Almost Clinical: Linguistic properties of synthetic electronic health records

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Authors: Serge Sharoff, John Baker, David Francis Hunt, Alan Simpson
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Abstract

This study evaluates the linguistic and clinical suitability of synthetic electronic health records in mental health. First, we describe the rationale and the methodology for creating the synthetic corpus. Second, we examine expressions of agency, modality, and information flow across four clinical genres (Assessments, Correspondence, Referrals and Care plans) with the aim to understand how LLMs grammatically construct medical authority and patient agency through linguistic choices. While LLMs produce coherent, terminology-appropriate texts that approximate clinical practice, systematic divergences remain, including registerial shifts, insufficient clinical specificity, and inaccuracies in medication use and diagnostic procedures. The results show both the potential and limitations of synthetic corpora for enabling large-scale linguistic research otherwise impossible with genuine patient records.

Fields of Study & Subjects

Electronic Health Records Systems Machine Learning in Healthcare Interpreting and Communication in Healthcare

Publication details

Journal / source
arXiv (Cornell University)
Publication date
3 January 2026
Document type
Preprint