Institutional Agent Based Models for Healthcare Applications (Simstitution)

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The objective of my research program is to further develop agent-based modeling (ABM) techniques in combination with data prospecting/mining/fusion. A further objective is to validate ABMs with real data - as a compelling methodology with healthcare modeling as the main application area. Many of the ideas for data mining are novel, in that data is becoming more readily available as a consequence of the presence of tracking technologies and on-line information as well as the recognition of these sources as input into ABMs. ABMs require a strong background in technologies that offer data mining opportunities, understanding of ABM and its benefits, and of statistical inference. I have helped develop ABMs for community-level epidemic modeling, as well as institution-level models for assessing patient access policy in EDs and modeling of nosocomial infection and influenza-like-illness. This application continues development of ABMs for use within an institution. Over the longer term, I am actively pursuing research to augment ABM with diverse empirical data. A prototype system is being developed, using Smartphones as proximity location systems to provide real data to an agent-based platform for improving ED operations. In a second instance, we are working with Emergency Department Information System data to be used as empirical inputs to both our community- and institution-level agent based models. In a third instance I will be using GPUs to improve the performance of the ABMs we are developing. This suite of modeling tools is under development in my lab, and currently engages four graduate students and one summer student. Efforts to date have demonstrated that the opportunities for the training of HQP are significant. By placing an emphasis on data, this research retains a particular affinity to computer engineering, both in utility and in the potential for computer engineering to make unique and significant contributions to this research area. While the outlined approach is highly suited to computer engineering, the chosen application area of healthcare modeling is also of particular significance as these are unsolved problems with substantial public health and health policy benefits.