The potential benefits of a well-connected digital healthcare system, clinical decision-support systems, and integration of personal device monitoring into the treatment pathway have long since been stated (e.g., [1]). However, implementation of such a system varies strongly between different countries [15].

In Germany, we face a strong separation between the healthcare sectors and their distinct stakeholders. The sectors have completely different reimbursement schemes that are even more diverse due to the federal structure of Germany. This has led to a competitive rather than a collaborative relationship between the different sectors, resulting in a highly fragmented system. The information loss at the transition between the different sectors and even between healthcare providers within the same sector impedes optimal care quality and increases costs [7]. Attempts by national legislation in the past two decades have reduced regulatory burden, provided incentives, and resulted in a fund to investigate new forms of care. But despite numerous healthcare reforms, cross-sectoral care has only slightly improved: digitalization with process optimization may shift workload and responsibilities between healthcare actors, which implies renegotiation of roles and duties. Different state data protection laws make it difficult to achieve solutions that are accepted nationwide [12]. Health information technology in Germany is largely provided by small and medium enterprises that claim difficulties with timely implementation of mandatory interoperability standards, and respective deadlines are typically postponed. However, the near monopolistic provision of the so-called telematic infrastructure, Germany’s national secure network for health information exchange, by, ultimately, two companies, has also been criticized for its high costs and negative impacts on functionality. On the other hand, digital health apps can be prescribed and are reimbursed by statutory health insurances in Germany, provided they are certified and enlisted by the Federal Institute for Drugs and Medical Devices. The recently published “Digitalization strategy for the health system and nursing” of the German Ministry of Health envisions 80% of all communication in medicine and nursing to be paperless in 2026, with establishment of digitally supported intersectoral and interprofessional care processes, and will enforce uptake of the electronic health record with an opt-out for citizens [11]. Moreover, the European Commission announced for the European Health Data Space in 2022 [9], with key aspects for primary use of health data, among other things, that “Patients will have their electronic health data available via access points established by Member States […] will be empowered to control and share their electronic health data with a healthcare provider of their choice” and “To support data being shared between healthcare providers, mandatory requirements for interoperability, security, safety and privacy will be introduced.”

A notable shift towards the empowerment of citizens and patients is observed in current governmental statements on digital health, acknowledging the sensitive role of health data for self-determination and privacy. Handling of patient data by medical doctors is strongly safeguarded through medical confidentiality within the patient–doctor relationship, with few exceptions defined by specific laws, such as those related to remuneration, cancer registries, or infection protection. Therefore, the only actors who have the right to decide on sharing health data beyond urgent medical need are the citizens themselves. But patient participation is today regarded as more than just signing informed consent. Active engagement may be implemented along the continuum of consultation, involvement, partnership, and shared leadership on the levels from direct care, organizational redesign, and evaluation of healthcare delivery, up to policy making [16].

True patient ownership of health data can only be achieved if a seamless, secure, and privacy-preserving option exists for sharing health data along the patient pathway. Advanced cryptographic methods available today can provide robust protection of data at rest and in transit, while providing authorized access [6].

Wearable health trackers such as smart watches have gained widespread popularity in the lifestyle sector, and integration of such devices into the regular health system is typically acknowledged as beneficial. They can provide health information over extended periods in daily environments, complementary to clinical assessments [26]. However, the new Medical Device Regulation (MDR) of the European Union (EU) states, “Software intended to monitor physiological processes is classified as class IIa” and the same holds for “Software intended to provide information which is used to take decisions with diagnosis or therapeutic purposes” [8]. Only software “which solely record, store or display information would generally not be considered devices”; all other software is regarded as class I. All medical devices (MDs) must be certified before used in healthcare, i.e., receive a certificate of conformance from an appointed authority. For example, an app that records questionnaires and integrates data from a smart watch is considered an MD. Smart clinical decision-support systems that employ AI are not only considered an MD, but also fall under the currently proposed European AI act, which classifies MDs generally as high-risk systems [13] that “will be assessed before being put on the market and also throughout their life-cycle.” To date, the act is not yet passed, but the bureaucratic burden is expected to be similar to MDR certification. Therefore, implementation of telemedical systems where the attending physician has access to wearable data and can employ AI-based analysis methods might be difficult to realize if the additional costs for development and market entry are not expected to be compensated [4].