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VIDAL assembles, collates, links, and distributes information describing medicines and their therapeutic properties including indications, contraindication, side-effects, and usage guidelines.  The information is published in an electronic document form, and as part of a Decision Support Module that is integrated into a number of clinical information systems used in both hospitals and physician offices during the authoring of prescriptions.

 Although the system has proven to be very useful, it is limited by its heavy reliance on free text rather than computable concepts, a fact that, in turn, places limitations on search specificity and granularity in the context of individual patient queries.

 To address these limitations, we are migrating to a more formal, computable semantic infrastructure based on use of Semantic Web standards, and are considering utilizing SNOMED in this infrastructure because we believe that the concept-based content of SNOMED can add considerable value to the prescription-writing process using linked data structures such as those developed by VIDAL.

 We will discuss our reasons – both Pro and Con – regarding the use of SNOMED as a foundational component for our semantic drug database infrastructure.  Included will be our observations on the importance of four critical success factors:  i) Availability of SNOMED in local language; ii) an IHTSDO-certified representation of SNOMED in RDF; iii) IHTSDO-certified integration of IDMP semantics into SNOMED; and iv) a decision by National Health Policy to encourage the use of structured SNOMED coding of clinical context in CPOEs.


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