HL7 Europe Common Cancer Model, published by HL7 Europe. This guide is not an authorized publication; it is the continuous build for version 0.1.0 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/hl7-eu/cancer-common/ and changes regularly. See the Directory of published versions

Authors and Contributors

The HL7 Europe Cancer Common Data Model (ECCDM) Implementation Guide is the result of collaboration across HL7 Europe, European projects, oncology institutions, research organisations, vendors, implementers, and a community of volunteers.

The work is community-driven and brings together complementary perspectives on cancer data modelling, clinical oncology, research, interoperability, and technical implementation.

Major Contributors and Their Roles

• HL7 Europe provides the project-agnostic collaboration framework for developing the guide and supports the technical and administrative activities related to HL7 Europe Implementation Guides.
• The HL7 Europe volunteer community contributes domain knowledge, modelling experience, implementation feedback, review, and editorial work.
• European projects contribute requirements, use cases, and modelling experience developed in the context of specific cancer-related initiatives.
• Oncology centres and clinical experts provide the medical background needed to ensure that the model reflects clinically meaningful cancer concepts and patient journey patterns.
• Cancer research centres and researchers contribute expertise on the use of cancer data for research, analytics, secondary use, and cross-project reuse.
• Researchers and experts involved in national cancer registries contribute experience on cancer registration, population-level cancer data, longitudinal follow-up, and reuse of cancer information across institutions and countries.
• Vendors, solution developers, and implementers contribute practical experience from the development and deployment of oncology data solutions, interoperability services, and implementation artefacts.

This combination of perspectives is intended to support a model that is clinically meaningful, reusable across projects, and suitable for progressive implementation in different technical ecosystems.