Semi-Automatic Mark-Up and UMLS Annotation of Clinical Guidelines

Clinical guidelines and clinical pathways are accepted and proven instruments for quality assurance and process optimization in the healthcare domain. To derive clinical pathways from clinical guidelines, the imprecise, non-formalized abstract guidelines must be formalized. The transfer of evidence-based knowledge (clinical guidelines) to care processes (clinical pathways) is not straightforward due to different information contents and semantical constructs. A complex step within this formalization process is the mark-up step and annotation of the text passages to terminologies. The Unified Medical Language System (UMLS) provides a common reference terminology as well as the semantic link for combining the clinical pathways to patient-specific information. This paper proposes a semi-automated mark-up and UMLS annotation for clinical guidelines by using natural language processing techniques. The algorithm has been tested and evaluated using a German breast cancer guideline.