Development of agent-based models for healthcare: applications and critique
| dc.contributor.author | Demianyk, Bryan C.P. | |
| dc.contributor.examiningcommittee | Ferens, Ken (Electrical and Computer Engineering) Eskicioglu, Rasit (Computer Science) | en_US |
| dc.contributor.supervisor | McLeod, Bob (Electrical and Computer Engineering) Friesen, Marcia (Electrical and Computer Engineering) | en_US |
| dc.date.accessioned | 2016-01-13T17:09:42Z | |
| dc.date.available | 2016-01-13T17:09:42Z | |
| dc.date.issued | 2011 | en_US |
| dc.date.issued | 2010 | en_US |
| dc.degree.discipline | Electrical and Computer Engineering | en_US |
| dc.degree.level | Master of Science (M.Sc.) | en_US |
| dc.description.abstract | Agent-based modeling (ABM) is a modeling and simulation paradigm well-suited to social systems where agents interact and have some degree of autonomy. In their most basic sense, ABMs consist of agents (generally, individuals) interacting in an environment according to a set of behavioural rules. The foundational premise and the conceptual depth of ABM is that simple rules of individual behaviour will aggregate to illuminate complex and/or emergent group-level phenomena that are not specifically encoded by the modeler and that cannot be predicted or explained by the agent-level rules. In essence, ABM has the potential to reveal a whole that is greater than the sum of its parts. In this thesis, ABMs have been utilized as a modeling framework for three specific healthcare applications, including: • the development of an ABM of an emergency department within a hospital allowing the modeling of contact-based infectious diseases such as influenza, and simulating various mitigation strategies; • the development of an ABM to model the effectiveness of a real-time location system (RTLS) using radio frequency identification (RFID) in an emergency department, used for patient tracking as one measure of hospital efficiency; and, • the development of an ABM to test strategies for disaster preparedness (high volume, high risk patients) using a fictitious case of zombies in an emergency department. Although each ABM was purposeful and meaningful for its custom application, each ABM also represented an iteration toward the development of a generic ABM framework. Finally, a thorough critique of ABMs and the modifications required to create a more robust framework are provided. | en_US |
| dc.description.note | February 2016 | en_US |
| dc.identifier.citation | M. Laskowski, B.C.P. Demianyk, J. Witt, S.N. Mukhi, M.R. Friesen, and R.D. McLeod. "Agent-based modeling of the spread of influenza-like illness in an emergency department: a simulation study," IEEE Transactions on Information Technology in Biomedicine, vol. 15, no. 6, pp. 877-889, 2011. | en_US |
| dc.identifier.citation | M. Laskowski, B.C.P. Demianyk, G. Naigeboren, B.W. Podaima, M.R. Friesen, and R.D. McLeod. (2010). "RFID Modeling in Healthcare," in Sustainable Radio Frequency Identification Solutions [Online], C. Turcu, Ed. InTech. Available http://www.intechopen.com/books/sustainable-radio-frequency-identificationsolutions/rfid-modeling-in-healthcare. | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/31049 | |
| dc.language.iso | eng | en_US |
| dc.publisher | IEEE | en_US |
| dc.publisher | InTech | en_US |
| dc.rights | open access | en_US |
| dc.subject | ABM | en_US |
| dc.subject | modeling and simulation | en_US |
| dc.subject | healthcare modeling | en_US |
| dc.subject | agent-based modeling | en_US |
| dc.title | Development of agent-based models for healthcare: applications and critique | en_US |
| dc.type | master thesis | en_US |
| local.subject.manitoba | yes | en_US |