, body weight
Data values
Date types for instance values e.g. coded terms,
measurements with units
ISO EN 13606-1 Reference Model
EHR and knowledge integration
These areas need to be represented
consistently to deliver meaningful and safe
Clinical data standards are needed!
  • To formally model clinical domain concepts
  • e.g. smoking history, discharge summary,
  • To encapsulate evidence and professional
    consensus on how clinical data should be
  • published and shared within a clinical community,
    or globally
  • imported by vendors into EHR system data
  • To support consistent data capture, adherence to
  • 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)
Example archetype for adverse reaction
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
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
  • referenced from modular (re-usable) care pathway
  • 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

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
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 terminolo
gy binding to archetypes semantic context
model categorial structures
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

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?

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

Semantic Interoperability  (ctd)
Longer term
In the longer term a governance organisation needs
 to be nominated
  • to support, oversee and quality manage the future
    development of semantic interoperability resources
      (clinical models) for health
  • and to develop an action plan for future research 
    and educational investments.

A role for
Past, ongoing and future EU efforts
  • Deployment of certification at Pan-European level
  • 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
  • Personalised Medicine and mobile device issues
    integration of biomedical data, PHRs and other
    issues (INBIOMEDvision and eHealth Innovation)
  • More focus on semantics, on clinicians
    involvement and on EHR-content-related
    certification criteria (SemanticHealthNet, SALUS,

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
  • EuroRec will strengthen its network via further
    EC funded projects (and by involving its ProRec
    centers through new mechanisms ) (cf. also
    EuroRecs complete market inventory and roadmap)
  • Eurorec believes in new technologies and new
    paradigms (existing legacy systems are often a
  • 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.)

a future new ProRec centre?
Prof. Dr. Georges J.E. De Moor - - http//