OpenEHR Standard

An OpenEHR Standard is an Clinical Data Standard that is an Open Standard for managing, storing, retrieving, and exchanging clinical data in electronic health records based on the ISO 13606 standard.

• AKA: OpenEHR Specification.
• Context:
  • Website: https://openehr.org
  • It is currently maintained by the openEHR International, and previously maintained by the openEHR Foundation up to 2003.
  • It is based on the results of the EU's GEHR-Project.
  • It defines an openEHR reference model and an openEHR clinical archetype model enabling domain experts to model clinical concepts and generate EHR templates and archetypes.
  • It uses a RESTful Interface to upload clinical data into a OpenEHR Repository.
  • It uses an Archetype Query Language (AQL) to access the data in the Open EHR repository.
  • It can used an OpenEHR Mapper to support the integration of clinical data into the cBioPortal.
  • It is specified to support multi-centre research.
• Example(s):
  • an Open EHR EHR Extract Specification,
  • an OpenEHR Template,
  • an OpenEHR Archetype,
  • …
• Counter-Examples(s):
  • Clinical Data Interchange Standards Consortium (CDISC) Standard,
  • Health Level Seven (HL7) Standard,
  • LOINC Standard,
  • SNOMED CT.
• See: Electronic Health Record (EHR), Archetype Model, Clinical Information Model, Clinical Service Model, De-Facto Standard, Clinical Terminology Standard, Standard-Developing Organization (SDO), Clinical Trial, Healthcare System, Clinical Knowledge Manager (CKM), Semantic Interoperability, cBioPortal.

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References

2022a

• (openEHR, 2022) ⇒ https://www.openehr.org Retrieved:2022-3-4.
  • QUOTE: openEHR is a technology for e-health consisting of open platform specifications, clinical models and software that together define a domain-driven information systems platform for healthcare and medical research. The principal architectural concepts include the patient-centric health record, clinical guidelines and decision support.

    Solutions based on the published artefacts are implemented by vendors, provider institutions and research groups for use in various operational environments, including point of care, research projects and public health.

    Benefits of the openEHR methodology and architecture include:

    • Domain professionals directly define the content and other semantics of implemented solutions rather than IT developers.
    • Application development may be largely be performed by low-code tools, enabling rapid development.
    • Interoperability is an automatic outcome of the platform architecture rather than an ad hoc case-by-case problem.
    • The platform approach enables a component-oriented healthcare IT economy based on published interfaces, which provides procurement the possibility of flexible and incremental purchasing from a wide variety of implementers.

2022b

• (Wikipedia, 2022) ⇒ https://en.wikipedia.org/wiki/openEHR Retrieved:2022-3-1.
  • openEHR is an open standard specification in health informatics that describes the management and storage, retrieval and exchange of health data in electronic health records (EHRs). In openEHR, all health data for a person is stored in a "one lifetime", vendor-independent, person-centred EHR. The openEHR specifications include an EHR Extract specification but are otherwise not primarily concerned with the exchange of data between EHR-systems as this is the focus of other standards such as EN 13606 and HL7. The openEHR specifications are maintained by the openEHR Foundation, a not for profit foundation supporting the open research, development, and implementation of openEHR EHRs. The specifications are based on a combination of 15 years of European and Australian research and development into EHRs and new paradigms, including what has become known as the archetype methodology for specification of content. The openEHR specifications include information and service models for the EHR, demographics, clinical workflow and archetypes. They are designed to be the basis of a medico-legally sound, distributed, versioned EHR infrastructure(...)

    The architecture of the openEHR specifications as a whole consists of the following key elements:

    • information models (aka 'Reference Model');
    • the archetype formalism;
    • the portable archetype query language;
    • service models / APIs.

The use of the first two enable the development of 'archetypes' and 'templates', which are formal models of clinical and related content, and constitute a layer of de facto standards of their own, far more numerous than the base specifications on which they are built. The query language enables queries to be built based on the archetypes, rather than physical database schemata, thus decoupling queries from physical persistence details. The service models define access to key back-end services, including the EHR Service and Demographics Service, while a growing set of lightweight REST-based APIs based on archetype paths are used for application access.

