Clinical Program


The openEHR Clinical Program has historically had a scope focussed on development of healthcare domain knowledge artefacts, including archetypes (data points and data groups), templates (data sets) and terminology subsets. These are freely available via the web-based Clinical Knowledge Manager (CKM). The work has proceeded under the governance of a Clinical Models Editorial Group.

By 2022, the growth in the use of openEHR clinical models and systems has led to the need to reformulate the Clinical Program. It will in future address an enlarged scope, including methodology, modelling, dissemination, and monitoring use in the field, and will have a newly constituted Clinical Program Board (CPB), created from public nominations. This Board will undertake the management of the Program overall, according to a formal terms of reference.

The clinical modelling activity, tools and repository of models found at the Clinical Knowledge Manager will come under the CPB when it is established.

Clinical Knowledge Governance

The openEHR Clinical Knowledge Manager (CKM) is an online application that supports knowledge governance within and across the health enterprise. In practice, it is a system for collaborative development, management and publishing of a wide range of clinical knowledge resources including archetypes, templates and terminology subsets.


Models of clinical information exist in every computer system that is used in health care. While doctors, nurses and other health professionals share many clinical concepts and can communicate very effectively about these concepts, computers have not had a standard means of representing clinical information. openEHR offers this capability and in doing so provides a platform for health care computing.


Archetypes are the fundamental shareable specifications of clinical information we need to provide quality health care, and the Archetype Definition formalism has been formally accepted as an ISO standard in 2008, updated again to AOM2 in 2019. An archetype is a computable specification of the data points and groups of a specific linical topic, such as 'ECG result', 'fetal heartrate' or 'problem/diagnosis'. Archetypes are defined as constraint structured based on the openEHR Reference Model, which itself guarantees that the contextual meta-data in health records (i.e. who, when and where) are taken care of and do not need to be redefined in each archetype.


Templates are a means of building clinical data sets specific to a use case. These are composed of elements of one or more archetypes and may add further constraints required for the use of those archetypes in a particular setting. Thus, data groups from archetypes for blood pressure, weight and blood sugar may be used when recording an annual review of a diabetic person or in an antenatal visit by a pregnant woman. Thus, templates will be created specific to 'diabetic review' and 'antenatal visit'.


Terminology is as old as computers in health care. Initially used to minimise disk space, the use of terminologies has grown to classify health care offered and more recently, through use of SNOMED-CT (SNOMED International) to support automated clinical process. Archetypes, and openEHR for that matter, are designed to work with terminology.

Archetypes and Terminology

Every term in an archetype can be 'bound' to a terminology to better understand the authors intent. Further, archetypes allow expression of subsets to determine which terms are appropriate values at a given data point. This is called a 'constraint definition' and is really a placeholder for a valueset that is offered to the user within the application.

Templates and Terminology

Terminologies used in Healthcare include ICD-10 (and its predecessor ICD-9), SNOMED-CT, LOINC and many others.

Most terminologies use codes as identifiers or references to each individual term or concept. Codes and identifiers are generally to aid processing by computer rather than humans. They come at a price.

Codes, EHRs and Semantic Interoperability

One often hears that coded data are essential for semantic interoperability and decision support. Coding is the use of symbolic, or alphanumeric identifiers to tag data items as referring to concepts or terms from an agreed vocabulary or ontology. Coding, may, in many circumstances have some value. But it also comes at a price. This article looks at the balance sheet to tease out the issues facing those making recommendations for electronic health records and semantic interoperability.