The openEHR Developers' workshop

Ian McNicoll ^a,b, Koray Atalag ^c, Erik Sundvall ^d,e, Sebastian Garde ^f, Thomas Beale ^a

^a openEHR Foundation

^b CHIME UCL

^c University of Auckland

^d Linköping University

^eRegion Östergötland

^f Ocean Informatics

Abstract: openEHR publishes and maintain a set of open specifications against which implementers can build highly maintainable and semantically interoperable electronic health record systems that can respond in an agile way to changing clinical reality. It is closely related to the family of ISO 13606 standards and to HL7 CIMI and has influenced HL7 FHIR architecture development. openEHR-based systems are designed to consume detailed clinical models (archetypes and templates), authored by global and regional clinical communities. openEHR archetypes are also often used as a source of clinical requirements gathering for non-archetype-based systems and interoperability standards (e.g.HL7 FHIR). Several different technical openEHR persistence implementation approaches have now been developed fostering development of an ‘open platform ecosystem’ on which new innovative applications can be built. This workshop will introduce and discuss openEHR from an implementation and systems-engineering perspective.

Keywords: Electronic Health Records, openEHR, archetype, interoperability, intraoperability, open-source software, clinical standards, HL7 FHIR, IHE

1. Introduction

openEHR has its roots in decades of academic investigation into the optimum requirements for a health record architecture capable of meeting the highly complex and ever evolving needs of 21^st-century healthcare.

It espouses several key principles:

Vendor-neutral data storage and querying
Technology-neutral storage and querying
Multilingual support
Collaborative clinical engagement in the design of clinical content models
Permissive, open-source licensing of both specifications and content definitions

Building the tools and technologies capable of implementing these principles has taken some time but there is now an ever-expanding market of openEHR tooling and storage solutions based on a variety of operating systems and persistence technologies. The next exciting phase is the emergence of an ‘open platform ecosystem’ where third-party innovators can take advantage of the tight integration afforded by an openEHR-based system, without the risk of technology or vendor lock-in.

After a brief introduction to the openEHR architecture, governance and ‘open platform’ philosophy, several short presentations will introduce a series of openEHR-related projects, current topics and research interests, with a technical focus. This will be followed by a plenary session to discuss issues raised by the presentations or other topics raised by workshop participants. Knowledge of the openEHR specification/technology and computer science is helpful to understand some details in the workshop, but not required for understanding the general concepts.

2. Workshop: openEHR in practice

2.1. Workshop Speakers

Ian McNicoll, MSc, MbChB, openEHR, CHIME UCL, UK
Erik Sundvall, MSc, PhD, Linköping University and Region Östergötland, Sweden
Thomas Beale, openEHR, London, UK
Sebastian Garde, Dr. sc. hum., Dipl.-Inform. Med., FACHI, Ocean Informatics, Germany
Koray Atalag, MD, PhD, FACHI, University of Auckland, New Zealand

2.2. openEHR architecture overview (Ian McNicoll)

openEHR¹ is an open specification, for a clinical information model architecture, capable of supporting an ‘open health data platform’ which is both vendor and technology-neutral. Systems built on openEHR² can respond directly to clinical innovation and diversity, without complex and expensive re-engineering. openEHR has been adopted by a variety of health system implementers and national organisations to underpin system development or national clinical standards programs, with proven scalability and vendor-neutrality. There is increasing interest in the deployment of openEHR-based clinical data repositories alongside traditional clinical systems as a more agile and responsive partner, sometimes described as a ‘Bi-modal’ approach or ‘Post-modern EHR’.

The core technology of openEHR specification features a multi-level modelling system, often referred to as ‘archetype-based systems’³. In this archetype-based technology, technical implementation is separated from the continuously updated detailed clinical modelling concerns in a way that makes it easier for implementers to maintain semantic intra- or interoperability.

