A dynamic, data-driven, decision support system for emergency medical services

  • Authors:
  • Mark Gaynor;Margo Seltzer;Steve Moulton;Jim Freedman

  • Affiliations:
  • School of Management, Boston University, Boston;Division of Engineering and Applied Sciences, Harvard University;School of Medicine, Boston University, Boston, MA;School of Management, Boston University, Boston

  • Venue:
  • ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
  • Year:
  • 2005

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Abstract

In crisis, decisions must be made in human perceptual timeframes under pressure to respond to dynamic uncertain conditions. To be effective management must have access to real time environmental data in a form that can be immediately understood and acted upon. The emerging computing model of Dynamic Data-Driven Application Systems (DDDAS) fits well in crisis situations where rapid decision-making is essential. We explore the value of a DDDAS (iRevive) in support of emergency medical treatment decisions in response to a crisis. This complex multi-layered dynamic environment both feeds and responds to an ever-changing stream of real-time data that enables coordinated decision-making by heterogeneous personnel across a wide geography at the same time. This complex multi-layered dynamic environment both feeds and responds to an ever-changing stream of real-time data that enables coordinated decision-making by heterogeneous personnel across a wide geography at the same time.