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
207C
Session ID: 
171

Description

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

Audience: 

Clinical Informaticists
IT Professional
Management Engineer and Process Improvement Prof.

Speaker(s): 

Level: 

Intermediate

WHERE THE BRIGHTEST MINDS

in health and IT meet.

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