2.3. HL7 FHIR, openEHR and IHE: perspectives on coexistence and collaboration (Erik Sundvall and Ian McNicoll)

The HL7 FHIR² standard has many benefits over some previous HL7 approaches and is gaining a lot of attention and implementation. There is also FHIR-hype, usually not from the core team behind FHIR, but from others hoping that FHIR will solve (almost) all healthcare information interoperability needs. We will highlight some differences and commonalities between the FHIR and openEHR approaches and exemplify how context of use and political/business views influence the short- and long-term benefits of different options and combinations. Some systems based on openEHR are successfully used in IHE⁵ profiled exchange environments and some are IHE-certified, we'll also discuss such options and combinations.

2.4. Process-enabled openEHR - future directions (Thomas Beale)

Building on the solid semantic architecture and existing features this work, such as its standard state machine for tracking order lifecycle, and its 500+ archetypes (detailed clinical models), the openEHR Specifications group is working on adding support for planned actions, order sets, care plans, managed medications and integrated reporting

The aim is to provide an open architecture for a process-enabled EHR that helps the clinical team take a person needing care from where they are now to a goal state, via an efficient, evidence-based pathway tailored for the patient.

2.5. Clinical Knowledge Manager (Sebastian Garde)

One of the crucial aspects when sharing clinical information across health information systems (of whatever kind) is to ensure that the data can be interpreted semantically without a margin for misinterpretation. For this, it is critical to achieve a common, comprehensive and formal understanding of the core clinical concepts we are dealing with. In the openEHR landscape, such clinical models are expressed as archetypes and it is the aim to agree on these clinical models internationally where possible. Broad input is required from the relevant health domains and professions to achieve a comprehensive understanding about a clinical concept. To support this, the openEHR Clinical Knowledge Manager (CKM) is geared toward the collaborative development, discussion, management, validation, review, publishing and maintenance of openEHR archetypes and other clinical knowledge resources⁶. For this, CKM is used internationally by the openEHR Foundation. In addition, CKMs are in place for regional and national programmes to allow the programmes to work independently – while reusing internationally agreed archetypes where possible and ideally contributing back their results to the international community.

2.6. Working with openEHR semantically (Koray Atalag)

We have used openEHR to model and persist experimental data that underpins computational physiology models (e.g. VPH, Human Physiome). The idea is then to link both experimental and real-world clinical information to these quantitative and predictive models to create a new breed of decision support tools that can deliver highly personalised and precision medicine. We have had some key important learnings while representing such models and especially when semantically annotating them - which in openEHR world corresponds to term and constraint bindings and data instance level term mappings. We will explain our methodology and discuss lessons learned which we hope will facilitate the use of openEHR in Semantic Web environments.

3. Target audience

This session is directed at students, clinicians, informaticians and system implementers who are interested in the technical aspects of openEHR methodologies and future directions.

4. Educational goals

Participants will gain a better understanding of the technical background to openEHR and how this has been carried through to relate to real-world projects.

5. References

[1] openEHR Foundation, openEHR.org [Accessed December 8, 2016]

[2] Beale T, Heard S, Kalra D, Lloyd D, The openEHR EHR Reference Model, At http://www. openehr.org.

[3] Beale T Archetypes: Constraint-based Domain Models for Future-proof Information Systems. In: Baclawski K, Kilov H. (eds.) Eleventh OOPSLA Workshop on Behavioral Semantics: Serving the Customer (Seattle, Washington, USA, November 4, 2002). Boston, 2002.

[4] HL7 Fast Healthcare Interoperability Resources, https://www.hl7.org/fhir [Accessed December 8, 2016]

[5] Rinner C, Kohler M, Hübner-Bloder G, Saboor S, Ammenwerth E, Duftschmid G. Archetype based search in an IHE XDS environment. Stud Health Technol Inform. 2012;180:631–5.

[6] Leslie H, Heard S, Garde S, McNicoll I, Engaging Clinicians in Clinical Content: Herding Cats or Piece of Cake? Studies in health technology and informatics 150 (2009), 125-129.