Professional language in Swedish clinical text: Linguistic characterization and comparative studies

• Published in: Nordic journal of linguistics Vol. 37; no. 2; pp. 297 - 323
• Main Authors: Smith, Kelly, Megyesi, Beata, Velupillai, Sumithra, Kvist, Maria
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 01.10.2014
• Subjects: Abbreviations; clinical text; comparative register analysis; Computational Linguistics; Computer Generated Language Analysis; Discourse Functions; doctor's daily notes; electronic health records; Function words; Languages; Linguistics; Medical Language; medical terminology; part-of-speech tagging; radiology reports; Scientific Technical Language; Sentence Structure; Statistical Analysis; Swedish; Swedish language; Tagging; Verbs; Sweden; radiology reports; doctor’s daily notes; part-of-speech tagging; medical terminology; clinical text; comparative register analysis; electronic health records
• ISSN: 0332-5865; 1502-4717; 1502-4717
• DOI: 10.1017/S0332586514000213

This study investigates the linguistic characteristics of Swedish clinical text in radiology reports and doctor's daily notes from electronic health records (EHRs) in comparison to general Swedish and biomedical journal text. We quantify linguistic features through a comparative register analysis to determine how the free text of EHRs differ from general and biomedical Swedish text in terms of lexical complexity, word and sentence composition, and common sentence structures. The linguistic features are extracted using state-of-the-art computational tools: a tokenizer, a part-of-speech tagger, and scripts for statistical analysis. Results show that technical terms and abbreviations are more frequent in clinical text, and lexical variance is low. Moreover, clinical text frequently omit subjects, verbs, and function words resulting in shorter sentences. Clinical text not only differs from general Swedish, but also internally, across its sub-domains, e.g. sentences lacking verbs are significantly more frequent in radiology reports. These results provide a foundation for future development of automatic methods for EHR simplification or clarification.