Decision support environment for medical product safety surveillance

Taxiarchis Botsis, Christopher Jankosky, Deepa Arya, Kory Kreimeyer, Matthew Foster, Abhishek Pandey, Wei Wang, Guangfan Zhang, Richard Forshee, Ravi Goud, David Menschik, Mark Walderhaug, Emily Jane Woo, John Scott

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


We have developed a Decision Support Environment (DSE) for medical experts at the US Food and Drug Administration (FDA). The DSE contains two integrated systems: The Event-based Text-mining of Health Electronic Records (ETHER) and the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment (PANACEA). These systems assist medical experts in reviewing reports submitted to the Vaccine Adverse Event Reporting System (VAERS) and the FDA Adverse Event Reporting System (FAERS). In this manuscript, we describe the DSE architecture and key functionalities, and examine its potential contributions to the signal management process by focusing on four use cases: the identification of missing cases from a case series, the identification of duplicate case reports, retrieving cases for a case series analysis, and community detection for signal identification and characterization.

Original languageEnglish (US)
Pages (from-to)354-362
Number of pages9
JournalJournal of Biomedical Informatics
StatePublished - Dec 1 2016
Externally publishedYes


  • Information retrieval
  • Natural language processing
  • Network analysis
  • Post-marketing surveillance
  • Text mining

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics


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