WP 1
Coronary Heart Disease

Personalized Medicine, Prevention, and Digital Innovation

WP1.1 – Cohorts & IT Infrastructure for Personalized Medicine

• Achievements: 
  • Establishment of a digital platform for analyzing individual patient profiles.
  • Development of a clinical data integration center (DIZ) compliant with the MII standard.
  • Integration of clinical parameters, omics analyses, and imaging data.
  • Validation of biomarkers and risk scores for improved diagnosis and treatment.
  • Implementation of a secure, scalable IT architecture for the storage and processing of sensitive health data.
  • Incorporation of ethics, data protection, and interoperability to ensure legally compliant research and subsequent clinical application.
• Sustainability: 
  • The developed digital structures and methods are interoperable and can be transferred to the DigiMed Bayern Secure Cloud 2.0 as well as the Bavarian Health Cloud (BHC).
  • Long-term scaling at the European level (European Health Dataspace, EHDS) is planned. 

WP1.2 – HerzFit App: Digital Prevention for Cardiovascular Diseases

• Achievements: 
  • Development and launch of the HerzFit App as a central digital prevention platform (>150,000 downloads).
  • Integration of an anonymized data donation and study module for new scientific insights.
  • Risk calculator for various target groups, freely available on the website of the German Heart Foundation (DHS).
  • Close coordination with data protection authorities (BayLfD) to ensure anonymization and information security.
• Scientific added value: 
  • Establishment of a scientific database and development of a study module for the data protection-compliant collection of pseudonymized data.
  • First clinical studies with participant recruitment and implementation via the HerzFit study module since February 2025.
• Challenges: 
  • Long-term financing and further development of the app, particularly regarding technical status and competitiveness.

WP1.3 – Digital Prevention and Disease Prevention Using Health Insurance Data

• Achievements:
  • Creation of an anonymized dataset comprising over 2.3 million insured individuals from Bavaria, in close coordination with data protection authorities.
  • Development and use of a PostgreSQL database for standardized querying and analysis of healthcare data.
  • Implementation of use cases, e.g., 
    • Comparison of medications (prasugrel vs. ticagrelor) in heart attack patients – with high methodological quality and regulatory relevance.
    • Analysis of the impact of COVID-19 on atherosclerotic diseases.
    • Investigation of the effects of weather conditions on cardiovascular events.
    • Gender differences following myocardial infarction (STEMI): Women demonstrate better myocardial preservation and lower 5-year mortality following primary PCI.
  • The data enable a nearly complete mapping of medical history through diagnoses (ICD-10), procedures (OPS), medications (ATC/PZN), and demographic characteristics.
• Scientific added value:
  • Development of predictive models for risk, prevention, and therapy.
  • Health economic analyses: e.g., financial burden due to non-compliance and failure to manage risk factors.
  • Future prospects: Expansion of the datasets to include additional health insurance providers (e.g., Barmer, >10 million patients nationwide).
• Sustainability and outlook:
  • Several publications in progress.
  • Comparison of clinical studies with healthcare data from the Bavarian population.
  • Expansion of the datasets and integration into national and international research initiatives.