WHERE THE BRIGHTEST MINDS in health and IT meet.

Semantic Data Analysis for Interoperability

February 22, 2017 — 11:30AM EST - 12:30PM EST
Orange County Convention Center
Session ID: 


We’ve spent the last decade working to ensure that we can interconnect our healthcare systems, treating the problem as a technical or connectivity issue. With data combined, we’re now seeing that the real problem is one of identifying or establishing shared meaning across all of that data: semantics. This presentation explains the various structural, syntactic and semantic issues that arise with healthcare data sharing and consolidation, and offers a strategy for data curation that enhances the semantic shared meaning of data across and among institutions.

Learning Objectives: 

  • Distinguish forms of data structuration along a continuum from syntactic to semantic that prevent interoperability, with an emphasis on differences in meaning and relationships
  • Explain why information is lost when free text notes and reports are forced into sets of discrete data elements in order to populate applications and databases
  • Differentiate incidental mismatches caused by the ways we’ve implemented different types of healthcare systems from semantic mismatches caused by gaps in medical and scientific knowledge
  • Describe how to annotate data content, allowing the semantic meanings found within the data to become discrete data even if the underlying data remains unstructured
  • Evaluate patient privacy risks from inadvertent disclosure of textual semantic data during data sharing, even when redaction has removed or blocked recognized identifying data


Clinical Informaticists
IT Professional
Management Engineer and Process Improvement Prof.





in health and IT meet.