HiGHmed Consortium in Germany established a semantic interoperable electronic health record architecture in a vendor- and technology-neutral format. 

This enabled them to set up systems and tools that add value to decision-making support in day-to-day clinical practice and support research questions. Furthermore, this is also the basis for their data-centric app ecosystem.

Project description

HiGHmed created Medical Data Integration Centers (MeDICs) based on a generic and scalable reference architecture for integrating data from care, research, and external sources, which facilitate the development of new solutions for medical data analytics benefitting clinicians, patients and researchers. HiGHmed is developing a joint cross-institutional reference architecture based on relevant existing standards such as IHE, openEHR and FHIR.

Better Platform, an openEHR based clinical data repository, provides the required capabilities for the management of structured clinical information, and supports integration between individual deployments using IHE XDS profiles. The HiGHmed reference architecture, based on the Better Platform, is scalable and open for adoption by additional partner hospitals and to solution developers to provide innovative applications, e.g. for data integration or analytics.

Client’s challenges

  • The volume of data generated
  • Low data integration for routine processes in a clinical practice
  • An application-centred approach which creates a vast amount of data silos
  • A lack of data availability for research purposes
  • The absence of a clinical data repository which could easily be extended to cover additional research initiatives

Key benefits

  • The availability of structured clinical data in a single CDR
  • An information model governance framework
  • A shared data dictionary
  • The separation of data and applications
  • The implementation of additional applications
  • Archetype Query Language (AQL)
  • Cost-effectiveness


  • A national infrastructure for the cross-institutional use of medical data for research and teaching, with the aim of being able to use the findings in everyday clinical practices for patients.
  • Interoperable data management solutions.
  • The integration of data from research, clinical operations, and external sources.
  • New solutions for the analysis of medical data for the benefit of patients, clinicians, researchers, and society at large.

COVID-19: HiGHmed Consortium’s Smart Infection Control System

One of the solutions built upon Better Platform is the Smart Infection Control System (SmICS) which was developed independently by HiGHmed during the COVID-19 pandemic. It is able to show contacts between patients, basic epidemiological statistics, and patient timelines. The main goal of the SmICS is to provide relevant, precise, and structured data for the German healthcare system in order to improve COVID-19 patient care. Better Platform will also contribute to the German National COVID-19 Research Network.



By implementing the open-data approach, the Consortium gained several benefits:

  • the availability of structured clinical data in a single CDR: for statistical analysis, machine learning, and the execution of decision-support algorithms,
  • an information model governance framework: this helps to establish a common understanding of the data between the participating hospitals by allowing collaborative work on archetypes (formal representations of clinical information models),
  • a shared data dictionary: allows standardised data models to be incorporated directly within the HiGHmed platform to create new clinical and research application systems, and databases,
  • the separation of data and applications: applications do not use their own database layer, which would then form a typical data silo, but leverage the platform to store any structured patient data instead,
  • the implementation of additional applications: comprehensive and full-blown clinical application systems can be developed on top of the HiGHmed platform and provide standard-compliant and interoperable data “by design” and without costly mappings,
  • archetype Query Language (AQL): a reliable and safe way to query data, deploy algorithms, and develop clinical decision-support systems in a highly-distributed environment,
  • cost-effectiveness: further development of the system can be done according to a given hospital’s resources and priorities.
Future aspects
  • Data-exchange in full operation between the core consortium Hannover-Göttingen-Heidelberg and the partners Münster, Berlin, Würzburg, Cologne, Schleswig-Holstein.
  • The establishment of a structured collection of research results, ongoing filling, and expansion.
  • The use of research results in clinical operations.
  • Evaluation of the results and possible continuity from 2022.
  • Collaborations with new, non-university partners.

Content for the HiGHmed case was partly taken from: openEHR in HiGHmed by Birger Haarbrandt, an article in openEHR – open data platforms in medical informatics, a brochure which was published by HiGHmed in June 2018. 

The Client – HiGHmed consortium

HiGHmed consortium in Germany is funded by the German Federal Ministry of Education and Research (BMBF) and is comprised of 8 university hospitals:

  • The Hannover Medical School (MHH)
  • Heidelberg University Hospital (UKL-HD)
  • The University Medical Center Göttingen (UMG)
  • The University Medical Center Schleswig-Holstein
  • The University Hospital Cologne
  • The University Hospital of Würzburg
  • The Charité – Universitätsmedizin Berlin
  • Münster University Hospital (UKM)

The consortium is complemented by more than 20 partners from academia and industry.

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