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Medicine|Feb 9, 2026

Standards and conditions for the success of digitalization for Public health authorities

Dtsch Med Wochenschr. 2026 Feb;151(4):180-184. doi: 10.1055/a-2725-3723. Epub 2026 Feb 9.

ABSTRACT

In 2025, Germany faces a dual transformation: the institutionalization of a federal Ministry for Digital Affairs and a controversial relaxation of data protection regulations, i.e. register for mentally ill people. These developments coincide with increasing political polarization, which not only shapes public discourse but also exerts measurable effects on health behavior, trust in institutions, and access to care. Despite operating one of the world’s most expensive health systems, structural inequalities in Germany persist, with life expectancy differing by up to eight years across socioeconomic groups. Public health authorities (Öffentlicher Gesundheitsdienst, ÖGD) could act as a corrective force, yet they remain underfunded, digitally underdeveloped, and vulnerable to political influence. This article argues that polarization has emerged as a social determinant of health, comparable in significance to income or education. We highlight the urgent need for institutional trustworthiness. We present the OSCADO-AI ethical code, an open-source, inter-operational, and privacy-conscious digital standard designed to enhance the resilience of public health institutions. By enabling transparent data use, secure communication, real-time surveillance, and collaborative platforms, OSCADO-AI strengthens both evidence-based decision-making and public trust. Case examples from Frankfurt illustrate how digital sovereignty and open infrastructures can protect democratic institutions against partisan interference while fostering citizen-centered health governance. Ultimately, the future of the German public health system depends on its capacity to combine medical independence, digital innovation, and civic accountability to reduce inequality and safeguard democracy.

PMID:41662865 | DOI:10.1055/a-2725-3723


Source: PubMed Research Database