​​Requirement Analysis for Data Modeling of Colorectal and Lung Cancers​

The goal of this deliverable is to define interoperable data models specific to Colorectal Cancer (CRC) and Lung Cancers. Instead of developing the data models from scratch, Dataspace4Health adopts and adapts the oncology data model defined by the German Medical Informatics Initiative (GMII) [1] for strategic and practical reasons. GMII is a 500 million euros project funded by the German Federal Ministry of Education and Research (BMBF) and all German university hospitals have joined this initiative. Numerous researchers in the German MII consortia endeavoured developing a comprehensive data model framework including the oncology data module. The data model framework has been validated and rolled out across all university hospitals in Germany demonstrating its robust design and utility with multiple case studies including Molecular Tumorboards (MTB) [2]. Therefore, adopting the GMII data model enables us to align the Dataspace4Health project with internationally recognized standards.  

It also adheres to global healthcare data standards such as the HL7 International healthcare standards organization [3], Fast Healthcare Interoperability Resources (FHIR) [4], Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) [5], and Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) [6], ensuring semantic consistency and data representation. The standardized healthcare data model is the key to enable interoperability (e.g., data exchange and service exchange). By adhering with the data standards, the GMII data model framework eases research collaborations across healthcare entities and borders (e.g., participation in multinational clinical trials). Moreover, the GMII data model aligns with European data protection regulations referred to as GDPR [7] and ethical guidelines for handling sensitive patient data [8]. This means that we ensure that our data modeling approach meets legal and ethical requirements for medical research from the outset.  

Given these advantages, the German GMII oncology data model serves as the foundation for defining the data requirements for CRC and lung cancers in Luxembourg and reduces costs and human resources and accelerates the timeline, instead of reinventing the wheel.