Clinical decision support in cardiology

The increasing digitalization in routine clinical practice has now become evident in many areas of diagnostics and treatment. Current examples include electronic patient records, telemedical applications and the use of robotic surgery. Another example is the development of clinical decision support (CDS) solutions, which started decades ago and is currently unfolding its whole potential through digitalization. Particularly in cardiovascular medicine there is good evidence for the clinical approach in many diseases and from each of these updated guideline recommendations can be derived. Digital decision support apps can help to improve safety and transparency as well as enabling better treatment quality by achieving higher guideline adherence. The current technical developments regarding digital decision aids in medicine are increasingly shifting from "knowledge-based " approaches (e.g. rules from guidelines) to "non-knowledge-based " systems, which use, for example, methods of artificial intelligence (AI) and learning from patterns out of different clinical data sets (machine learning). The requirements of future CDS systems are manifold and will need, above all, international data standards and a high degree of independence from existing clinical information systems.