Text Generation in Clinical Medicine – a Review

Abstract

Summary Objectives: This article aims at an analysis of ways of producing documents (such as findings or referral letters) in clinical medicine. Special emphasis is given to the question of whether the field of “Natural Language Generation” (NLG) can provide new approaches to ameliorate the current situation. Methods: In order to assess the currently used techniques in text production, an analysis of commercially available systems was performed in addition to an extensive review of the literature. The sketch of current NLG approaches is also based on a literature review.To estimate the applicability of several techniques to clinical documents, a typology of documents in clinical medicine was developed, based on rhetorical structure theory, speech act theory and certain recurrent linguistic phenomena exposed in the said documents. Results: Current ways of producing text for documents in medicine are less than optimal in several respects. The field of NLG draws on the idea of generating text from a conceptual representation of not only certain facts, but also knowledge about how to express them via (written) language.Unfortunately, NLG does not yet offer “ready-to-run” solutions for the automatic production of most of the document types in the given typology.It seems, however, highly plausible that the demands of medical informatics for these kinds of systems will be satisfiable as NLG matures. Conclusions: NLG offers a promising way of generating text for clinical documents, a problem of enormous economical importance. The medical informatics community should therefore commit itself to the idea of NLG in medicine.