AI-Assisted Clinical Documentation in Routine Danish General Practice: Quantitative Pre-Post Study.

Authors

Louise Nørgaard Olsen, Philipp Harbig, Anna Bay Laurberg, Jacob Laurberg, Morten Haaning Charles

Published in

JMIR human factors. Volume 13. Pages e94431. Oct 02, 2026. Epub Oct 02, 2026.

Abstract

Administrative workload in general practice limits time for direct patient care. AI-assisted documentation has been proposed as a way to reduce the documentation burden, but evidence from routine primary care settings remains limited.
This study aimed to evaluate general practitioners' (GPs) acceptance of AI-assisted documentation and its association with documentation time and clinical note quality in routine Danish general practice.
We conducted a quantitative pragmatic pre-post quality improvement evaluation in Danish general practice. A total of 20 GPs documented 239 consultations before and 236 consultations after implementation of an AI-assisted documentation system. Documentation quality, structure, clinical clarity, and documentation time categories were self-assessed using standardized audit forms completed immediately after each consultation. Technology acceptance and usability were assessed using the technology acceptance model (TAM) and the System Usability Scale (SUS).
Self-assessed documentation structure increased from 3.99 to 4.45, while self-reported documentation time categories decreased from 2.85 to 2.29. Technology acceptance and usability were high (TAM domain means 3.76-4.19; SUS mean 77.5). GP-level paired analyses showed moderate improvements in structure and clarity and a reduction in documentation time. Combined blinded external assessments showed higher postimplementation scores for quality, structure, and clinical clarity, although reviewer-specific ratings diverged, and interrater reliability was low. The association between documentation time and perceived quality was negligible. TAM and SUS indicated high clinician acceptance.
AI-assisted documentation was associated with lower self-reported documentation time categories while maintaining or modestly improving perceived clinical note quality. These findings support the feasibility of AI-assisted documentation in primary care, while highlighting the need for controlled studies with objective time measurement and longer follow-up.

PMID:
42826248
Bibliographic data and abstract were imported from PubMed on 03 Oct 2026.

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