Decision support environment for medical product safety surveillance

J Biomed Inform. 2016 Dec:64:354-362. doi: 10.1016/j.jbi.2016.07.023. Epub 2016 Jul 28.

Abstract

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.

Keywords: Information retrieval; Natural language processing; Network analysis; Post-marketing surveillance; Text mining.

MeSH terms

  • Adverse Drug Reaction Reporting Systems*
  • Data Mining*
  • Decision Support Techniques*
  • Environment
  • Humans
  • Research Report
  • United States
  • United States Food and Drug Administration*