title: A meta-data model for knowledge in decision support systems.
abstract: Clinical decision support such as alerts, reminders and guidance are driven by rules often distributed among a variety of applications in a healthcare information system. Due to the increasing size of rule bases, there is a growing need to manage this dispersed knowledge in an integrated environment. A system for management of executable clinical knowledge such as rules should (1) assist in the development and maintenance of rules throughout the rules' life-cycles, (2) support search and retrieval of rules in the knowledge base (e.g., rules for diabetes, rules created by a particular individual), and (3) facilitate the analyses of rules in the knowledge base (e.g., identify rules not updated in the last year). In order to create such a clinical knowledge management system it is necessary to model the meta-data of rules. There have been efforts to document meta-data about rules within the Arden Syntax Medical Logical Modules' project. However, the maintenance and library categories in that project allow mainly free-text information about a rule. We have created a comprehensive meta-data structure and taxonomy for describing clinical rules that supports the features of a knowledge management system. We also tested this model using a representative set of rules.
authors.affiliation: Brigham and Women's Hospital, Boston, MA, USA.
authors.forename: Yaron
authors.initials: Y
authors.lastname: Denekamp
authors.forename: Aziz A
authors.initials: AA
authors.lastname: Boxwala
authors.forename: Gilad
authors.initials: G
authors.lastname: Kuperman
authors.forename: Blackford
authors.initials: B
authors.lastname: Middelton
authors.forename: Robert A
authors.initials: RA
authors.lastname: Greenes
mesh_terms: D001185:Artificial Intelligence; D002965:Classification; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D016247:Information Storage and Retrieval