Project »Neighborhood Diagnostics«

Project description

The lack of physicians and thus access to medical diagnostics in rural areas is a serious problem in our society. Fast and/or regular and timely medical care for acutely or chronically ill patients is therefore often connected with great expense for those affected. In the worst case, health problems are not detected early enough or the spread of infectious diseases is not contained in time. Adequate telemedical digital care for these patients often fails due to the unavailability of the diagnostics required for informed medical decision-making.

In the "Neighborhood Diagnostics" project, a mobile, fully automated health station will be developed to enable professional medical diagnostics in a cost-efficient manner in low-population regions. The health station will automate the entire process of sample collection, sample preparation and diagnostic tests on the sample material. Integrated into an intelligent digital ecosystem, this health station will enable digital and decentralized next generation care for acutely and chronically ill patients. The project combines the expertise of the three core institutes Fraunhofer IESE, Fraunhofer IZI, and Fraunhofer IZI-BB, as well as the Fraunhofer Institute for Factory Operation and Automation - IFF. The project focuses exemplarily on individual medical use cases, but is pursuing a platform concept that should make it possible to equip the health care station for a wide variety of diagnostics on a demand-oriented basis.

Contribution to the mission of the Fraunhofer-Center for Digital Diagnostics

Health care in the countryside is one of the center's main topics. By means of automation and a digital ecosystem, the Neighborhood Diagnostics project aims to provide modern cost-effective healthcare in the area by means of diagnostics. The project is a key element of the Professional Testing program.

Vision

The vision of the "Neighborhood Diagnostics" project is to enable largely digital and fully integrated healthcare in structurally weak regions, making it possible to detect diseases or episodes in the chronically ill at an early stage and to treat them adequately quickly, but also to avoid unnecessary medical consultations or hospital visits.  

Initiated by the medical staff, e.g. after telephone consultation or via wearables indicating a critical situation, the person to be treated visits a health station at any time. There, samples are automatically taken and analyzed for the relevant diagnostic parameters. The results are made available digitally to the person receiving care and the medical staff. An AI analyzes the results in real time, supports treatment decisions in accordance with the applicable guidelines, or initiates emergency measures in acutely critical situations, e.g. alerting the emergency medical and/or rescue service.