Prevention is a great opportunity for digital health. But what exactly does that mean? The field of prevention means to prevent health problems before they occur and thus stop them from spreading. This can be done through individual measures such as vaccinations, or at the societal level by promoting health-related working and living conditions. These include, for example, sports and nutrition programs or legal regulations, such as the Non-Smokers Protection Act.
Prevention is also one of the main focus areas of Prof. Lothar Wieler, who heads the “Digital Global Public Health” department at the HPI and is the spokesperson for the Digital Health Cluster.
In this interview, he explains how innovative technologies such as wearables, AI-supported chatbots and intelligent algorithms contribute to the early detection or prevention of diseases.
Hasso Plattner Institute: Why is artificial intelligence so promising for the field of prevention?
Prof. Lothar Wieler: One advantage is that information in the healthcare sector can be addressed more easily to specific target groups – for example, cultural background, socio-economic status or health status can be taken into account much better using images and language. The informative value of predictive analyses also increases: on the one hand, through the possibility of linking data from different data silos, and on the other hand, through the possibility of jointly evaluating data from different sources using algorithms. Wearables, for example, are another area that enables barrier-free determination of risk indicators, which are then reported back directly to the wearer. This can be of benefit to diabetics or stroke patients, for example. AI-generated chatbots can also answer specific questions with significantly higher quality, as well as provide low-threshold and always independent factual information, so that advice is possible independently of, for example, office hours in doctors' offices. Last but not least, telemedical applications without visits to the doctor can be significantly optimized.
HPI: That sounds really promising. What other examples are there that are relevant for the population as a whole?
Prof. Wieler: During heat waves, for example, data in wearables can be used to provide targeted information and advice to the chronically ill. In nursing care, movement profiles can be used to record certain activities that require documentation. This saves a considerable amount of time. Survey data from the recording of influenza-like symptoms, such as those collected by the RKI's GrippeWeb, can be linked with further data from the study participants (heart rate, blood oxygen levels, temperature, etc.) to better assess their state of health and also to better evaluate the severity of an epidemic. Or just think of the Corona-Warn-App or other apps that provided real-time information on COVID-19 infections. The data behind this information could also have been used to predict the waves of infection in Germany.
HPI: What progress can be achieved for public health with this?
Prof. Wieler: The progress can be summarized in three sentences. We can analyze more precisely and quickly. We can provide more precise and faster information about risks. And we give our fellow human beings the chance to take preventive action more precisely and earlier.
Thank you for the interview!
On March 26 and 27, the HPI invites you to the first Digital Health Innovation Forum. The hosts are Prof. Lothar Wieler and Prof. Ariel Dora Stern. The topics of the forum will also include AI in healthcare, global public health and prevention.
More information and tickets for the event are available at: https://hpi.de/en/hpi-digital-health-innovation-forum/
