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Using features of Arden Syntax with object-oriented medical data models for guideline modeling
1Stanford Medical Informatics, Stanford University School of Medicine, Stanford, CA, USA.
Abstract:
Computer-interpretable guidelines (CIGs) can deliver patient-specific decision support at the point of care. CIGs base their recommendations on eligibility and decision criteria that relate medical concepts to patient data. CIG models use expression languages for specifying these criteria, and define models for medical data to which the expressions can refer. In developing version 3 of the GuideLine Interchange Format (GLIF3), we used existing standards as the medical data model and expression language. We investigated the object-oriented HL7 Reference Information Model (RIM) as a default data model. We developed an expression language, called GEL, based on Arden Syntax's logic grammar. Together with other GLIF constructs, GEL reconciles incompatibilities between the data models of Arden Syntax and the HL7 RIM. These incompatibilities include Arden's lack of support for complex data types and time intervals, and the mismatch between Arden's single primary time and multiple time attributes of the HL7 RIM.
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