Digitalisierung und Künstliche Intelligenz in Krankenhaushygiene und Infektiologie

Digitalisierung und künstliche Intelligenz spielen in der Medizin heute eine zunehmend große Rolle. Dieser Beitrag erläutert Hintergründe, macht eine Bestandsaufnahme und geht auf konkrete Chancen, Hindernisse und Hürden im Kontext der Infektionsmedizin und Hygiene ein. Dabei wird im Einzelnen u.a. auf Decision-Support-Systeme, digitale Scores und Frühwarnsysteme, Wissensdatenbanken und die Telemedizin eingegangen.

Kernaussagen

• Die KI-Entwicklung in der Medizin hat 3 Generationen durchlaufen – von regelbasierten Systemen (KI 1.0) über Mustererkennung (KI 2.0) bis zu Foundation-Modellen (KI 3.0) –, welche neue Inhalte generieren, aber auch Risiken wie Halluzinationen bergen.

• Dem enormen Potenzial der KI steht in Deutschland ein erheblicher Digitalisierungsrückstand mit fragmentierten IT-Systemen gegenüber, der die praktische Anwendung bremst.

• Strenge regulatorische Hürden (MDR, AI-Act) und limitierter Datenzugang durch Datenschutz und Einwilligungspflichten erschweren die Entwicklung und Implementierung von KI-Lösungen.

• Digitale Surveillance-Systeme (z.B. KISS, DEMIS) zur Überwachung von Infektionen und Antibiotikaverbrauch sind in Deutschland bereits erfolgreich etabliert und stellen eine wichtige Säule dar.

• Elektronische Frühwarnsysteme für Sepsis verbessern zwar die Sensitivität, führen aber häufig zu Falschalarmen (Overalerting) und potenzieller Übertherapie.

• Prädiktive KI-Modelle zeigen in Studien hohes Potenzial, sind aber aufgrund fehlender Validierung und des Bias-Risikos aktuell eine Ergänzung, kein Ersatz für klinische Expertise.

• Wearables und Telemedizin ermöglichen die Fernüberwachung, ihre breite klinische Integration wird jedoch durch fehlende Standards, teils ungenaue Daten und Datenschutzfragen limitiert.

Schlüsselwörter

Digitalisierung - Krankenhaushygiene - Künstliche Intelligenz - KI - Clinical Decision Support

Publication History

Article published online:
05 December 2025

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