Core Unit Digital Medicine and Interoperability

Our vision is an interconnected digital health infrastructure that enables new technologies to predict diseases more accurately, develop better technology, personalized treatments, promote active patient participation, and ensure high data security. In cooperation with hospitals, research institutions, health care industry, and politics we plan, develop, and test interoperability and documentation solutions using international IT standards and terminologies at a local, national, and global level.

Research data infrastructures for Germany are defined in the MI-Initiative and NFDI4Health projects and harmonized with other major projects (NFN, KBV/gematik, NAMSE) based on international standards. The Core Unit eHealth & Interoperability has thus established itself as the center of the most important research data management activities in Germany. These are aligned with the strategic goals of the European Commission, Germany and BIH@Charité. 

Members of CEI serve as chair of the standardization committees DIN, IHE, HL7 Germany and international committees at GA4GH, WHO, CEN, and ISO-Level. Therefore, we have a significant influence on the development of international standards. This becomes more important as this data influences the global market, research, and patient care. 

The membership of SNOMED CT International and the cooperation with the Regenstrief Institute (LOINC) in context with FHIR will result in extensive work and adaptations for Germany. Our working group has unique national expertise in the field of semantic interoperability. It represents the corresponding committees (Board for Classifications in Health Care with WG LOINC at the BfArM, Technical Committee Terminologies HL7, KBV/gematik Expert Council) and will lead these developments scientifically and make the results available to research in Germany and Europe. These terminologies will be implemented in projects, applications and persistent infrastructure of the Charité (PROMS, Clinical Trials, Laboratory Data, Data Integration Center). This ensures (international) comparability, precise data exchange, patient safety, and FAIR data. This data can also serve as basis for decision support systems and algorithms for machine learning and artificial intelligence. 

Data protection and data security enable and are prerequisites for data use in medical care and medical research. They guarantee confidentiality, integrity and availability of sensitive patient data. CEI's data competence team deals not only with organizational and technical aspects of data usage, but also with ethical, legal and social issues (ELSI), influencing each other.  The leading paradigm is to leave the data in its place of origin with the responsible institution generating the data. The information should be in the right place at the right time with the right people. Data should not be transferred to algorithms, but algorithms rather to the data. The focus of interest lies on methods of decentralized analysis and cryptographic procedures of Secure Multi Party Computation (SMPC). These methods avoid the transfer of sensitive clinical and genetic data between parties, as defined in Article nine of the GDPR. Especially in the area of rare diseases, both horizontal extensions (more patients) and vertical additions (including external history data) are targeted by connecting data sets. 

The Berlin Hospital Law (Krankenhausgesetz Berlin) will be transformed into a new law, that allows data processing aiming to improve patient outcomes and enable adequate (Health Data) Science.

Up to date, certain aspects in Digital Medicine remain challenging concerning digital illiteracy and unjust healthcare access. To share information with end users in a truthful manner, there is the requirement of informed consent and fairness when dealing with storage, access, sharing and ownership of data. Now it is the turn of stakeholders, especially providers and regulators in digital health, to shape digital health innovations with an ethical and fair mindset. We need to use this transformation to create a fair approach to digital health and foster health equity all over the world. It should be a fundamental right that new technologies established through Digital Medicine are available to everyone, including under-privileged groups and communities. Digital Medicine should promote equally innovation as well as democratization of healthcare. Ethical concerns, especially when using artificial intelligence and machine learning in healthcare, need to be considered carefully.

We support gender equality, diversity, and inclusivity in digital medicine. Therefore, we submitted a grant proposal for the project SHEHEALTH aiming to enhance visibility of women in digital medicine and science.