title: Factuality levels of diagnoses in Swedish clinical text.
abstract: Different levels of knowledge certainty, or factuality levels, are expressed in clinical health record documentation. This information is currently not fully exploited, as the subtleties expressed in natural language cannot easily be machine analyzed. Extracting relevant information from knowledge-intensive resources such as electronic health records can be used for improving health care in general by e.g. building automated information access systems. We present an annotation model of six factuality levels linked to diagnoses in Swedish clinical assessments from an emergency ward. Our main findings are that overall agreement is fairly high (0.7/0.58 F-measure, 0.73/0.6 Cohen's κ, Intra/Inter). These distinctions are important for knowledge models, since only approx. 50% of the diagnoses are affirmed with certainty. Moreover, our results indicate that there are patterns inherent in the diagnosis expressions themselves conveying factuality levels, showing that certainty is not only dependent on context cues.
authors: Dept. of Computer and Systems Sciences (DSV), Stockholm University, Forum 100, SE-164 40 Kista, Sweden.
authors: Sumithra
authors: S
authors: Velupillai
authors: Hercules
authors: H
authors: Dalianis
authors: Maria
authors: M
authors: Kvist
mesh_terms: D000465:Algorithms; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D001330:Electronic Data Processing; D057286:Electronic Health Records; D004632:Emergency Medical Services; D006801:Humans; D007802:Language; D008490:Medical Informatics / Q000379:methods; D015588:Observer Variation; D015203:Reproducibility of Results; D012984:Software; D013548:Sweden; D009626:Terminology as Topic