DIGITAL HEALTH

Digitalization and artificial intelligence (AI) are rapidly changing the healthcare system. In clinics, hospitals, and medical offices, electronic patient records, data management systems, AI-supported assessments, predictions, and resource planning, intelligent assistants, and many other technologies are on the rise. Doctors, healthcare professionals, and patients increasingly rely on cognitive systems, from the initial telemedicine consultation to AI-supported diagnosis, individualized therapy, and follow-up care at home.

Despite the current digital transformation in Europe and the increasing digitalization of the healthcare system, developing reliable AI is often challenging, especially in the field of medical imaging, because only small amounts of data are available. Training and testing AI models typically require large or very large amounts of data to achieve a high level of accuracy and reliability in AI decisions.

Algorithms can utilize enormous amounts of patient data. No human could process a comparable amount of data. This is why algorithms can recognize patterns that remain hidden to humans. For medicine, this means that an algorithm can recognize and calculate probabilities that a physician may not even estimate exist.

Measures to promote healthy aging include much more than just eliminating diseases; they also involve the active promotion of health throughout life and specific support to maintain functionality in old age. In the context of healthy aging, the term “health” refers to a person’s ability to do the things that are important to them.

Digital technologies offer enormous potential to shift from traditional medical routines to telemedicine and transform our ability to manage health and independence in aging populations. The role of wearable devices is particularly relevant in helping older adults monitor their health and maintain independence at home.

Wearables can assist older adults in remotely tracking chronic illnesses or ongoing treatments and monitoring safety issues, all without interrupting daily activities. For example, wearable platforms can continuously and non-invasively capture biometric and biomolecular data, which is not possible with traditional health assessments. They can generate instant alerts in emergencies, such as a stroke, seizure, or fall, allowing for timely medical interventions. These tools are also expected to reduce geographical inequalities by providing older adults living in rural areas with better access to healthcare services.

The application of digital technologies to assist clinical practice can address the increasing demands in service by providing convenient and continuous remote healthcare to patients and holds great promise for transforming healthcare.

Wearable sensor devices capable of real-time monitoring of various aspects of health or user behavior have attracted enormous attention over the last two decades due to their diverse applications. Wearable sensors have rapidly evolved since the advent of the Internet of Things and mobile devices, from the early trackers of user mobility and vital signs to today’s advanced multimodal detection devices capable of generating valuable data that were impossible to obtain just a few years ago.

Continuous and remote monitoring of vital signs can generate alerts for adverse events and deterioration of conditions in older adults, including the early onset of cardiovascular, neurological, and pulmonary diseases. For example, abnormal respiratory rates can predict respiratory failure, elevated body temperature can indicate an infection, and abnormal patterns in electrocardiogram signals can alert to cardiac arrest.

While digital technologies promise to revolutionize geriatric care, their practical implementation faces significant challenges, including a lack of digital literacy, threats to data privacy and security, and the limited performance of devices. Overcoming these challenges is crucial for the widespread use of digital technology in geriatric healthcare.