Project Lead: Judit Erdös
Authors: Judit Erdös, Lena Grabenhofer
Publication: February 2026
Language: English (with German summary)
Clinical documentation is a major driver of administrative burden and workload in hospitals. AI-enabled digital health technologies (DHTs) are increasingly promoted as tools to support or partially automate documentation tasks, with the potential to reduce clinician burden. This review provides a systematic overview of current AI applications for clinical documentation, including AI scribes, text structuring, AI-generated documentation, patient-friendly summaries, error detection, and automated billing code assignment. Based on a systematic literature search including seven reviews and 200 primary studies, the evidence shows heterogeneous and context-dependent performance. While clinicians often report high satisfaction; accuracy, completeness, and productivity gains vary across use cases, and human oversight remains essential. Evidence on organisational impacts, implementation requirements, and long-term performance is limited. A structured, risk-based approach with appropriate governance is required before routine implementation in hospital settings.