A Dynamic, Data-Driven, Decision Support System for Emergency Medical Services

Abstract

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.

Decision Support Systems in Anesthesia, Emergency Medicine and Intensive Care Medicine

“…However, the studies are somewhat inconclusive: whereas DSSs have very successfully been implemented in the pre-hospital care system, making triage and organization far easier than without them, their implementation in the hospital based emergency care system is somewhat disappointing. For the pre-hospital care system, the iRevive EMT application is a very good example of successful implementation of a DSS in a complex environment (Gaynor et al, 2005). It is designed as a network of wireless, handheld computers, with wireless patient location and vital sign sensors, connected to an ambulance base station, and a central command center.…”

Managing social media uncertainty to support the decision making process during Emergencies

“…A more extended use of social media is as a mass communication channel, in order to inform large numbers of stakeholders at once (Ki & Nekmat, 2014;Muralidharan et al, 2011;Stříteský, Stránská, & Drábik, 2015;Utz, Schultz, & Glocka, 2013). Additionally, it provides a unique opportunity to collect and make use of large amounts of real-time data (Big Data), which is paramount in decision support systems and any emergency management decision-making process (Gaynor, Seltzer, & Moulton, 2005;Kamel Boulos et al, 2011;U.S. Department of Homeland Security, 2014).…”

“…In 2013 during the 'Big Data and Disaster Management JST / NSF Joint Workshop' , veracity 1 was declared as one of the biggest challenges for the correct integration of big data within emergency management. Ideally, verification should be achieved in real-time to support decisions made during emergencies (Gaynor et al, 2005;Kamel Boulos et al, 2011). Due to limitations on resource availability, the importance of real-time data verification increases after the emergency takes place; and therefore during the response phase (Computing Community Consortium, 2012;Radisch & Jacobzone, 2010).…”

An Architecture for Local Decision Support in Ad Hoc Sensor Networks

“…Emerging field information and automation technologies provide the construction industry great opportunities to improve performance Applications include: laser devices mounted on equipments to prevent vehicle collision (Teizer et al 2005), RFIDs and GPS attached onto material components for materials management (Jaselskis and El-Misalami 2003;Song et al 2005), laser scanning devices or combination of GPS and smart sensors deployed on moving vehicles for collision detection (Riaz et al 2006;Teizer et al 2005), sensors equipped on construction equipment for danger alert to laborers (Nuntasunti and Bernold 2002), mobile devices (e.g., PDA and tablet) with embedded software and wireless communication capacity for inventory management and decision support based on collected data (COMIT 2003;Gaynor et al 2005). These applications, among others, are constituent components of a vision for the "Intelligent Job Site" (FIATECH 2003).…”