About the project
Blood donations are needed as blood products for operations and to treat diseases. In view of the declining willingness to donate and the demographic trend in Germany, an increasing shortage of donated blood is to be expected in the future. There is therefore an acute and medium-term threat of gaps in the supply. Currently, 15,000 units of blood are needed for clinical purposes in Germany every day. This scarce resource is constantly used in everyday medical practice and can be vital for the survival of patients in acute situations.
The aim of AutoPiLot is to improve the patient-related use and stockpiling of cellular blood products by systematically using the large amounts of digital health data available in hospitals to make optimized decisions. We are pursuing three complementary approaches to increase patient safety, quality of care and cost-effectiveness in the supply of blood products to patients:
Testing and decision support for guideline-compliant blood product requests with knowledge-based expert systems and intelligent human-machine interaction to increase patient safety
AI-supported patient-specific blood product allocation through pattern recognition and analysis as well as prediction of patient-specific transfusion requirements to increase patient safety and optimize inventory management
Prediction of hospital-wide blood product requirements using artificial intelligence to improve logistics management and reduce the expiry of blood products as well as for targeted donor mobilization using a smartphone app
Fachhochschule Dortmund's focus in the project is on developing a digital expert system for ordering blood products quickly and, above all, in line with guidelines. This allows requests to be managed more efficiently. A blood donation app is also being developed that will be linked to the "AutoPiLoT" system in addition to donor information and digital appointment scheduling.
Sponsor
Funding program / Research program
Digital innovations for improving patient-centered care in the healthcare sector; Module 2 Smart data use