title: How can information extraction ease formalizing treatment processes in clinical practice guidelines? A method and its evaluation.
abstract: OBJECTIVE
  Formalizing clinical practice guidelines (CPGs) for a subsequent computer-supported processing is a challenging, but burdensome and time-consuming task. Existing methods and tools to support this task demand detailed medical knowledge, knowledge about the formal representations, and a manual modeling. Furthermore, formalized guideline documents mostly fall far short in terms of readability and understandability for the human domain modeler.
  
  
  METHODS
  We propose a new multi-step approach using information extraction methods to support the human modeler by both automating parts of the modeling process and making the modeling process traceable and comprehensible. This paper addresses the first steps to obtain a representation containing processes which is independent of the final guideline representation language.
  
  
  RESULTS
  We have developed and evaluated several heuristics without the need to apply natural language understanding and implemented them in a framework to apply them to several guidelines from the medical subject of otolaryngology. Findings in the evaluation indicate that using semi-automatic, step-wise information extraction methods are a valuable instrument to formalize CPGs.
  
  
  CONCLUSIONS
  Our evaluation shows that a heuristic-based approach can achieve good results, especially for guidelines with a major portion of semi-structured text. It can be applied to guidelines irrespective to the final guideline representation format.
authors.affiliation: Vienna University of Technology, Institute of Software Technology & Interactive Systems, Favoritenstrasse 9-11/188, A-1040 Vienna, Austria. kaiser@ifs.tuwien.ac.at
authors.forename: Katharina
authors.initials: K
authors.lastname: Kaiser
authors.forename: Cem
authors.initials: C
authors.lastname: Akkaya
authors.forename: Silvia
authors.initials: S
authors.lastname: Miksch
mesh_terms: D001185:Artificial Intelligence; D001331:Automation; D003201:Computers; D006801:Humans; D008962:Models, Theoretical; D017410:Practice Guidelines as Topic / Q000592:standards*; D013812:Therapeutics / Q000379:methods* / Q000592:standards* / Q000639:trends