openEHR provides a layered ecosystem that separates clinical knowledge from software implementation so that health systems are interoperable, maintainable and clinically accurate. The ecosystem can be organised into six practical categories used across real-world implementations: Applications, Guidelines and CDS, Knowledge Management, Libraries, Modelling Tools, and Platforms
At the foundation are the clinical models (archetypes and templates) that describe what health information means. Above that sit platform components (EHR servers, storage and APIs) that define how data is stored and served.
A broad collection of tools – authoring, validation, terminology, analytics, and UI toolkits – help teams build, validate and integrate openEHR-based solutions.
Finally, commercial and open-source products (clinical apps, decision support, registries, patient portals) use those layers to deliver real-world functionality to clinicians, patients, and administrators. This separation speeds development, improves safety and enables multi-vendor ecosystems.
The stack
Modelling Tools
- Clinical modelling environments such as Archetype Editors and Template Designers used to create and refine archetypes and templates.
- Validation tools and CI utilities for automated syntax checks, conformance verification and publish-ready content.
- Model visualisers and mapping utilities that help analysts, clinicians and developers understand data structures.
Libraries
- SDKs in multiple languages (Java, .NET, Python, JS, etc.) for working with archetypes, templates, compositions and APIs.
- UI component libraries and helper utilities for form generation, rendering and binding.
- Integration libraries and adapters that connect openEHR systems to external services or legacy systems.
Platform
- EHR servers and persistence engines that store, version and manage clinical data.
- Core openEHR APIs, including REST APIs and AQL (Archetype Query Language) for querying structured clinical information.
- Terminology services, indexing, authentication, authorisation and audit services that underpin secure and reliable data operations.
Knowledge management
- Tools and repositories for managing the lifecycle of archetypes, templates and terminology bindings (e.g., CKM).
- Governance workflows for reviewing, approving, versioning and publishing clinical content.
- Terminology binding support (SNOMED CT, LOINC, local code sets) and quality assurance processes for semantic consistency.
Guidelines and CDS
- Tools for authoring, managing and executing computable clinical guidelines (GDL, BPMN, rule engines).
- Decision-support frameworks linking guidelines to openEHR data structures.
- Execution environments that deliver real-time recommendations, alerts and pathway support within clinical apps.
Applications
- Clinical applications including EMR modules, clinical workflows, observations, orders and results.
- Patient-facing apps such as portals, PHRs and digital front-door services.
- Decision support applications, order management systems, registries, research platforms and population-health dashboards.
- Commercial and open-source solutions built on top of the openEHR platform and models.