RFID Modeling in Healthcare
M. Laskowski, Bryan Demianyk, G. Naigeboren, Blake W. Podaima, Marcia Friesen, R.D. McLeo · InTech eBooks · 2010
Increasingly, healthcare management systems include investment in and implementation of technology to track the status and movement of various entities within the healthcare environment, including patients, healthcare workers and physical assets. This is often a means of understanding patient flow, controlling inventory, tracking equipment usage, and thereby (ideally) assessing efficiencies in order to optimize resources and processes within that environment (Wang et al., 2006). The focus of this chapter is to highlight the contributions of RFID systems modeling, particularly in relation to an understanding of the nature and extent of system error that is often overlooked experientially. The healthcare environment was chosen as it is an increasingly complex and interesting application area for RFID, and in which a wide range of RFID-based applications and devices already exist and can be envisioned for the future. The insights gained through modeling provide a complementary set of data to those gained from the experiential knowledge of performance in existing installations. To that end, this chapter focuses on a case study of an agent-based model (ABM) of a hospital emergency department (ED), with extensions to modeling the provisioning of a real-time location system (RTLS) using RFID for patient tracking. To contextualize this work, Section 2 reviews conventional and emerging RFID applications in healthcare. Section 3 introduces the agent based modeling technique, invoked to investigate system performance in an application for RFID-enabled patient tracking within an ED. The ABM was developed as a decision support tool oriented towards optimizing RFID placement (minimizing uncertainty) for an actual ED where healthcare managers are considering the deployment of such systems. Section 4 outlines the ABM simulation results, with a particular focus on the nature and extent of system error and uncertainty – both spatial and temporal – that modeling illuminates. Section 5 discusses implementation strategies for an RFID RTLS system reflecting a Service Oriented Architecture approach that leverages existing software systems and focuses on being IP-centric and application- and device-agnostic.