Decision support, knowledge representation and management: structuring knowledge for better access. Findings from the Yearbook 2008 Section on Decision Support, Knowledge Representation and Management.
OBJECTIVE
To summarize current outstanding research in the field of decision support, knowledge representation and management.


METHODS
Synopsis of the articles selected for the IMIA Yearbook 2008.


RESULTS
Five papers from international peer reviewed journals have been selected for the section on decision support, knowledge representation and management. They address a wide range of topics such as the recognition and extraction of negation or time from clinical narratives, the use of ontological elements to reduce the complexity of natural language processing applications or to strengthen the precision of document retrieval as well as the benefits of integrating clinical decision support within computer provider order entry.


CONCLUSIONS
The best paper selection brings to light that whatever the methodological approach used in decision support, knowledge representation and management, all applications benefit from manipulating information that is expressed in both a meaningful and structured way. In order to combine the flexibility and expressive power of natural language with the computational tractability of structured data, the electronic health record based on structured narrative offers new perspectives.
Rassinoux
A-M
AM
University Hospitals of Geneva, Service of Medical Informatics, Unit of Clinical Informatics, 24, rue Micheli-du-Crest, CH-1211 Geneva 14, Switzerland. anne-marie.rassinoux@sim.hcuge.ch
D003658:Decision Making, Computer-Assisted; D003661:Decision Support Techniques; D019451:Information Management; D016247:Information Storage and Retrieval; D050316:Medical Order Entry Systems; D009323:Natural Language Processing; D018875:Vocabulary, Controlled