The openEHR Architecture Overview provides a summary of the architecture and the detailed specifications.

2021

• (Reimer et al., 2021) ⇒ Niklas Reimer, Hannes Ulrich, Hauke Busch, Ann-Kristin Kock-Schoppenhauer, and Josef Ingenerf (2019). "openEHR Mapper – A Tool to Fuse Clinical and Genomic Data Using the openEHR Standard". In: German Medical Data Sciences: Bringing Data to Life: Proceedings of the Joint Annual Meeting of the German Association of Medical Informatics, Biometry and Epidemiology (gmds EV) and the Central European Network-International Biometric Society (CEN-IBS) 2020 in Berlin, Germany (Vol. 278, p. 86). IOS Press. DOI:10.3233/shti210055.
  • QUOTE: openEHR is an open standard for Electronic Health Records (EHRs) based on the ISO 13606 standard. It defines a reference model and the Archetype Definition Language enabling domain experts to model basic concepts, i.e., clinical parameters like blood pressure in archetypes. Archetypes can be combined in blocks to build a template that represents a more complex concept like a report. This architecture allows using the same archetype for multiple purposes as well as sharing archetypes and templates on national or international platforms like the Clinical Knowledge Managers .

    For storing clinical information in an openEHR repository, the data is assembled as Compositions and uploaded via a RESTful interface. Data inside the repository can be accessed using the Archetype Query Language (AQL), a special language for openEHR with a syntax similar to query languages like SQL. To ensure data quality and interoperability, openEHR offers terminology binding for local terminologies that are provided by the archetypes themselves as well as bindings to external terminologies like LOINC or SNOMED CT.

Figure 1: The Architecture of openEHR Mapper – Mapping clinical and preprocessed genetic data to the openEHR information model at the input side, querying data using AQL for generating compositions, and managing EHRs in the core component and exporting a cancer study for cBioPortal at the output side.

2020a

• (Leslie, 2020) ⇒ Heather Leslie (2020). "openEHR Archetype Use and Reuse Within Multilingual Clinical Data Sets: Case Study". In: Journal of medical Internet research, 22(11), e23361. DOI:10.2196/23361.
  • QUOTE: Since 2008, the openEHR Clinical Models program has developed a comprehensive and collaborative methodology to develop clinical information models known as openEHR archetypes . It has gradually developed an extensive library of high-quality, multilingual, and use-case agnostic archetypes that can then be aggregated, constrained, and reused in implementable data sets known as openEHR templates.

    An openEHR archetype is a computable specification for a single clinical concept, based on the ISO 13606-2 Archetype interchange specification . The archetypes represent clinical knowledge in a consistent, formal, computable format, independent of any software application or technical implementation. Combined with terminology, they provide a standardized and consistent way to capture, store, display, exchange, aggregate, and analyze health data(...)

    Templates represent a specific data set, comprising one or more archetypes that are constrained to accurately match the data set requirements for a particular clinical use case, health domain, profession, or geographical location. The number of archetypes used in a template reflects the required scope of content and level of detail. Some simple templates representing a laboratory test report may comprise only a single archetype(...)

    Principles of template development methodology strongly encourage reuse of existing published openEHR archetypes where available, customize existing archetypes to fit the clinical use case, and develop new archetypes only in situations where no previous archetype exists.

    The two-level modeling approach described in the openEHR Archetype formalism —defining and standardizing archetypes first, followed by combining and constraining them to create clinical templates—is unique to the openEHR approach. The rigorously governed, published archetypes held in the CKM provide a robust clinical knowledge foundation. Simultaneously, the templates enable modelers to represent diverse and complex real-world clinical information in standardized data sets.

