Fragmented Hospital IT Hinders AI Adoption in Germany

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The article identifies the primary obstacle to AI implementation in German hospitals as 'IT system fragmentation' and 'lack of interoperability.' The core issue is not the capability of individual algorithms, but whether hospital systems can provide structured, current, and cross-system information—such as lab results, vital signs, and medication data. While digitalization levels show an upward trend (average score increased from 33 to 42 out of 100), most hospitals remain at low digital maturity levels. A significant gap exists between large 'maximal providers' and general 'basic providers.' Solutions mentioned include the implementation of ISiK and the ePA, which rely on standards like HL7 FHIR and IHE. However, their effectiveness depends not only on technical mandates but also on whether hospitals can technically, financially, and professionally implement them. The German Medical Association (DKG) demands legally binding technical and semantic standards, financial compensation for data provision, and diverse training data for AI. It highlights a funding gap because current funds promote systems without adequately covering infrastructure and operational costs. The article concludes that coordinated national strategies, mandatory standards, and secured operating cost financing are crucial, citing international examples.