Title
Assessing the readability of clinical documents in a document engineering environment
Abstract
Previous work has established that specific linguistic markers present in specialised medical documents (clinical guidelines) can be used to support their automatic structuring within a document engineering environment. This technique is commonly used by the French Health Authority (la Haute Autorite de Sante) during elaboration of clinical guidelines to improve the quality of the final document. In this paper, we explore the readability of clinical guidelines. We discuss a structural measure of document readability that exploits the ratio between these linguistic markers (deontic structures) and the remainder of the text. We describe an experiment in which a corpus of 10 French clinical guidelines is scored for structural readability. We correlate these scores with measures of textual cohesion (computed using latent semantic analysis) and the results of a readability survey performed by a panel of domain experts. Our results suggest an association between the density of deontic structures in a clinical guideline and its overall readability. This implies that certain generic readability measures can henceforth be utilised in our document engineering environment.
Year
DOI
Venue
2010
10.1145/1860559.1860585
ACM Symposium on Document Engineering
Keywords
Field
DocType
structural readability,document readability,document engineering environment,certain generic readability measure,clinical guideline,final document,readability survey,deontic structure,overall readability,clinical document,french clinical guideline,human factors,theory,cohesion,measurement,document processing,latent semantic analysis,languages,document engineering
Medical documents,Deontic logic,Information retrieval,Computer science,Document engineering,Readability,Artificial intelligence,Natural language processing,Latent semantic analysis,Guideline,Elaboration,Database
Conference
Citations 
PageRank 
References 
1
0.37
11
Authors
4
Name
Order
Citations
PageRank
Mark Truran128614.43
Gersende Georg26511.11
M. Cavazza31605161.76
Dong Zhou434225.99