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University of Cologne
Institute for Biomedical Informatics

© University of Cologne and University Hospital Cologne Institute for Biomedical Informatics

Project Logo DICE-CD

DICE-CD

Contact
Employee photo Mr Oliver Diekmeier
Oliver Diekmeier (M.Sc.) Researcher and Doctoral Candidate
Project Status
Running
Kick-off Date
January 1, 2026
Quicklinks
About the Project

Description

DICE-CD (Data Innovations in Collaborative Ecosystems for Clinical Domains) is a nationally funded project (BMBF DigiNutzenDat) that develops a modular, scalable data ecosystem for clinical domains. The project connects hospitals, research institutions, and industry partners to integrate electronic health records, imaging, lab, and genomic data into a unified architecture. Using autosomal dominant polycystic kidney disease (ADPKD) as a reference case, DICE-CD builds a blueprint for data-driven, interoperable clinical workflows that improve decision-making, enable AI applications, and streamline care. The project also creates a Clinical Data Usage Maturity Model to help hospitals measure and advance their data capabilities. Our goal: turning fragmented data into actionable insights – empowering clinicians, researchers, and patients alike, and creating a foundation for the future of digital healthcare.

Project Team

Funding

This project is supported by

Gefördert durch: Bundesministerium für Forschung, Technologie und Raumfahrt
Co-funded by the European Union
Outcome

Achievements & Results

DICE-CD delivers concrete, validated outcomes that advance clinical research and healthcare delivery:

  • Reference Architecture: A scalable, modular data ecosystem for ADPKD that can be adapted to other clinical domains.
  • Clinical Data Usage Maturity Model: A dynamic framework for hospitals to assess and improve data integration and utilization.
  • Interoperable Interfaces & APIs: Secure, standardized data flows across EHR, lab, imaging, and research systems.
  • Validated Pilot Implementation: A fully functional prototype tested in two leading ADPKD centers, with real-world clinician feedback.
  • Innovation Catalog: Prioritized use cases and guidelines for embedding AI and analytics into clinical workflows.
  • Knowledge Transfer: Open-access publications, conference presentations, and open-source components to support adoption and scalability.

Together, these results create a blueprint for digital transformation in healthcare – improving decision-making, efficiency, and patient outcomes.