2020b

• (Li et al., 2020) ⇒ Mengyang Li, Heather Leslie, Bin Qi, Shan Nan, Hongshuo Feng, Hailing Cai, Xudong Lu, and Huilong Duan(2020). "Development of an openEHR Template for COVID-19 Based on Clinical Guidelines". In: Journal of medical Internet research, 22(6), e20239. DOI:/10.2196/20239.
  • QUOTE: An open, semantic-sharing, and collaborative-modeling framework is needed to meet the dynamic change of data requirements. openEHR specifications can be used to create standards and build information and interoperability solutions for health care as a multilevel modeling framework . In the approach suggested by openEHR, the reference model (RM) focuses on the logic structures and attributes required to express data, so it is stable and provides basic components for building concrete medical information models. The archetype model is comprised of archetypes and templates. Based on the RM, archetypes can be developed to define all the attributes about specific clinical concepts. Different archetypes can be organized into context-specific data sets, templates that are mostly developed and used locally. Only the RM is implemented in apps, while clinical information (archetypes and templates) is independent of specific implementations. The approach allows data models to be flexible and extensible within the constraints of the RM, which can keep up with the development of the clinical knowledge and meet the requirements of the complicated clinical environment .

2018a

• (Min et al., 2018a) ⇒ Lingtong Min, Qi Tian, Xudong Lu, and Huilong Duan (2018) ⇒ "Modeling EHR with the openEHR approach: an exploratory study in China". In: BMC medical informatics and decision making, 18(1), 1-15. DOI:/10.1186/s12911-018-0650-6.
  • QUOTE: The openEHR approach can improve the interoperability of electronic health record (EHR) through two-level modeling. Developing archetypes for the complete EHR dataset is essential for implementing a large-scale interoperable EHR system with the openEHR approach. Although the openEHR approach has been applied in different domains, the feasibility of archetyping a complete EHR dataset in a hospital has not been reported in academic literature, especially in a country where using openEHR is still in its infancy stage, like China. This paper presents a case study of modeling an EHR in China aiming to investigate the feasibility and challenges of archetyping a complete EHR dataset with the openEHR approach.

2018b

• (Min et al., 2018b) ⇒ Lingtong Min, Qi Tian, Xudong Lu, Jiye An, Huilong Duan (2018). "An openEHR based approach to improve the semantic interoperability of clinical data registry". In: BMC medical informatics and decision making, 18(1), 49-56.
  • QUOTE: Semantic interoperability is a challenge when integrating the data from more than one clinical data registry. The openEHR approach can represent the information and knowledge semantics by multi-level modeling, and it advocates the use of collaborative modeling to facilitate reusing existing archetypes with consistent semantics so as to be a potential solution to improve the semantic interoperability.

2005

• (Garde et al., 2005, 2005) ⇒ Sebastian Garde, Petra Knaup, Thilo Schuler, and Evelyn Hovenga (2005). "Can openEHR Archetypes Empower Multi-Centre Clinical Research?". In: Studies in health technology and informatics, 116, 971-976.
  • QUOTE: The aim of openEHR is to enable the development of open specifications and software for EHR systems. openEHR is based on the results of the GEHR-Project of the European Union. GEHR is an acronym for Good European Health Record respectively later Good Electronic Health Record. Following GEHR several projects extended and refined its results (e.g. the Synapses and SynEx projects). All these projects influenced the openEHR architecture. openEHR has pioneered a two level modelling approach for EHRs. An overview of this approach is given in Figure 1. The first level is the reference information model which is pared down to the minimum to support the medico-legal requirements and record management functions. This ensures that clinicians can always send information to another provider and receive information which they can read – thus ensuring data interoperability. The second level involves the openEHR archetype methodology – a way of sharing evolving clinical information so that it can be processed by the receiving provider – thus ensuring semantic interoperability. A blood pressure archetype for example represents a description of all the information a clinician might want or has to report about a blood pressure measurement. Basically, one archetype therefore represents one clinical concept.

Figure 1: Overview of the openEHR two level modelling approach for EHRs.

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