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Motivation
In Germany, there are about 5 million fall incidents every year. The risk of falls among older people is increased, especially if they are unsteady in their gait or if they take some medications. It is often difficult to assess the individual risk and thus to successfully implement preventive measures. Artificial intelligence (AI) could make an important contribution here. However, access to the data that an AI needs to learn is often difficult.
Objectives and procedure
The aim of the project is to give caregivers and researchers easier access to the data they need. The identification of fall risks is only one possible application. In addition, the data can also provide information about other nursing-relevant problems, such as states of confusion or the consequences of multimedication. For this purpose, a decentralised database is to be developed by two large care institutions, a deep-tech start-up as well as a technical university and a research institute for digitalisation. To protect the patients' data, they never leave the respective institution. Instead, the data will be used to develop models that can generate and replicate realistic patient data.
